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Sample records for ratio predict improvement

  1. An Improved Optimal Slip Ratio Prediction considering Tyre Inflation Pressure Changes

    Directory of Open Access Journals (Sweden)

    Guoxing Li

    2015-01-01

    Full Text Available The prediction of optimal slip ratio is crucial to vehicle control systems. Many studies have verified there is a definitive impact of tyre pressure change on the optimal slip ratio. However, the existing method of optimal slip ratio prediction has not taken into account the influence of tyre pressure changes. By introducing a second-order factor, an improved optimal slip ratio prediction considering tyre inflation pressure is proposed in this paper. In order to verify and evaluate the performance of the improved prediction, a cosimulation platform is developed by using MATLAB/Simulink and CarSim software packages, achieving a comprehensive simulation study of vehicle braking performance cooperated with an ABS controller. The simulation results show that the braking distances and braking time under different tyre pressures and initial braking speeds are effectively shortened with the improved prediction of optimal slip ratio. When the tyre pressure is slightly lower than the nominal pressure, the difference of braking performances between original optimal slip ratio and improved optimal slip ratio is the most obvious.

  2. Physiologically-based, predictive analytics using the heart-rate-to-Systolic-Ratio significantly improves the timeliness and accuracy of sepsis prediction compared to SIRS.

    Science.gov (United States)

    Danner, Omar K; Hendren, Sandra; Santiago, Ethel; Nye, Brittany; Abraham, Prasad

    2017-04-01

    Enhancing the efficiency of diagnosis and treatment of severe sepsis by using physiologically-based, predictive analytical strategies has not been fully explored. We hypothesize assessment of heart-rate-to-systolic-ratio significantly increases the timeliness and accuracy of sepsis prediction after emergency department (ED) presentation. We evaluated the records of 53,313 ED patients from a large, urban teaching hospital between January and June 2015. The HR-to-systolic ratio was compared to SIRS criteria for sepsis prediction. There were 884 patients with discharge diagnoses of sepsis, severe sepsis, and/or septic shock. Variations in three presenting variables, heart rate, systolic BP and temperature were determined to be primary early predictors of sepsis with a 74% (654/884) accuracy compared to 34% (304/884) using SIRS criteria (p < 0.0001)in confirmed septic patients. Physiologically-based predictive analytics improved the accuracy and expediency of sepsis identification via detection of variations in HR-to-systolic ratio. This approach may lead to earlier sepsis workup and life-saving interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Predicted versus observed cosmic-ray-produced noble gases in lunar samples: improved Kr production ratios

    International Nuclear Information System (INIS)

    Regnier, S.; Hohenberg, C.M.; Marti, K.; Reedy, R.C.

    1979-01-01

    New sets of cross sections for the production of krypton isotopes from targets of Rb, Sr, Y, and Zr were constructed primarily on the bases of experimental excitation functions for Kr production from Y. These cross sections were used to calculate galactic-cosmic-ray and solar-proton production rates for Kr isotopes in the moon. Spallation Kr data obtained from ilmenite separates of rocks 10017 and 10047 are reported. Production rates and isotopic ratios for cosmogenic Kr observed in ten well-documented lunar samples and in ilmenite separates and bulk samples from several lunar rocks with long but unknown irradiation histories were compared with predicted rates and ratios. The agreements were generally quite good. Erosion of rock surfaces affected rates or ratios for only near-surface samples, where solar-proton production is important. There were considerable spreads in predicted-to-observed production rates of 83 Kr, due at least in part to uncertainties in chemical abundances. The 78 Kr/ 83 Kr ratios were predicted quite well for samples with a wide range of Zr/Sr abundance ratios. The calculated 80 Kr/ 83 Kr ratios were greater than the observed ratios when production by the 79 Br(n,γ) reaction was included, but were slightly undercalculated if the Br reaction was omitted; these results suggest that Br(n,γ)-produced Kr is not retained well by lunar rocks. The productions of 81 Kr and 82 Kr were overcalculated by approximately 10% relative to 83 Kr. Predicted-to-observed 84 Kr/ 83 ratios scattered considerably, possibly because of uncertainties in corrections for trapped and fission components and in cross sections for 84 Kr production. Most predicted 84 Kr and 86 Kr production rates were lower than observed. Shielding depths of several Apollo 11 rocks were determined from the measured 78 Kr/ 83 Kr ratios of ilmenite separates. 4 figures, 5 tables

  4. Asthma Medication Ratio Predicts Emergency Depart...

    Data.gov (United States)

    U.S. Department of Health & Human Services — According to findings reported in Asthma Medication Ratio Predicts Emergency Department Visits and Hospitalizations in Children with Asthma, published in Volume 3,...

  5. Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study

    Science.gov (United States)

    Ahn, Song Vogue; Baik, Soon Koo; Cho, Youn zoo; Koh, Sang Baek; Huh, Ji Hye; Chang, Yoosoo; Sung, Ki-Chul; Kim, Jang Young

    2016-01-01

    Aims The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study. Material and Methods The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40–70 years, who participated from 2005–2008 (baseline) without metabolic syndrome and were followed up from 2008–2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods. Results During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422–0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124–0.337, Pmetabolic syndrome and had incremental predictive value for incident metabolic syndrome. PMID:27560931

  6. PROFITABILITY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    Daniel BRÎNDESCU – OLARIU

    2016-07-01

    Full Text Available The current study evaluates the potential of the profitability ratio in predicting corporate bankruptcy. The research is focused on Romanian companies, with the targeted event being represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were conducted over 2 paired samples of 1176 Romanian companies. The methodology employed in evaluating the potential of the profitability ratio was based on the Area Under the ROC Curve (0.663 and the general accuracy ensured by the ratio (62.6% out-of-sample accuracy. The results confirm the practical utility of the profitability ratio in the prediction of bankruptcy and thus validate the need for further research focused on developing a methodology of analysis.

  7. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  8. SOLVENCY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

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    Daniel BRÎNDESCU–OLARIU

    2016-08-01

    Full Text Available The current study evaluates the potential of the solvency ratio in predicting corporate bankruptcy. The research is focused on Romania and, in particular, on Timis County. The interest for the solvency ratio was based on the recommendations of the scientific literature, as well as on the availability of information concerning its values to all stakeholders. The event on which the research was focused was represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were performed over 2 paired samples of 1176 companies in total. The methodology employed in evaluating the potential of the solvency ratio was based on the Area Under the ROC Curve (0.646 and the general accuracy ensured by the ratio (64.5% out-of-sample accuracy. The results confirm the practical utility of the solvency ratio in the prediction of bankruptcy.

  9. Prediction of renovascualar hypertension by captopril-stimulated renal vein renin ratios

    International Nuclear Information System (INIS)

    Roubidoux, M.A.; Dunnick, N.R.; Svetkey, L.; Newmann, G.E.; Cohan, R.H.; Kadir, S.; Klotman, P.

    1989-01-01

    The authors have prospectively studied 114 patients with suspected renovascular hypertension to determine whether captopril-stimulated, selective, renal vein renin ratios could be used to predict renovascular hypertension. As judged by the response to correction of renal artery lesions, 14 patients had renovascular hypertension, and renal vein renin ratios were significant in eight (sensitivity 57%). Overall, the positive predictive value of renal vein renin ratios was 33%, and the negative predictive value was 89%. The authors concluded that, in patients with renal artery stenosis, renal vein renin ratios predict neither the need for conventional arteriography nor potential benefit from the correction of vascular insufficiency

  10. Fetal omphalocele ratios predict outcomes in prenatally diagnosed omphalocele.

    Science.gov (United States)

    Montero, Freddy J; Simpson, Lynn L; Brady, Paula C; Miller, Russell S

    2011-09-01

    The objective of the study was to evaluate whether ratios considering omphalocele diameter relative to fetal biometric measurements perform better than giant omphalocele designation at predicting inability to achieve neonatal primary surgical closure. Cases of fetal omphalocele that underwent evaluation between May 2003 and July 2010 were identified. Inclusion was restricted to live births with plan for postnatal repair. Omphalocele diameter upon antenatal ultrasound was compared with abdominal circumference, femur length, and head circumference, yielding the respective omphalocele (O)/abdominal circumference (AC), O/femur length (FL), and O/head circumference (HC) ratios. The absolute measurements were used to classify giant lesions. Omphalocele ratios and giant omphalocele designations were evaluated as predictors of inability to achieve primary repair. Among 25 included cases, staged or delayed closure occurred in 52%. With an optimal cutoff of 0.21 or greater, O/HC best predicted the primary outcome (sensitivity, 84.6%; specificity, 58.3%; odds ratio, 7.7). The O/HC of 0.21 or greater outperformed giant designations. The O/HC of 0.21 or greater best predicted staged or delayed omphalocele closure. Giant omphalocele designation, regardless of definition, poorly predicted outcome. Copyright © 2011 Mosby, Inc. All rights reserved.

  11. Serial binary interval ratios improve rhythm reproduction

    Directory of Open Access Journals (Sweden)

    Xiang eWu

    2013-08-01

    Full Text Available Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8, non-binary integer (1:3:5:6, and non-integer (1:2.3:5.3:6.4 ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

  12. Serial binary interval ratios improve rhythm reproduction.

    Science.gov (United States)

    Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

    2013-01-01

    Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

  13. Cardiothoracic ratio for prediction of left ventricular dilation: a systematic review and pooled analysis.

    Science.gov (United States)

    Loomba, Rohit S; Shah, Parinda H; Nijhawan, Karan; Aggarwal, Saurabh; Arora, Rohit

    2015-03-01

    Increased cardiothoracic ratio noted on chest radiographs often prompts concern and further evaluation with additional imaging. This study pools available data assessing the utility of cardiothoracic ratio in predicting left ventricular dilation. A systematic review of the literature was conducted to identify studies comparing cardiothoracic ratio by chest x-ray to left ventricular dilation by echocardiography. Electronic databases were used to identify studies which were then assessed for quality and bias, with those with adequate quality and minimal bias ultimately being included in the pooled analysis. The pooled data were used to determine the sensitivity, specificity, positive predictive value and negative predictive value of cardiomegaly in predicting left ventricular dilation. A total of six studies consisting of 466 patients were included in this analysis. Cardiothoracic ratio had 83.3% sensitivity, 45.4% specificity, 43.5% positive predictive value and 82.7% negative predictive value. When a secondary analysis was conducted with a pediatric study excluded, a total of five studies consisting of 371 patients were included. Cardiothoracic ratio had 86.2% sensitivity, 25.2% specificity, 42.5% positive predictive value and 74.0% negative predictive value. Cardiothoracic ratio as determined by chest radiograph is sensitive but not specific for identifying left ventricular dilation. Cardiothoracic ratio also has a strong negative predictive value for identifying left ventricular dilation.

  14. PROFITABILITY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    OpenAIRE

    Daniel BRÎNDESCU – OLARIU

    2016-01-01

    The current study evaluates the potential of the profitability ratio in predicting corporate bankruptcy. The research is focused on Romanian companies, with the targeted event being represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were conducted over 2 paired samples of 1176 Romanian companies. The methodology employed in evaluating the potential of the profitability ratio was based on the Area Under the ROC Curve (0.663...

  15. Predictive value of C-reactive protein/albumin ratio in acute pancreatitis.

    Science.gov (United States)

    Kaplan, Mustafa; Ates, Ihsan; Akpinar, Muhammed Yener; Yuksel, Mahmut; Kuzu, Ufuk Baris; Kacar, Sabite; Coskun, Orhan; Kayacetin, Ertugrul

    2017-08-15

    Serum C-reactive protein (CRP) increases and albumin decreases in patients with inflammation and infection. However, their role in patients with acute pancreatitis is not clear. The present study was to investigate the predictive significance of the CRP/albumin ratio for the prognosis and mortality in acute pancreatitis patients. This study was performed retrospectively with 192 acute pancreatitis patients between January 2002 and June 2015. Ranson scores, Atlanta classification and CRP/albumin ratios of the patients were calculated. The CRP/albumin ratio was higher in deceased patients compared to survivors. The CRP/albumin ratio was positively correlated with Ranson score and Atlanta classification in particular and with important prognostic markers such as hospitalization time, CRP and erythrocyte sedimentation rate. In addition to the CRP/albumin ratio, necrotizing pancreatitis type, moderately severe and severe Atlanta classification, and total Ranson score were independent risk factors of mortality. It was found that an increase of 1 unit in the CRP/albumin ratio resulted in an increase of 1.52 times in mortality risk. A prediction value about CRP/albumin ratio >16.28 was found to be a significant marker in predicting mortality with 92.1% sensitivity and 58.0% specificity. It was seen that Ranson and Atlanta classification were higher in patients with CRP/albumin ratio >16.28 compared with those with CRP/albumin ratio ≤16.28. Patients with CRP/albumin ratio >16.28 had a 19.3 times higher chance of death. The CRP/albumin ratio is a novel but promising, easy-to-measure, repeatable, non-invasive inflammation-based prognostic score in acute pancreatitis. Copyright © 2017 The Editorial Board of Hepatobiliary & Pancreatic Diseases International. Published by Elsevier B.V. All rights reserved.

  16. CD4/CD8 Ratio and KT Ratio Predict Yellow Fever Vaccine Immunogenicity in HIV-Infected Patients.

    Science.gov (United States)

    Avelino-Silva, Vivian I; Miyaji, Karina T; Hunt, Peter W; Huang, Yong; Simoes, Marisol; Lima, Sheila B; Freire, Marcos S; Caiaffa-Filho, Helio H; Hong, Marisa A; Costa, Dayane Alves; Dias, Juliana Zanatta C; Cerqueira, Natalia B; Nishiya, Anna Shoko; Sabino, Ester Cerdeira; Sartori, Ana M; Kallas, Esper G

    2016-12-01

    HIV-infected individuals have deficient responses to Yellow Fever vaccine (YFV) and may be at higher risk for adverse events (AE). Chronic immune activation-characterized by low CD4/CD8 ratio or high indoleamine 2,3-dioxygenase-1 (IDO) activity-may influence vaccine response in this population. We prospectively assessed AE, viremia by the YFV virus and YF-specific neutralizing antibodies (NAb) in HIV-infected (CD4>350) and -uninfected adults through 1 year after vaccination. The effect of HIV status on initial antibody response to YFV was measured during the first 3 months following vaccination, while the effect on persistence of antibody response was measured one year following vaccination. We explored CD4/CD8 ratio, IDO activity (plasma kynurenine/tryptophan [KT] ratio) and viremia by Human Pegivirus as potential predictors of NAb response to YFV among HIV-infected participants with linear mixed models. 12 HIV-infected and 45-uninfected participants were included in the final analysis. HIV was not significantly associated with AE, YFV viremia or NAb titers through the first 3 months following vaccination. However, HIV-infected participants had 0.32 times the NAb titers observed for HIV-uninfected participants at 1 year following YFV (95% CI 0.13 to 0.83, p = 0.021), independent of sex, age and prior vaccination. In HIV-infected participants, each 10% increase in CD4/CD8 ratio predicted a mean 21% higher post-baseline YFV Nab titer (p = 0.024). Similarly, each 10% increase in KT ratio predicted a mean 21% lower post-baseline YFV Nab titer (p = 0.009). Viremia by Human Pegivirus was not significantly associated with NAb titers. HIV infection appears to decrease the durability of NAb responses to YFV, an effect that may be predicted by lower CD4/CD8 ratio or higher KT ratio.

  17. CD4/CD8 Ratio and KT Ratio Predict Yellow Fever Vaccine Immunogenicity in HIV-Infected Patients

    Science.gov (United States)

    Hunt, Peter W.; Huang, Yong; Simoes, Marisol; Lima, Sheila B.; Freire, Marcos S.; Caiaffa-Filho, Helio H.; Hong, Marisa A.; Costa, Dayane Alves; Dias, Juliana Zanatta C.; Cerqueira, Natalia B.; Nishiya, Anna Shoko; Sabino, Ester Cerdeira; Sartori, Ana M.; Kallas, Esper G.

    2016-01-01

    Background HIV-infected individuals have deficient responses to Yellow Fever vaccine (YFV) and may be at higher risk for adverse events (AE). Chronic immune activation–characterized by low CD4/CD8 ratio or high indoleamine 2,3-dioxygenase-1 (IDO) activity—may influence vaccine response in this population. Methods We prospectively assessed AE, viremia by the YFV virus and YF-specific neutralizing antibodies (NAb) in HIV-infected (CD4>350) and -uninfected adults through 1 year after vaccination. The effect of HIV status on initial antibody response to YFV was measured during the first 3 months following vaccination, while the effect on persistence of antibody response was measured one year following vaccination. We explored CD4/CD8 ratio, IDO activity (plasma kynurenine/tryptophan [KT] ratio) and viremia by Human Pegivirus as potential predictors of NAb response to YFV among HIV-infected participants with linear mixed models. Results 12 HIV-infected and 45-uninfected participants were included in the final analysis. HIV was not significantly associated with AE, YFV viremia or NAb titers through the first 3 months following vaccination. However, HIV–infected participants had 0.32 times the NAb titers observed for HIV-uninfected participants at 1 year following YFV (95% CI 0.13 to 0.83, p = 0.021), independent of sex, age and prior vaccination. In HIV-infected participants, each 10% increase in CD4/CD8 ratio predicted a mean 21% higher post-baseline YFV Nab titer (p = 0.024). Similarly, each 10% increase in KT ratio predicted a mean 21% lower post-baseline YFV Nab titer (p = 0.009). Viremia by Human Pegivirus was not significantly associated with NAb titers. Conclusions HIV infection appears to decrease the durability of NAb responses to YFV, an effect that may be predicted by lower CD4/CD8 ratio or higher KT ratio. PMID:27941965

  18. Novel bacterial ratio for predicting fecal age

    Energy Technology Data Exchange (ETDEWEB)

    Nieman, J.; Brion, G.M. [Univ. of Kentucky, Dept. of Civil Engineering, Lexington, Kentucky (United States)]. E-mail: gbrion@engr.uky.edu

    2002-06-15

    This study presents an extension of ongoing research into the utility of the ratio of bacterial colonies isolated on membrane filters during the total coliform test using m-Endo broth media for the prediction of fecal age. Analysis of the relative shifts in concentrations of indicator bacterial populations in Kentucky River water quality data collected from the inlet of a local water treatment plant showed a correlation between raw concentrations of atypical colonies (AC) and total coliform colonies (TC) formed on m-Endo membrane filter tests, and fecal age. Visual analysis of plant treatment records showed that low values of the AC/TC ratio were related to periods of high flow, when runoff added fresh fecal material to the river. A more detailed analysis of 2 years of Kentucky River water quality data showed the average AC/TC ratio during months with high river flow (rain) to be 3.4, rising to an average of 27.6 during months with low flow. The average AC/TC ratio during high flow months compared to that found in other studies for raw human sewage (3.9) and the ratio increased to values associated with animal impacted urban runoff (18.9) during low flow months. (author)

  19. Novel bacterial ratio for predicting fecal age

    International Nuclear Information System (INIS)

    Nieman, J.; Brion, G.M.

    2002-01-01

    This study presents an extension of ongoing research into the utility of the ratio of bacterial colonies isolated on membrane filters during the total coliform test using m-Endo broth media for the prediction of fecal age. Analysis of the relative shifts in concentrations of indicator bacterial populations in Kentucky River water quality data collected from the inlet of a local water treatment plant showed a correlation between raw concentrations of atypical colonies (AC) and total coliform colonies (TC) formed on m-Endo membrane filter tests, and fecal age. Visual analysis of plant treatment records showed that low values of the AC/TC ratio were related to periods of high flow, when runoff added fresh fecal material to the river. A more detailed analysis of 2 years of Kentucky River water quality data showed the average AC/TC ratio during months with high river flow (rain) to be 3.4, rising to an average of 27.6 during months with low flow. The average AC/TC ratio during high flow months compared to that found in other studies for raw human sewage (3.9) and the ratio increased to values associated with animal impacted urban runoff (18.9) during low flow months. (author)

  20. Financial and Staffing Ratio Analysis: Predicting Fiscal Distress in School Districts.

    Science.gov (United States)

    Lee, Robert Alan

    1983-01-01

    From analysis of data from 579 school districts it is concluded that financial ratios have the ability to forecast fiscal distress a year in advance. Liquidity ratios and salary and fringe benefit ratios were found to be strong forecasters, while per pupil expenditure data had little predictive value. (MJL)

  1. An evaluation of the usefulness of cash flow ratios to predict financial distress

    Directory of Open Access Journals (Sweden)

    L. Jooste

    2007-12-01

    Full Text Available Purpose: With the introduction of the cash flow statement it became an integral part of financial reporting. A need arose to develop ratios for the effective evaluation of cash flow information. This article investigates cash flow ratios suggested by various researchers and suggests a list of ratios with the potential to predict financial failure. Design: The cash flow ratios suggested by researchers, from as early as 1966, are investigated and eight cash flow ratios selected for inclusion in an analysis to predict financial failure. Ten failed entities are selected for a cash flow evaluation by means of the selected ratios for five years prior to failure. For a comparison, non-failed entities in similar sectors are selected and also evaluated by means of the cash flow ratios. The mean values of each ratio, for each year prior to failure, were then calculated and the means of the failed entities were compared to the non-failed entities. Findings: The comparison revealed that cash flow ratios have predictive value with the cash flow to total debt identified as the best indicator of failure. It was also determined that, although failed entities have lower cash flows than non-failed entities, they also had smaller reserves of liquid assets. Furthermore, they have less capacity to meet debt obligations and they tend to incur more debt. The ratios of the failed entities were unstable and fluctuated from one year to the next. Finally, bankruptcy could be predicted three years prior to financial failure. Implications: Income statement and balance sheet ratios are not enough to measure liquidity. An entity can have positive liquidity ratios and increasing profits, yet have serious cash flow problems. Ratios developed from the cash flow statement should supplement traditional accrual-based ratios to provide additional information on the financial strengths and weaknesses of an entity .

  2. A prediction model for wind speed ratios at pedestrian level with simplified urban canopies

    Science.gov (United States)

    Ikegaya, N.; Ikeda, Y.; Hagishima, A.; Razak, A. A.; Tanimoto, J.

    2017-02-01

    The purpose of this study is to review and improve prediction models for wind speed ratios at pedestrian level with simplified urban canopies. We adopted an extensive database of velocity fields under various conditions for arrays consisting of cubes, slender or flattened rectangles, and rectangles with varying roughness heights. Conclusions are summarized as follows: first, a new geometric parameter is introduced as a function of the plan area index and the aspect ratio so as to express the increase in virtual density that causes wind speed reduction. Second, the estimated wind speed ratios in the range 0.05 coefficients between the wind speeds averaged over the entire region, and the front or side region values are larger than 0.8. In contrast, in areas where the influence of roughness elements is significant, such as behind a building, the wind speeds are weakly correlated.

  3. Econometric models for predicting confusion crop ratios

    Science.gov (United States)

    Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)

    1979-01-01

    Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

  4. Development and evaluation of a regression-based model to predict cesium concentration ratios for freshwater fish

    International Nuclear Information System (INIS)

    Pinder, John E.; Rowan, David J.; Rasmussen, Joseph B.; Smith, Jim T.; Hinton, Thomas G.; Whicker, F.W.

    2014-01-01

    Data from published studies and World Wide Web sources were combined to produce and test a regression model to predict Cs concentration ratios for freshwater fish species. The accuracies of predicted concentration ratios, which were computed using 1) species trophic levels obtained from random resampling of known food items and 2) K concentrations in the water for 207 fish from 44 species and 43 locations, were tested against independent observations of ratios for 57 fish from 17 species from 25 locations. Accuracy was assessed as the percent of observed to predicted ratios within factors of 2 or 3. Conservatism, expressed as the lack of under prediction, was assessed as the percent of observed to predicted ratios that were less than 2 or less than 3. The model's median observed to predicted ratio was 1.26, which was not significantly different from 1, and 50% of the ratios were between 0.73 and 1.85. The percentages of ratios within factors of 2 or 3 were 67 and 82%, respectively. The percentages of ratios that were <2 or <3 were 79 and 88%, respectively. An example for Perca fluviatilis demonstrated that increased prediction accuracy could be obtained when more detailed knowledge of diet was available to estimate trophic level. - Highlights: • We developed a model to predict Cs concentration ratios for freshwater fish species. • The model uses only two variables to predict a species CR for any location. • One variable is the K concentration in the freshwater. • The other is a species mean trophic level measure easily obtained from (fishbase.org). • The median observed to predicted ratio for 57 independent test cases was 1.26

  5. The dividend-price ratio does predict dividend growth: International evidence

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard

    Unpredictable dividend growth by the dividend-price ratio is considered a 'stylized fact' in post war US data. Using long-term data, covering more than 80 years from the US and three European countries, we revisit this stylized fact, and we also report results on return predictability. We find...... similar to those for the US. For Sweden and Denmark we find no evidence of return predictability, but strong evidence of predictable dividend growth in the 'right' direction on both short and long horizons and over both the full sample periods and the post war period. We also document that implied long......-horizon coefficients from VAR's often differ substantially from direct estimates in multi-year regres- sions. Throughout, we report both standard asymptotic tests and simulated small- sample tests and, following Cochrane (2008), we investigate the joint distribution of dividend-price ratio coefficients in return...

  6. Bankruptcy Prediction Based on the Autonomy Ratio

    Directory of Open Access Journals (Sweden)

    Daniel Brîndescu Olariu

    2016-11-01

    Full Text Available The theory and practice of the financial ratio analysis suggest the existence of a negative correlation between the autonomy ratio and the bankruptcy risk. Previous studies conducted on a sample of companies from Timis County (largest county in Romania confirm this hypothesis and recommend the autonomy ratio as a useful tool for measuring the bankruptcy risk two years in advance. The objective of the current research was to develop a methodology for measuring the bankruptcy risk that would be applicable for the companies from the Timis County (specific methodologies are considered necessary for each region. The target population consisted of all the companies from Timis County with annual sales of over 10,000 lei (aprox. 2,200 Euros. The research was performed over all the target population. The study has thus included 53,252 yearly financial statements from the period 2007 – 2010. The results of the study allow for the setting of benchmarks, as well as the configuration of a methodology of analysis. The proposed methodology cannot predict with perfect accuracy the state of the company, but it allows for a valuation of the risk level to which the company is subjected.

  7. Distal Ureteral Diameter Ratio is Predictive of Breakthrough Febrile Urinary Tract Infection.

    Science.gov (United States)

    Arlen, Angela M; Leong, Traci; Guidos, P Joseph; Alexander, Siobhan E; Cooper, Christopher S

    2017-12-01

    Distal ureteral diameter ratio is an objective measure that is prognostic of spontaneous resolution of vesicoureteral reflux. Along with likelihood of resolution, improved identification of children at risk for recurrent febrile urinary tract infections may impact management decisions. We evaluated the usefulness of ureteral diameter ratio as a predictive factor for breakthrough febrile urinary tract infections. Children with primary vesicoureteral reflux and detailed voiding cystourethrogram were identified. Ureteral diameter ratio was computed by measuring largest ureteral diameter within the pelvis and dividing by the distance between L1 and L3 vertebral bodies. Demographics, vesicoureteral reflux grade, laterality, presence/absence of bladder-bowel dysfunction, and ureteral diameter ratio were tested in univariate and multivariable analyses. Primary outcome was breakthrough febrile urinary tract infections. We analyzed 112 girls and 28 boys with a mean ± SD age of 2.5 ± 2.3 years at diagnosis. Vesicoureteral reflux was grade 1 to 2 in 64 patients (45.7%), grade 3 in 50 (35.7%), grade 4 in 16 (11.4%) and grade 5 in 10 (7.2%). Mean ± SD followup was 3.2 ± 2.7 years. A total of 40 children (28.6%) experienced breakthrough febrile urinary tract infections. Ureteral diameter ratio was significantly greater in children with (0.36) vs without (0.25) breakthrough febrile infections (p = 0.004). Controlling for vesicoureteral reflux grade, every 0.1 U increase in ureteral diameter ratio resulted in 1.7 times increased odds of breakthrough infection (95% CI 1.24 to 2.26, p urinary tract infections independent of reflux grade. Ureteral diameter ratio provides valuable prognostic information about risk of recurrent pyelonephritis and may assist with clinical decision-making. Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  8. THE USEFULNESS OF THE AUTONOMY RATIO IN THE PREDICTION OF BANKRUPTCY

    Directory of Open Access Journals (Sweden)

    Daniel BRÎNDESCU-OLARIU

    2015-11-01

    Full Text Available The purpose of the current study was to test the potential of the autonomy ratio in the prediction of bankruptcy. The target population included all the active companies from the Timis County with annual sales of over 10,000 lei. The event the research was focused on is represented by the occurence of bankruptcy 2 years after the date of the financial statements of reference. The bankruptcy was defined in accordance with the Romanian law applicable over the period targeted by the study. The tests were performed over a paired-sample that included all the companies from the target population that went bankrupt during the period 2011-2012. The discrimination power of the autonomy ratio was evaluated for different cut-off values recommended by the existing literature. The research proves the utility of the autonomy ratio in the prediction of bankruptcy two years before its occurence.

  9. Impact of Different Active-Speech-Ratios on PESQ’s Predictions in Case of Independent and Dependent Losses (in Presence of Receiver-Side Comfort-Noise

    Directory of Open Access Journals (Sweden)

    P. Pocta

    2010-04-01

    Full Text Available This paper deals with the investigation of PESQ’s behavior under independent and dependent loss conditions from an Active-Speech-Ratio perspective in presence of receiver-side comfort-noise. This reference signal characteristic is defined very broadly by ITU-T Recommendation P.862.3. That is the reason to investigate an impact of this characteristic on speech quality prediction more in-depth. We assess the variability of PESQ’s predictions with respect to Active-Speech-Ratios and loss conditions, as well as their accuracy, by comparing the predictions with subjective assessments. Our results show that an increase in amount of speech in the reference signal (expressed by the Active-Speech-Ratio characteristic may result in an increase of the reference signal sensitivity to packet loss change. Interestingly, we have found two additional effects in this investigated case. The use of higher Active-Speech-Ratios may lead to negative shifting effect in MOS domain and also PESQ’s predictions accuracy declining. Predictions accuracy could be improved by higher packet losses.

  10. Risk prediction is improved by adding markers of subclinical organ damage to SCORE

    DEFF Research Database (Denmark)

    Sehestedt, Thomas; Jeppesen, Jørgen; Hansen, Tine W

    2010-01-01

    cardiovascular, anti-diabetic, or lipid-lowering treatment, aged 41, 51, 61, or 71 years, we measured traditional cardiovascular risk factors, left ventricular (LV) mass index, atherosclerotic plaques in the carotid arteries, carotid/femoral pulse wave velocity (PWV), and urine albumin/creatinine ratio (UACR......) and followed them for a median of 12.8 years. Eighty-one subjects died because of cardiovascular causes. Risk of cardiovascular death was independently of SCORE associated with LV hypertrophy [hazard ratio (HR) 2.2 (95% CI 1.2-4.0)], plaques [HR 2.5 (1.6-4.0)], UACR > or = 90th percentile [HR 3.3 (1.......07). CONCLUSION: Subclinical organ damage predicted cardiovascular death independently of SCORE and the combination may improve risk prediction....

  11. Cardiovascular risk prediction: the old has given way to the new but at what risk-benefit ratio?

    Directory of Open Access Journals (Sweden)

    Yeboah J

    2014-10-01

    Full Text Available Joseph Yeboah Heart and Vascular Center of Excellence, Wake Forest University School of Medicine, Winston-Salem, NC, USA Abstract: The ultimate goal of cardiovascular risk prediction is to identify individuals in the population to whom the application or administration of current proven lifestyle modifications and medicinal therapies will result in reduction in cardiovascular disease events and minimal adverse effects (net benefit to society. The use of cardiovascular risk prediction tools dates back to 1976 when the Framingham coronary heart disease risk score was published. Since then a lot of novel risk markers have been identified and other cardiovascular risk prediction tools have been developed to either improve or replace the Framingham Risk Score (FRS. In 2013, the new atherosclerotic cardiovascular disease risk estimator was published by the American College of Cardiology and the American Heart Association to replace the FRS for cardiovascular risk prediction. It is too soon to know the performance of the new atherosclerotic cardiovascular disease risk estimator. The risk-benefit ratio for preventive therapy (lifestyle modifications, statin +/− aspirin based on cardiovascular disease risk assessed using the FRS is unknown but it was assumed to be a net benefit. Should we also assume the risk-benefit ratio for the new atherosclerotic cardiovascular disease risk estimator is also a net benefit? Keywords: risk prediction, prevention, cardiovascular disease

  12. Development and evaluation of a regression-based model to predict cesium-137 concentration ratios for saltwater fish

    International Nuclear Information System (INIS)

    Pinder, John E.; Rowan, David J.; Smith, Jim T.

    2016-01-01

    Data from published studies and World Wide Web sources were combined to develop a regression model to predict "1"3"7Cs concentration ratios for saltwater fish. Predictions were developed from 1) numeric trophic levels computed primarily from random resampling of known food items and 2) K concentrations in the saltwater for 65 samplings from 41 different species from both the Atlantic and Pacific Oceans. A number of different models were initially developed and evaluated for accuracy which was assessed as the ratios of independently measured concentration ratios to those predicted by the model. In contrast to freshwater systems, were K concentrations are highly variable and are an important factor in affecting fish concentration ratios, the less variable K concentrations in saltwater were relatively unimportant in affecting concentration ratios. As a result, the simplest model, which used only trophic level as a predictor, had comparable accuracies to more complex models that also included K concentrations. A test of model accuracy involving comparisons of 56 published concentration ratios from 51 species of marine fish to those predicted by the model indicated that 52 of the predicted concentration ratios were within a factor of 2 of the observed concentration ratios. - Highlights: • We developed a model to predict concentration ratios (C_r) for saltwater fish. • The model requires only a single input variable to predict C_r. • That variable is a mean numeric trophic level available at (fishbase.org). • The K concentrations in seawater were not an important predictor variable. • The median-to observed ratio for 56 independently measured C_r was 0.83.

  13. Predictive contribution of neutrophil/lymphocyte ratio in diagnosis of brucellosis.

    Science.gov (United States)

    Olt, Serdar; Ergenç, Hasan; Açıkgöz, Seyyid Bilal

    2015-01-01

    Here we wanted to investigate predictive value of neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) in the diagnosis of brucellosis. Thirty-two brucellosis patients diagnosed with positive serum agglutination test and thirty-two randomized healthy subjects were enrolled in this study retrospectively. Result with ROC analyzes the baseline NLR and hemoglobin values were found to be significantly associated with brucellosis (P = 0.01, P = 0.01, resp.). Herein we demonstrated for the first time that NLR values were significantly associated with brucellosis. This situation can help clinicians during diagnosis of brucellosis.

  14. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Hang-cheong Wong

    2012-01-01

    Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.

  15. Improved analysis of bacterial CGH data beyond the log-ratio paradigm

    Directory of Open Access Journals (Sweden)

    Aakra Ågot

    2009-03-01

    Full Text Available Abstract Background Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach. Results A data set containing 32 hybridizations of sequenced versus sequenced genomes have been used to test and compare methods. A ROC-analysis has been performed to illustrate the ability to rank probes with respect to Present/Absent calls. Classification into Present and Absent is compared with that of a gaussian mixture model. Conclusion The results indicate our proposed method is an improvement of existing methods with respect to ranking and classification of probes, especially for multi-genome arrays.

  16. Audiovisual biofeedback improves motion prediction accuracy.

    Science.gov (United States)

    Pollock, Sean; Lee, Danny; Keall, Paul; Kim, Taeho

    2013-04-01

    The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients' respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction. An AV biofeedback system combined with real-time respiratory data acquisition and MR images were implemented in this project. One-dimensional respiratory data from (1) the abdominal wall (30 Hz) and (2) the thoracic diaphragm (5 Hz) were obtained from 15 healthy human subjects across 30 studies. The subjects were required to breathe with and without the guidance of AV biofeedback during each study. The obtained respiratory signals were then implemented in a kernel density estimation prediction algorithm. For each of the 30 studies, five different prediction times ranging from 50 to 1400 ms were tested (150 predictions performed). Prediction error was quantified as the root mean square error (RMSE); the RMSE was calculated from the difference between the real and predicted respiratory data. The statistical significance of the prediction results was determined by the Student's t-test. Prediction accuracy was considerably improved by the implementation of AV biofeedback. Of the 150 respiratory predictions performed, prediction accuracy was improved 69% (103/150) of the time for abdominal wall data, and 78% (117/150) of the time for diaphragm data. The average reduction in RMSE due to AV biofeedback over unguided respiration was 26% (p biofeedback improves prediction accuracy. This would result in increased efficiency of motion management techniques affected by system latencies used in radiotherapy.

  17. Improving CT detection sensitivity for nodal metastases in oesophageal cancer with combination of smaller size and lymph node axial ratio

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jianfang [Chinese Academy of Medical Sciences and Peking Union Medical College, National Cancer Center/Cancer Hospital, Beijing (China); Capital Medical University Electric Power Teaching Hospital, Beijing (China); Wang, Zhu; Qu, Dong; Yao, Libo [Chinese Academy of Medical Sciences and Peking Union Medical College, National Cancer Center/Cancer Hospital, Beijing (China); Shao, Huafei [Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai (China); Liu, Jian [Meitan General Hospital, Beijing (China)

    2018-01-15

    To investigate the value of CT with inclusion of smaller lymph node (LN) sizes and axial ratio to improve the sensitivity in diagnosis of regional lymph node metastases in oesophageal squamous cell carcinoma (OSCC). The contrast-enhanced multidetector row spiral CT (MDCT) multiplanar reconstruction images of 204 patients with OSCC were retrospectively analysed. The long-axis and short-axis diameters of the regional LNs were measured and axial ratios were calculated (short-axis/long-axis diameters). Nodes were considered round if the axial ratio exceeded the optimal LN axial ratio, which was determined by receiver operating characteristic analysis. A positive predictive value (PPV) exceeding 50% is needed. This was achieved only with LNs larger than 9 mm in short-axis diameter, but nodes of this size were rare (sensitivity 37.3%, specificity 96.4%, accuracy 85.8%). If those round nodes (axial ratio exceeding 0.66) between 7 mm and 9 mm in size were considered metastases as well, it might improve the sensitivity to 67.2% with a PPV of 63.9% (specificity 91.6%, accuracy 87.2%). Combination of a smaller size and axial ratio for LNs in MDCT as criteria improves the detection sensitivity for LN metastases in OSCC. (orig.)

  18. Improvement of Risk Prediction After Transcatheter Aortic Valve Replacement by Combining Frailty With Conventional Risk Scores.

    Science.gov (United States)

    Schoenenberger, Andreas W; Moser, André; Bertschi, Dominic; Wenaweser, Peter; Windecker, Stephan; Carrel, Thierry; Stuck, Andreas E; Stortecky, Stefan

    2018-02-26

    This study sought to evaluate whether frailty improves mortality prediction in combination with the conventional scores. European System for Cardiac Operative Risk Evaluation (EuroSCORE) or Society of Thoracic Surgeons (STS) score have not been evaluated in combined models with frailty for mortality prediction after transcatheter aortic valve replacement (TAVR). This prospective cohort comprised 330 consecutive TAVR patients ≥70 years of age. Conventional scores and a frailty index (based on assessment of cognition, mobility, nutrition, and activities of daily living) were evaluated to predict 1-year all-cause mortality using Cox proportional hazards regression (providing hazard ratios [HRs] with confidence intervals [CIs]) and measures of test performance (providing likelihood ratio [LR] chi-square test statistic and C-statistic [CS]). All risk scores were predictive of the outcome (EuroSCORE, HR: 1.90 [95% CI: 1.45 to 2.48], LR chi-square test statistic 19.29, C-statistic 0.67; STS score, HR: 1.51 [95% CI: 1.21 to 1.88], LR chi-square test statistic 11.05, C-statistic 0.64; frailty index, HR: 3.29 [95% CI: 1.98 to 5.47], LR chi-square test statistic 22.28, C-statistic 0.66). A combination of the frailty index with either EuroSCORE (LR chi-square test statistic 38.27, C-statistic 0.72) or STS score (LR chi-square test statistic 28.71, C-statistic 0.68) improved mortality prediction. The frailty index accounted for 58.2% and 77.6% of the predictive information in the combined model with EuroSCORE and STS score, respectively. Net reclassification improvement and integrated discrimination improvement confirmed that the added frailty index improved risk prediction. This is the first study showing that the assessment of frailty significantly enhances prediction of 1-year mortality after TAVR in combined risk models with conventional risk scores and relevantly contributes to this improvement. Copyright © 2018 American College of Cardiology Foundation

  19. Predictive value of IgE/IgG4 antibody ratio in children with egg allergy

    Directory of Open Access Journals (Sweden)

    Okamoto Shindou

    2012-06-01

    Full Text Available Abstract Background The aim of this study was to investigate the role of specific IgG4 antibodies to hen’s egg white and determine their utility as a marker for the outcome of oral challenge test in children sensitized to hen’s egg Methods The hen’s egg oral food challenge test was performed in 105 sensitized children without atopic dermatitis, and the titers of egg white-specific immunoglobulin G4 (IgG4 and immunoglobulin E (IgE antibodies were measured. To set the cut-off values of IgG4, IgE, and the IgE/IgG4 ratio for predicting positive results in oral challenges, receiver operating characteristic curves were plotted and the area under the curves (AUC were calculated. Results Sixty-four of 105 oral challenges with whole eggs were assessed as positive. The AUC for IgE, IgG4, and IgE/IgG4 for the prediction of positive results were 0.609, 0.724, and 0.847, respectively. Thus, the IgE/IgG4 ratio generated significantly higher specificity, sensitivity, positive predictive value (%, and negative predictive value (% than the individual IgE and IgG4. The negative predictive value of the IgE/IgG4 ratio was 90% at a value of 1. Conclusions We have demonstrated that the egg white-specific serum IgE/IgG4 ratio is important for predicting reactivity to egg during food challenges.

  20. Risk Preferences and Predictions about Others: No Association with 2D:4D Ratio

    Directory of Open Access Journals (Sweden)

    Katharina Lima de Miranda

    2018-02-01

    Full Text Available Prenatal androgen exposure affects the brain development of the fetus which may facilitate certain behaviors and decision patterns in the later life. The ratio between the lengths of second and the fourth fingers (2D:4D is a negative biomarker of the ratio between prenatal androgen and estrogen exposure and men typically have lower ratios than women. In line with the typical findings suggesting that women are more risk averse than men, several studies have also shown negative relationships between 2D:4D and risk taking although the evidence is not conclusive. Previous studies have also reported that both men and women believe women are more risk averse than men. In the current study, we re-test the relationship between 2D:4D and risk preferences in a German student sample and also investigate whether the 2D:4D ratio is associated with people’s perceptions about others’ risk preferences. Following an incentivized risk elicitation task, we asked all participants their predictions about (i others’ responses (without sex specification, (ii men’s responses, and (iii women’s responses; then measured their 2D:4D ratios. In line with the previous findings, female participants in our sample were more risk averse. While both men and women underestimated other participants’ (non sex-specific and women’s risky decisions on average, their predictions about men were accurate. We also found evidence for the false consensus effect, as risky choices are positively correlated with predictions about other participants’ risky choices. The 2D:4D ratio was not directly associated either with risk preferences or the predictions of other participants’ choices. An unexpected finding was that women with mid-range levels of 2D:4D estimated significantly larger sex differences in participants’ decisions. This finding needs further testing in future studies.

  1. Risk Preferences and Predictions about Others: No Association with 2D:4D Ratio

    Science.gov (United States)

    Lima de Miranda, Katharina; Neyse, Levent; Schmidt, Ulrich

    2018-01-01

    Prenatal androgen exposure affects the brain development of the fetus which may facilitate certain behaviors and decision patterns in the later life. The ratio between the lengths of second and the fourth fingers (2D:4D) is a negative biomarker of the ratio between prenatal androgen and estrogen exposure and men typically have lower ratios than women. In line with the typical findings suggesting that women are more risk averse than men, several studies have also shown negative relationships between 2D:4D and risk taking although the evidence is not conclusive. Previous studies have also reported that both men and women believe women are more risk averse than men. In the current study, we re-test the relationship between 2D:4D and risk preferences in a German student sample and also investigate whether the 2D:4D ratio is associated with people’s perceptions about others’ risk preferences. Following an incentivized risk elicitation task, we asked all participants their predictions about (i) others’ responses (without sex specification), (ii) men’s responses, and (iii) women’s responses; then measured their 2D:4D ratios. In line with the previous findings, female participants in our sample were more risk averse. While both men and women underestimated other participants’ (non sex-specific) and women’s risky decisions on average, their predictions about men were accurate. We also found evidence for the false consensus effect, as risky choices are positively correlated with predictions about other participants’ risky choices. The 2D:4D ratio was not directly associated either with risk preferences or the predictions of other participants’ choices. An unexpected finding was that women with mid-range levels of 2D:4D estimated significantly larger sex differences in participants’ decisions. This finding needs further testing in future studies. PMID:29472846

  2. Lipoprotein metabolism indicators improve cardiovascular risk prediction.

    Directory of Open Access Journals (Sweden)

    Daniël B van Schalkwijk

    Full Text Available BACKGROUND: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to investigate whether lipoprotein metabolism indicators can improve cardiovascular risk prediction and therapy management. METHODS AND RESULTS: We calculated lipoprotein metabolism indicators for 1981 subjects (145 cases, 1836 controls from the Framingham Heart Study offspring cohort in which NMR lipoprotein profiles were measured. We applied a statistical learning algorithm using a support vector machine to select conventional risk factors and lipoprotein metabolism indicators that contributed to predicting risk for general cardiovascular disease. Risk prediction was quantified by the change in the Area-Under-the-ROC-Curve (ΔAUC and by risk reclassification (Net Reclassification Improvement (NRI and Integrated Discrimination Improvement (IDI. Two VLDL lipoprotein metabolism indicators (VLDLE and VLDLH improved cardiovascular risk prediction. We added these indicators to a multivariate model with the best performing conventional risk markers. Our method significantly improved both CVD prediction and risk reclassification. CONCLUSIONS: Two calculated VLDL metabolism indicators significantly improved cardiovascular risk prediction. These indicators may help to reduce prescription of unnecessary cholesterol-lowering medication, reducing costs and possible side-effects. For clinical application, further validation is required.

  3. Prehospital shock index and pulse pressure/heart rate ratio to predict massive transfusion after severe trauma: Retrospective analysis of a large regional trauma database.

    Science.gov (United States)

    Pottecher, Julien; Ageron, François-Xavier; Fauché, Clémence; Chemla, Denis; Noll, Eric; Duranteau, Jacques; Chapiteau, Laurent; Payen, Jean-François; Bouzat, Pierre

    2016-10-01

    Early and accurate detection of severe hemorrhage is critical for a timely trigger of massive transfusion (MT). Hemodynamic indices combining heart rate (HR) and either systolic (shock index [SI]) or pulse pressure (PP) (PP/HR ratio) have been shown to track blood loss during hemorrhage. The present study assessed the accuracy of prehospital SI and PP/HR ratio to predict subsequent MT, using the gray-zone approach. This was a retrospective analysis (January 1, 2009, to December 31, 2011) of a prospectively developed trauma registry (TRENAU), in which the triage scheme combines patient severity and hospital facilities. Thresholds for MT were defined as either classic (≥10 red blood cell units within the first 24 hours [MT1]) or critical (≥3 red blood cells within the first hour [MT2]). The receiver operating characteristic curves and gray zones were defined for SI and PP/HR ratio to predict MT1 and MT2 and faced with initial triage scheme. The TRENAU registry included 3,689 trauma patients, of which 2,557 had complete chart recovery and 176 (6.9%) required MT. In the whole population, PP/HR ratio and SI moderately and similarly predicted MT1 (area under the receiver operating characteristic curve, 0.77 [95% confidence interval {CI}, 0.70-0.84] and 0.80 [95% CI, 0.74-0.87], respectively, p = 0.064) and MT2 (0.71 [95% CI, 0.67-0.76] and 0.72 [95% CI, 0.68-0.77], respectively, p = 0.48). The proportions of patients in the gray zone for PP/HR ratio and SI were 61% versus 40%, respectively, to predict MT1 (p ratio outperformed SI to predict MT2 (0.72 [95% CI, 0.59-0.84] vs. 0.54 [95% CI, 0.33-0.74]; p ratio were moderately accurate in predicting MT. In the seemingly least severe patients, an improvement of prehospital undertriage for MT may be gained by using the PP/HR ratio. Epidemiolgic study, level III.

  4. Mathematical model to predict temperature profile and air–fuel equivalence ratio of a downdraft gasification process

    International Nuclear Information System (INIS)

    Jaojaruek, Kitipong

    2014-01-01

    Highlights: • A mathematical model based on finite computation analysis was developed. • Model covers all zones of gasification process which will be useful to improve gasifier design. • Model can predict temperature profile, feedstock consumption rate and reaction equivalent ratio (ϕ). • Model-predicted parameters fitted well with experimental values. - Abstract: A mathematical model for the entire length of a downdraft gasifier was developed using thermochemical principles to derive energy and mass conversion equations. Analysis of heat transfer (conduction, convection and radiation) and chemical kinetic technique were applied to predict the temperature profile, feedstock consumption rate (FCR) and reaction equivalence ratio (RER). The model will be useful for designing gasifiers, estimating output gas composition and gas production rate (GPR). Implicit finite difference method solved the equations on the considered reactor length (50 cm) and diameter (20 cm). Conversion criteria for calculation of temperature and feedstock consumption rate were 1 × 10 −6 °C and 1 × 10 −6 kg/h, respectively. Experimental validation showed that model outputs fitted well with experimental data. Maximum deviation between model and experimental data of temperature, FCR and RER were 52 °C at combustion temperature 663 °C, 0.7 kg/h at the rate 8.1 kg/h and 0.03 at the RER 0.42, respectively. Experimental uncertainty of temperature, FCR and RER were 24.4 °C, 0.71 kg/h and 0.04, respectively, on confidence level of 95%

  5. Ratio of ovarian stroma and total ovarian area by ultrasound in prediction of hyperandrogenemia in reproductive-aged Thai women with polycystic ovary syndrome: a diagnostic test.

    Science.gov (United States)

    Leerasiri, Pichai; Wongwananuruk, Thanyarat; Rattanachaiyanont, Manee; Indhavivadhana, Suchada; Techatraisak, Kitirat; Angsuwathana, Surasak

    2015-02-01

    To evaluate the performance of ovarian stromal area to total ovarian area (S/A) ratio for the prediction of biochemical hyperandrogenism in Thai women with polycystic ovary syndrome (PCOS). A cross-sectional study was performed in 222 reproductive-aged Thai women with PCOS attending the Gynecologic Endocrinology Unit (GEU), Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital from May 2007 to January 2009. The patients were interviewed for medical history and examined for anthropometry and clinical hyperandrogenism. Venous blood samples were obtained for androgen profiles. An ovarian ultrasonogram was obtained via transvaginal or transrectal ultrasonography. The prevalences of clinical and biochemical hyperandrogenism were 48.6% and 81.1%, respectively. The S/A ratio at a cut-off point of 0.33 had modest predictability for hyperandrogenism, namely, 0.537 area under the receiver-operator curve, 36.6% sensitivity, 72.1% specificity, 83.8% positive predictive value (PPV) and 20.9% negative predictive value (NPV). The combination of clinical hyperandrogenism and S/A ratio improved the predictability for biochemical hyperandrogenism, with sensitivity, specificity, PPV and NPV of 72.1%, 58.1%, 87.8% and 33.3%, respectively. The S/A ratio alone is not a good predictor for biochemical hyperandrogenism in Thai PCOS women attending GEU for menstrual dysfunction. The combination of S/A ratio and clinical hyperandrogenism has better performance than the S/A ratio alone to predict biochemical hyperandrogenism. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

  6. An improved method for predicting brittleness of rocks via well logs in tight oil reservoirs

    Science.gov (United States)

    Wang, Zhenlin; Sun, Ting; Feng, Cheng; Wang, Wei; Han, Chuang

    2018-06-01

    There can be no industrial oil production in tight oil reservoirs until fracturing is undertaken. Under such conditions, the brittleness of the rocks is a very important factor. However, it has so far been difficult to predict. In this paper, the selected study area is the tight oil reservoirs in Lucaogou formation, Permian, Jimusaer sag, Junggar basin. According to the transformation of dynamic and static rock mechanics parameters and the correction of confining pressure, an improved method is proposed for quantitatively predicting the brittleness of rocks via well logs in tight oil reservoirs. First, 19 typical tight oil core samples are selected in the study area. Their static Young’s modulus, static Poisson’s ratio and petrophysical parameters are measured. In addition, the static brittleness indices of four other tight oil cores are measured under different confining pressure conditions. Second, the dynamic Young’s modulus, Poisson’s ratio and brittleness index are calculated using the compressional and shear wave velocity. With combination of the measured and calculated results, the transformation model of dynamic and static brittleness index is built based on the influence of porosity and clay content. The comparison of the predicted brittleness indices and measured results shows that the model has high accuracy. Third, on the basis of the experimental data under different confining pressure conditions, the amplifying factor of brittleness index is proposed to correct for the influence of confining pressure on the brittleness index. Finally, the above improved models are applied to formation evaluation via well logs. Compared with the results before correction, the results of the improved models agree better with the experimental data, which indicates that the improved models have better application effects. The brittleness index prediction method of tight oil reservoirs is improved in this research. It is of great importance in the optimization of

  7. Synchronous Condenser Allocation for Improving System Short Circuit Ratio

    DEFF Research Database (Denmark)

    Jia, Jundi; Yang, Guangya; Nielsen, Arne Hejde

    2018-01-01

    With converter-based renewable energy sources increasingly integrated into power systems and conventional power plants gradually phased out, future power systems will experience reduced short circuit strength. The deployment of synchronous condensers can serve as a potential solution. This paper...... presents an optimal synchronous condenser allocation method for improving system short circuit ratio at converter point of common coupling using a modified short circuit analysis approach. The total cost of installing new synchronous condensers is minimized while the system short circuit ratios...

  8. Ratio-based lengths of intervals to improve fuzzy time series forecasting.

    Science.gov (United States)

    Huarng, Kunhuang; Yu, Tiffany Hui-Kuang

    2006-04-01

    The objective of this study is to explore ways of determining the useful lengths of intervals in fuzzy time series. It is suggested that ratios, instead of equal lengths of intervals, can more properly represent the intervals among observations. Ratio-based lengths of intervals are, therefore, proposed to improve fuzzy time series forecasting. Algebraic growth data, such as enrollments and the stock index, and exponential growth data, such as inventory demand, are chosen as the forecasting targets, before forecasting based on the various lengths of intervals is performed. Furthermore, sensitivity analyses are also carried out for various percentiles. The ratio-based lengths of intervals are found to outperform the effective lengths of intervals, as well as the arbitrary ones in regard to the different statistical measures. The empirical analysis suggests that the ratio-based lengths of intervals can also be used to improve fuzzy time series forecasting.

  9. An improved data acquisition system for isotopic ratio mass spectrometers

    International Nuclear Information System (INIS)

    Saha, T.K.; Reddy, B.; Nazare, C.K.; Handu, V.K.

    1999-01-01

    Isotopic ratio mass spectrometers designed and fabricated to measure the isotopic ratios with a precision of better than 0.05%. In order to achieve this precision, the measurement system consisting of ion signal to voltage converters, analog to digital converters, and data acquisition electronics should be at least one order better than the overall precision of measurement. Using state of the art components and techniques, a data acquisition system, which is an improved version of the earlier system, has been designed and developed for use with multi-collector isotopic ratio mass spectrometers

  10. Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

    Science.gov (United States)

    Romanens, Michel; Ackermann, Franz; Spence, John David; Darioli, Roger; Rodondi, Nicolas; Corti, Roberto; Noll, Georg; Schwenkglenks, Matthias; Pencina, Michael

    2010-02-01

    Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

  11. Prediction of the compression ratio for municipal solid waste using decision tree.

    Science.gov (United States)

    Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

    2014-01-01

    The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

  12. Positive predictive value of albumin: globulin ratio for feline infectious peritonitis in a mid-western referral hospital population.

    Science.gov (United States)

    Jeffery, Unity; Deitz, Krysta; Hostetter, Shannon

    2012-12-01

    Low albumin to globulin ratio has been found previously to have a high positive predictive value for feline infectious peritonitis (FIP) in cats with clinical signs highly suggestive of the disease. However, FIP can have a more vague clinical presentation. This retrospective study found that the positive predictive value of an albumin:globulin (A:G) ratio of <0.8 and <0.6 was only 12.5% and 25%, respectively, in a group of 100 cats with one or more clinical signs consistent with FIP. The negative predictive value was 100% and 99% for an A:G ratio of <0.8 and A:G<0.6%, respectively. Therefore, when the prevalence of FIP is low, the A:G ratio is useful to rule out FIP but is not helpful in making a positive diagnosis of FIP.

  13. Skill of Predicting Heavy Rainfall Over India: Improvement in Recent Years Using UKMO Global Model

    Science.gov (United States)

    Sharma, Kuldeep; Ashrit, Raghavendra; Bhatla, R.; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.

    2017-11-01

    The quantitative precipitation forecast (QPF) performance for heavy rains is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. This study aims to evaluate the performance of UK Met Office Unified Model (UKMO) over India for prediction of high rainfall amounts (>2 and >5 cm/day) during the monsoon period (JJAS) from 2007 to 2015 in short range forecast up to Day 3. Among the various modeling upgrades and improvements in the parameterizations during this period, the model horizontal resolution has seen an improvement from 40 km in 2007 to 17 km in 2015. Skill of short range rainfall forecast has improved in UKMO model in recent years mainly due to increased horizontal and vertical resolution along with improved physics schemes. Categorical verification carried out using the four verification metrics, namely, probability of detection (POD), false alarm ratio (FAR), frequency bias (Bias) and Critical Success Index, indicates that QPF has improved by >29 and >24% in case of POD and FAR. Additionally, verification scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and SEDI (Symmetric EDI) are used with special emphasis on verification of extreme and rare rainfall events. These scores also show an improvement by 60% (EDS) and >34% (EDI and SEDI) during the period of study, suggesting an improved skill of predicting heavy rains.

  14. Prediction of failure strain and burst pressure in high yield-to-tensile strength ratio linepipe

    International Nuclear Information System (INIS)

    Law, M.; Bowie, G.

    2007-01-01

    Failure pressures and strains were predicted for a number of burst tests as part of a project to explore failure strain in high yield-to-tensile strength ratio linepipe. Twenty-three methods for predicting the burst pressure and six methods of predicting the failure strain are compared with test results. Several methods were identified which gave accurate and reliable estimates of burst pressure. No method of accurately predicting the failure strain was found, though the best was noted

  15. Prediction of failure strain and burst pressure in high yield-to-tensile strength ratio linepipe

    Energy Technology Data Exchange (ETDEWEB)

    Law, M. [Institute of Materials and Engineering Science, Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW (Australia)]. E-mail: mlx@ansto.gov.au; Bowie, G. [BlueScope Steel Ltd., Level 11, 120 Collins St, Melbourne, Victoria 3000 (Australia)

    2007-08-15

    Failure pressures and strains were predicted for a number of burst tests as part of a project to explore failure strain in high yield-to-tensile strength ratio linepipe. Twenty-three methods for predicting the burst pressure and six methods of predicting the failure strain are compared with test results. Several methods were identified which gave accurate and reliable estimates of burst pressure. No method of accurately predicting the failure strain was found, though the best was noted.

  16. Improving a two-equation eddy-viscosity turbulence model to predict the aerodynamic performance of thick wind turbine airfoils

    Science.gov (United States)

    Bangga, Galih; Kusumadewi, Tri; Hutomo, Go; Sabila, Ahmad; Syawitri, Taurista; Setiadi, Herlambang; Faisal, Muhamad; Wiranegara, Raditya; Hendranata, Yongki; Lastomo, Dwi; Putra, Louis; Kristiadi, Stefanus

    2018-03-01

    Numerical simulations for relatively thick airfoils are carried out in the present studies. An attempt to improve the accuracy of the numerical predictions is done by adjusting the turbulent viscosity of the eddy-viscosity Menter Shear-Stress-Transport (SST) model. The modification involves the addition of a damping factor on the wall-bounded flows incorporating the ratio of the turbulent kinetic energy to its specific dissipation rate for separation detection. The results are compared with available experimental data and CFD simulations using the original Menter SST model. The present model improves the lift polar prediction even though the stall angle is still overestimated. The improvement is caused by the better prediction of separated flow under a strong adverse pressure gradient. The results show that the Reynolds stresses are damped near the wall causing variation of the logarithmic velocity profiles.

  17. Study of improving signal-noise ratio for fluorescence channel

    Science.gov (United States)

    Wang, Guoqing; Li, Xin; Lou, Yue; Chen, Dong; Zhao, Xin; Wang, Ran; Yan, Debao; Zhao, Qi

    2017-10-01

    Laser-induced fluorescence(LIFS), which is one of most effective discrimination methods to identify the material at the molecular level by inducing fluorescence spectrum, has been popularized for its fast and accurate probe's results. According to the research, violet laser or ultraviolet laser is always used as excitation light source. While, There is no atmospheric window for violet laser and ultraviolet laser, causing laser attenuation along its propagation path. What's worse, as the laser reaching sample, part of the light is reflected. That is, excitation laser really react on sample to produce fluorescence is very poor, leading to weak fluorescence mingled with the background light collected by LIFS' processing unit, when it used outdoor. In order to spread LIFS to remote probing under the complex background, study of improving signal-noise ratio for fluorescence channel is a meaningful work. Enhancing the fluorescence intensity and inhibiting background light both can improve fluorescence' signal-noise ratio. In this article, three different approaches of inhibiting background light are discussed to improve the signal-noise ratio of LIFS. The first method is increasing fluorescence excitation area in the proportion of LIFS' collecting field by expanding laser beam, if the collecting filed is fixed. The second one is changing field angle base to accommodate laser divergence angle. The third one is setting a very narrow gating circuit to control acquisition circuit, which is shortly open only when fluorescence arriving. At some level, these methods all can reduce the background light. But after discussion, the third one is best with adding gating acquisition circuit to acquisition circuit instead of changing light path, which is effective and economic.

  18. A hypothetical model for predicting the toxicity of high aspect ratio nanoparticles (HARN)

    Science.gov (United States)

    Tran, C. L.; Tantra, R.; Donaldson, K.; Stone, V.; Hankin, S. M.; Ross, B.; Aitken, R. J.; Jones, A. D.

    2011-12-01

    The ability to predict nanoparticle (dimensional structures which are less than 100 nm in size) toxicity through the use of a suitable model is an important goal if nanoparticles are to be regulated in terms of exposures and toxicological effects. Recently, a model to predict toxicity of nanoparticles with high aspect ratio has been put forward by a consortium of scientists. The High aspect ratio nanoparticles (HARN) model is a platform that relates the physical dimensions of HARN (specifically length and diameter ratio) and biopersistence to their toxicity in biological environments. Potentially, this model is of great public health and economic importance, as it can be used as a tool to not only predict toxicological activity but can be used to classify the toxicity of various fibrous nanoparticles, without the need to carry out time-consuming and expensive toxicology studies. However, this model of toxicity is currently hypothetical in nature and is based solely on drawing similarities in its dimensional geometry with that of asbestos and synthetic vitreous fibres. The aim of this review is two-fold: (a) to present findings from past literature, on the physicochemical property and pathogenicity bioassay testing of HARN (b) to identify some of the challenges and future research steps crucial before the HARN model can be accepted as a predictive model. By presenting what has been done, we are able to identify scientific challenges and research directions that are needed for the HARN model to gain public acceptance. Our recommendations for future research includes the need to: (a) accurately link physicochemical data with corresponding pathogenicity assay data, through the use of suitable reference standards and standardised protocols, (b) develop better tools/techniques for physicochemical characterisation, (c) to develop better ways of monitoring HARN in the workplace, (d) to reliably measure dose exposure levels, in order to support future epidemiological

  19. A hypothetical model for predicting the toxicity of high aspect ratio nanoparticles (HARN)

    International Nuclear Information System (INIS)

    Tran, C. L.; Tantra, R.; Donaldson, K.; Stone, V.; Hankin, S. M.; Ross, B.; Aitken, R. J.; Jones, A. D.

    2011-01-01

    The ability to predict nanoparticle (dimensional structures which are less than 100 nm in size) toxicity through the use of a suitable model is an important goal if nanoparticles are to be regulated in terms of exposures and toxicological effects. Recently, a model to predict toxicity of nanoparticles with high aspect ratio has been put forward by a consortium of scientists. The High aspect ratio nanoparticles (HARN) model is a platform that relates the physical dimensions of HARN (specifically length and diameter ratio) and biopersistence to their toxicity in biological environments. Potentially, this model is of great public health and economic importance, as it can be used as a tool to not only predict toxicological activity but can be used to classify the toxicity of various fibrous nanoparticles, without the need to carry out time-consuming and expensive toxicology studies. However, this model of toxicity is currently hypothetical in nature and is based solely on drawing similarities in its dimensional geometry with that of asbestos and synthetic vitreous fibres. The aim of this review is two-fold: (a) to present findings from past literature, on the physicochemical property and pathogenicity bioassay testing of HARN (b) to identify some of the challenges and future research steps crucial before the HARN model can be accepted as a predictive model. By presenting what has been done, we are able to identify scientific challenges and research directions that are needed for the HARN model to gain public acceptance. Our recommendations for future research includes the need to: (a) accurately link physicochemical data with corresponding pathogenicity assay data, through the use of suitable reference standards and standardised protocols, (b) develop better tools/techniques for physicochemical characterisation, (c) to develop better ways of monitoring HARN in the workplace, (d) to reliably measure dose exposure levels, in order to support future epidemiological

  20. Kill ratio calculation for in-line yield prediction

    Science.gov (United States)

    Lorenzo, Alfonso; Oter, David; Cruceta, Sergio; Valtuena, Juan F.; Gonzalez, Gerardo; Mata, Carlos

    1999-04-01

    The search for better yields in IC manufacturing calls for a smarter use of the vast amount of data that can be generated by a world class production line.In this scenario, in-line inspection processes produce thousands of wafer maps, number of defects, defect type and pictures every day. A step forward is to correlate these with the other big data- generator area: test. In this paper, we present how these data can be put together and correlated to obtain a very useful yield predicting tool. This correlation will first allow us to calculate the kill ratio, i.e. the probability for a defect of a certain size in a certain layer to kill the die. Then we will use that number to estimate the cosmetic yield that a wafer will have.

  1. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling

    Directory of Open Access Journals (Sweden)

    Eric R. Edelman

    2017-06-01

    Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related

  2. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

    Science.gov (United States)

    Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A

    2017-01-01

    For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.

  3. Thermal fluctuation within nests and predicted sex ratio of Morelet's Crocodile.

    Science.gov (United States)

    Escobedo-Galván, Armando H; López-Luna, Marco A; Cupul-Magaña, Fabio G

    2016-05-01

    Understanding the interplay between thermal variations and sex ratio in reptiles with temperature-dependent sex determination is the first step for developing long-term conservation strategies. In case of crocodilians, the information is fragmentary and insufficient for establishing a general framework to consider how thermal fluctuation influence sex determination under natural conditions. The main goal of this study was to analyze thermal variation in nests of Crocodylus moreletii and to discuss the potential implications for predicting offspring sex ratio. The study was carried out at the Centro de Estudios Tecnológicos del Mar N° 2 and at the Sistemas Productivos Cocodrilo, Campeche, Mexico. Data was collected in the nesting season of Morelet's Crocodiles during three consecutive seasons (2007-2009). Thermal fluctuations for multiple areas of the nest chamber were registered by data loggers. We calculate the constant temperature equivalent based on thermal profiles among nests to assess whether there are differences between the nest temperature and its equivalent to constant temperature. We observed that mean nest temperature was only different among nests, while daily thermal fluctuations vary depending on the depth position within the nest chamber, years and nests. The constant temperature equivalent was different among and within nests, but not among survey years. We observed differences between constant temperature equivalent and mean nest temperature both at the top and in the middle of the nest cavities, but were not significantly different at the bottom of nest cavities. Our results enable examine and discuss the relevance of daily thermal fluctuations to predict sex ratio of the Morelet's Crocodile. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Strain histograms are equal to strain ratios in predicting malignancy in breast tumours

    DEFF Research Database (Denmark)

    Carlsen, Jonathan Frederik; Ewertsen, Caroline; Sletting, Susanne

    2017-01-01

    Objectives: To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS) 3 tumours for immediate biopsy. Methods: Ninety-nine breast tumours were examined using...

  5. Visible-near-infrared spectroscopy can predict the clay/organic carbon and mineral fines/organic carbon ratios

    DEFF Research Database (Denmark)

    Hermansen, Cecilie; Knadel, Maria; Møldrup, Per

    2016-01-01

    The ratios of mineral fines (carbon (OC), consisting of the n-ratio (i.e., the clay/OC ratio) and m-ratio (i.e., the fines/OC ratio) have recently been used to analyze and predict soil functional properties such as tilth conditions, clay dispersibility, degree...... from seven Danish and one Greenlandic fields, with a large textural range (clay: 0.027–0.355 kg kg−1; OC: 0.011–0.084 kg kg−1; n-ratio: 0.49–16.80; m-ratio: 1.46–32.14), were analyzed for texture and OC and subsequently scanned with a vis-NIR spectrometer from 400 to 2500 nm. The spectral data were...

  6. Predicting returns and rent growth in the housing market using the rent-to-price ratio: Evidence from the OECD countries

    DEFF Research Database (Denmark)

    Engsted, Tom; Pedersen, Thomas Quistgaard

    We investigate the predictive power of the rent-to-price ratio for future real estate returns and rent growth in 18 OECD countries over the period 1970 to 2011. First, we document that in most countries returns are signi…cantly predictable by the rent-price ratio. An increase (decrease...... dependent on whether returns and rents are measured in nominal or real terms. Finally, there is some evidence of sub-sample instability in the predictive patterns, especially wrt. rent growth predictability. The predictability tests are conducted within a restricted VAR framework based on the dynamic Gordon...

  7. Prediction of Pseudoexfoliation Syndrome and Pseudoexfoliation Glaucoma by Using Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio.

    Science.gov (United States)

    Ozgonul, Cem; Sertoglu, Erdim; Mumcuoglu, Tarkan; Ozge, Gokhan; Gokce, Gokcen

    2016-12-01

    To assess the levels of neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) in patients with pseudoexfoliation syndrome (PEX) and to compare the NLR and PLR results of patients with PEX, PEX glaucoma (PXG), and healthy controls. In total, 34 patients with PEX, 29 patients with PXG, and 42 healthy subjects were enrolled in this retrospective study. Complete ophthalmologic examination and complete blood count measurements were performed of all subjects. Complete blood counts were performed within 2 h of blood collection. There was a significant difference in NLR between PEX and control groups (p = 0.012) and PXG and control groups (p = 0.003). Also, a significant difference was found in PLR values between control and PXG groups (p = 0.024). Our study for the first time provides evidence that PLR and NLR may be useful for predicting the prognosis of PEX patients and progression to PXG.

  8. Earthquake predictions using seismic velocity ratios

    Science.gov (United States)

    Sherburne, R. W.

    1979-01-01

    Since the beginning of modern seismology, seismologists have contemplated predicting earthquakes. The usefulness of earthquake predictions to the reduction of human and economic losses and the value of long-range earthquake prediction to planning is obvious. Not as clear are the long-range economic and social impacts of earthquake prediction to a speicifc area. The general consensus of opinion among scientists and government officials, however, is that the quest of earthquake prediction is a worthwhile goal and should be prusued with a sense of urgency. 

  9. Improving Earth/Prediction Models to Improve Network Processing

    Science.gov (United States)

    Wagner, G. S.

    2017-12-01

    The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

  10. Watershed area ratio accurately predicts daily streamflow in nested catchments in the Catskills, New York

    Directory of Open Access Journals (Sweden)

    Chris C. Gianfagna

    2015-09-01

    New hydrological insights for the region: Watershed area ratio was the most important basin parameter for estimating flow at upstream sites based on downstream flow. The area ratio alone explained 93% of the variance in the slopes of relationships between upstream and downstream flows. Regression analysis indicated that flow at any upstream point can be estimated by multiplying the flow at a downstream reference gage by the watershed area ratio. This method accurately predicted upstream flows at area ratios as low as 0.005. We also observed a very strong relationship (R2 = 0.79 between area ratio and flow–flow slopes in non-nested catchments. Our results indicate that a simple flow estimation method based on watershed area ratios is justifiable, and indeed preferred, for the estimation of daily streamflow in ungaged watersheds in the Catskills region.

  11. Improving Hypertension Screening in Childhood Using Modified Blood Pressure to Height Ratio.

    Science.gov (United States)

    Dong, Bin; Wang, Zhiqiang; Wang, Hai-Jun; Ma, Jun

    2016-06-01

    Blood pressure to height ratio (BPHR) has been suggested as a simple method for screening children with hypertension, but its discriminatory ability in young children is not as good as that in older children. Using data of 89,664 Chinese children aged 7 to 11 years, the authors assessed whether modified BPHR (BP:eHT13) was better than BPHR in identifying young children with hypertension. BP:eHT13 was estimated as BP/(height+7×(13-age in years)). Using Youden's index, the thresholds of systolic/diastolic BP:eHT13 for identifying prehypertension and hypertension were 0.67/0.44 and 0.69/0.45, respectively. These proposed thresholds revealed high sensitivity, specificity, negative predictive value, and area under the curve (AUC), ranging from 0.874 to 0.999. In addition, BP:eHT13 showed better AUCs and fewer cutoff points than, if not similar to, two existing BPHR references. BP:eHT13 generally performed better than BPHR in discriminating BP abnormalities in young children and may improve early hypertension recognition and control. ©2015 Wiley Periodicals, Inc.

  12. The plasma leptin/adiponectin ratio predicts first cardiovascular event in men : A prospective nested case-control study

    NARCIS (Netherlands)

    Kappelle, Paul J.W.H.; Dullaart, Robin P. F.; van Beek, Andre P.; Hillege, Hans L.; Wolffenbuttel, Bruce H. R.

    2012-01-01

    Objective: The plasma leptin/adiponectin (L/A) ratio has been proposed as a preferential marker of atherosclerosis susceptibility compared to leptin and adiponectin alone. We determined the extent to which the L/A ratio predicts incident cardiovascular disease (CVD) taking account of clinical risk

  13. Decadal climate predictions improved by ocean ensemble dispersion filtering

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-06-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the whole ensemble with its

  14. Toxicity ratios: Their use and abuse in predicting the risk from induced cancer

    International Nuclear Information System (INIS)

    Mays, C.W.; Taylor, G.N.; Lloyd, R.D.

    1986-01-01

    The toxicity ratio concept assumes the validity of certain relationships. In some examples for bone sarcoma induction, the approximate toxicity of 239 Pu in man can be calculated algebraically from the observed toxicity in the radium-dial painters and the ratio of 239 Pu/ 226 Ra toxicities in suitable laboratory mammals. In a species highly susceptible to bone sarcoma induction, the risk coefficients for both 239 Pu and 226 Ra are elevated, but the toxicity ratio of 239 Pu to 226 Ra tends to be similar to the ratio in resistant species. Among the tested species the toxicity ratio of 239 Pu to 226 Ra ranged from 6 to 22 (a fourfold range), whereas their relative sensitivities to 239 Pu varied by a factor of 150. The toxicity ratio approach can also be used to estimate the actinide risk to man from liver cancer, by comparing to the Thorotrast patients; from lung cancer, by comparing to the uranium miners and the atomic-bomb survivors; and from neutron-induced cancers, by comparing to cancers induced by gamma rays. The toxicity ratio can be used to predict the risk to man from a specific type of cancer that has been reliably induced by a reference radiation in humans and that can be induced by both the reference and the investigated radiation in suitable laboratory animals. 26 refs., 3 figs., 1 tab

  15. Periodic TiO2 Nanostructures with Improved Aspect and Line/Space Ratio Realized by Colloidal Photolithography Technique

    Directory of Open Access Journals (Sweden)

    Loïc Berthod

    2017-10-01

    Full Text Available This paper presents substantial improvements of the colloidal photolithography technique (also called microsphere lithography with the goal of better controlling the geometry of the fabricated nano-scale structures—in this case, hexagonally arranged nanopillars—printed in a layer of directly photopatternable sol-gel TiO2. Firstly, to increase the achievable structure height the photosensitive layer underneath the microspheres is deposited on a reflective layer instead of the usual transparent substrate. Secondly, an increased width of the pillars is achieved by tilting the incident wave and using multiple exposures or substrate rotation, additionally allowing to better control the shape of the pillar’s cross section. The theoretical analysis is carried out by rigorous modelling of the photonics nanojet underneath the microspheres and by optimizing the experimental conditions. Aspect ratios (structure height/lateral structure size greater than 2 are predicted and demonstrated experimentally for structure dimensions in the sub micrometer range, as well as line/space ratios (lateral pillar size/distance between pillars greater than 1. These nanostructures could lead for example to materials exhibiting efficient light trapping in the visible and near-infrared range, as well as improved hydrophobic or photocatalytic properties for numerous applications in environmental and photovoltaic systems.

  16. Prediction of e± elastic scattering cross-section ratio based on phenomenological two-photon exchange corrections

    Science.gov (United States)

    Qattan, I. A.

    2017-06-01

    I present a prediction of the e± elastic scattering cross-section ratio, Re+e-, as determined using a new parametrization of the two-photon exchange (TPE) corrections to electron-proton elastic scattering cross section σR. The extracted ratio is compared to several previous phenomenological extractions, TPE hadronic calculations, and direct measurements from the comparison of electron and positron scattering. The TPE corrections and the ratio Re+e- show a clear change of sign at low Q2, which is necessary to explain the high-Q2 form factors discrepancy while being consistent with the known Q2→0 limit. While my predictions are in generally good agreement with previous extractions, TPE hadronic calculations, and existing world data including the recent two measurements from the CLAS and VEPP-3 Novosibirsk experiments, they are larger than the new OLYMPUS measurements at larger Q2 values.

  17. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

    Science.gov (United States)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

  18. Predictive Factors for Subjective Improvement in Lumbar Spinal Stenosis Patients with Nonsurgical Treatment: A 3-Year Prospective Cohort Study.

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    Ko Matsudaira

    Full Text Available To assess the predictive factors for subjective improvement with nonsurgical treatment in consecutive patients with lumbar spinal stenosis (LSS.Patients with LSS were enrolled from 17 medical centres in Japan. We followed up 274 patients (151 men; mean age, 71 ± 7.4 years for 3 years. A multivariable logistic regression model was used to assess the predictive factors for subjective symptom improvement with nonsurgical treatment.In 30% of patients, conservative treatment led to a subjective improvement in the symptoms; in 70% of patients, the symptoms remained unchanged, worsened, or required surgical treatment. The multivariable analysis of predictive factors for subjective improvement with nonsurgical treatment showed that the absence of cauda equina symptoms (only radicular symptoms had an odds ratio (OR of 3.31 (95% confidence interval [CI]: 1.50-7.31; absence of degenerative spondylolisthesis/scoliosis had an OR of 2.53 (95% CI: 1.13-5.65; <1-year duration of illness had an OR of 3.81 (95% CI: 1.46-9.98; and hypertension had an OR of 2.09 (95% CI: 0.92-4.78.The predictive factors for subjective symptom improvement with nonsurgical treatment in LSS patients were the presence of only radicular symptoms, absence of degenerative spondylolisthesis/scoliosis, and an illness duration of <1 year.

  19. Neutrophil-to-Lymphocyte Ratio in the Prediction of Microscopic Colitis

    Directory of Open Access Journals (Sweden)

    Feyzullah Ucmak

    2016-01-01

    Full Text Available Aim: The aim of this study was to investigate the importance of the neutrophil-to-lymphocyte ratio (NLR in predicting microscopic colitis (MC in patients with diarrhea-dominant type irritable bowel syndrome (IBS-D. Material and Method: Between January 1, 2010 and December 31, 2012, 49 patients who fulfilled the Roma III criteria for IBS-D were included in the study. All patients had underwent colonoscopy and colonoscopic biopsy (cecum, ascending, transverse, descending and rectosigmoid sections to diagnose MC (25 patients with MC. Complete blood count parameters were evaluated in the two groups (IBS-D and MC using standard methodology. Results: The patients were evaluated in two groups: MC and IBS-D. The groups were similar with respect to age, gender and presence of hypertension. The NLO was significantly higher in the MC group compared to the IBS-D group (2.48±0.99, 1.92±0.84; p=0.041, respectively. A cut-off value of 1.86 had a sensitivity of 76% and spesificity of 55% in predicting MC in patients with symptoms of IBS-D. Discussion: A significant association was found between the presence of MC in patients with IBS-D and increased NLR. The NLR may be a useful marker in predicting MC in patients with symptoms of IBS-D.

  20. Prediction of facial height, width, and ratio from thumbprints ridge count and its possible applications

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    Lawan Hassan Adamu

    2017-01-01

    Full Text Available The fingerprints and face recognition are two biometric processes that comprise methods for uniquely recognizing humans based on certain number of intrinsic physical or behavioral traits. The objectives of the study were to predict the facial height (FH, facial width, and ratios from thumbprints ridge count and its possible applications. This was a cross-sectional study. A total of 457 participants were recruited. A fingerprint live scanner was used to capture the plain thumbprint. The facial photograph was captured using a digital camera. Pearson's correlation analysis was used for the relationship between thumbprint ridge density and facial linear dimensions. Step-wise linear multiple regression analysis was used to predict facial distances from thumbprint ridge density. The result showed that in males the right ulnar ridge count correlates negatively with lower facial width (LFW, upper facial width/upper FH (UFW/UFH, lower FH/FH (LFH/FH, and positively with UFH and UFW/LFW. The right and left proximal ridge counts correlate with LFW and UFH, respectively. In males, the right ulnar ridge count predicts LFW, UFW/LFW, UFW/UFH, and LFH/FH. Special upper face height I, LFW, height of lower third of the face, UFW/LFW was predicted by right radial ridge counts. LFH, height of lower third of the face, and LFH/FH were predicted from left ulnar ridge count whereas left proximal ridge count predicted LFW. In females only, the special upper face height I was predicted by right ulnar ridge count. In conclusion, thumbprint ridge counts can be used to predict FH, width, ratios among Hausa population. The possible application of fingerprints in facial characterization for used in human biology, paleodemography, and forensic science was demonstrated.

  1. Usefulness of Eosinophil-Lymphocyte Ratio to Predict Stent Restenosis

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    Mehmet Zihni Bilik

    2016-06-01

    Full Text Available Objective: Stent restenosis (SR is an important compli­cation of percutaneous coronary intervention. There are many studies explored the relation of eosinophils with SR, however, there is no data about relationship between eo­sinophil-lymphocyte ratio (ELR and SR. In this study we aimed to investigate the relationship between the value of ELR on admission and SR. Methods: The study was included 314 patients who had been applied a coronary stent implantation and they were admitted to cardiology clinic with stabile angina and un­derwent repeat coronary angiography. The data obtained from patients were analyzed retrospectively. The patient group was consisted of 197 patients who were diagnosed as SR, and the control group was consisted of 117 pa­tients whose stents were patent angiographically. Results: The groups were similar in terms of age, gender, hypertension, diabetes mellitus, LDL-C, HDL-C, platelet count, platelet-lymphocyte ratio (PLR, hemoglobin and left ventricle ejection fraction (LVEF. White blood cell (WBC, neutrophil, eosinophil, C-reactive protein (CRP, ELR and neutrophil-lymphocyte ratio (NLR on admission were higher in the SR group compared to the controls. All patients were categorized into two groups according to ELR values and SR was more frequent in the high ELR group compared to low ELR group. An ELR value of ≥0.745 predicted SR with 64% sensitivity and 61% specif­ity. Conclusion: In this study ELR was found statistically higher in SR patients compared to the controls. Accord­ing to our data ELR as an inexpensive and easy method, may contribute to determination of high risk patients and increased ELR can be used as a predictor of SR.

  2. Blade tip, finite aspect ratio, and dynamic stall effects on the Darrieus rotor

    Science.gov (United States)

    Paraschivoiu, I.; Desy, P.; Masson, C.

    1988-02-01

    The objective of the work described in this paper was to apply the Boeing-Vertol dynamic stall model in an asymmetric manner to account for the asymmetry of the flow between the left and right sides of the rotor. This phenomenon has been observed by the flow visualization of a two-straight-bladed Darrieus rotor in the IMST water tunnel. Also introduced into the aerodynamic model are the effects of the blade tip and finite aspect ratio on the aerodynamic performance of the Darrieus wind turbine. These improvements are compatible with the double-multiple-streamtube model and have been included in the CARDAAV computer code for predicting the aerodynamic performance. Very good agreement has been observed between the test data (Sandia 17 m) and theoretical predictions; a significant improvement over the previous dynamic stall model was obtained for the rotor power at low tip speed ratios, while the inclusion of the finite aspect ratio effects enhances the prediction of the rotor power for high tip speed ratios. The tip losses and finite aspect ratio effects were also calculated for a small-scale vertical-axis wind turbine, with a two-straight-bladed (NACA 0015) rotor.

  3. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  4. Phytate/calcium molar ratio does not predict accessibility of calcium in ready-to-eat dishes.

    Science.gov (United States)

    Erba, Daniela; Manini, Federica; Meroni, Erika; Casiraghi, Maria C

    2017-08-01

    Phytic acid (PA), a naturally occurring compound of plant food, is generally considered to affect mineral bioavailability. The aim of this study was to investigate the reliability of the PA/calcium molar ratio as a predictive factor of calcium accessibility in composed dishes and their ingredients. Dishes were chosen whose ingredients were rich in Ca (milk or cheese) or in PA (whole-wheat cereals) in order to consider a range of PA/Ca ratios (from 0 to 2.4) and measure Ca solubility using an in vitro approach. The amounts of soluble Ca in composed dishes were consistent with the sum of soluble Ca from ingredients (three out of five meals) or higher. Among whole-wheat products, bread showed higher Ca accessibility (71%, PA/Ca = 1.1) than biscuits (23%, PA/Ca = 0.9) and pasta (15%, PA/Ca = 1.5), and among Ca-rich ingredients, semi-skimmed milk displayed higher Ca accessibility (64%) than sliced cheese (50%) and Parmesan (38%). No significant correlation between the PA/Ca ratio and Ca accessibility was found (P = 0.077). The reliability of the PA/Ca ratio for predicting the availability of calcium in composed dishes is unsatisfactory; data emphasized the importance of the overall food matrix influence on mineral accessibility. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  5. Optimum Installation of Sorptive Building Materials Using Contribution Ratio of Pollution Source for Improvement of Indoor Air Quality.

    Science.gov (United States)

    Park, Seonghyun; Seo, Janghoo

    2016-04-01

    Reinforcing the insulation and airtightness of buildings and the use of building materials containing new chemical substances have caused indoor air quality problems. Use of sorptive building materials along with removal of pollutants, constant ventilation, bake-out, etc. are gaining attention in Korea and Japan as methods for improving such indoor air quality problems. On the other hand, sorptive building materials are considered a passive method of reducing the concentration of pollutants, and their application should be reviewed in the early stages. Thus, in this research, activated carbon was prepared as a sorptive building material. Then, computational fluid dynamics (CFD) was conducted, and a method for optimal installation of sorptive building materials was derived according to the indoor environment using the contribution ratio of pollution source (CRP) index. The results show that a method for optimal installation of sorptive building materials can be derived by predicting the contribution ratio of pollutant sources according to the CRP index.

  6. Improved Modeling and Prediction of Surface Wave Amplitudes

    Science.gov (United States)

    2017-05-31

    AFRL-RV-PS- AFRL-RV-PS- TR-2017-0162 TR-2017-0162 IMPROVED MODELING AND PREDICTION OF SURFACE WAVE AMPLITUDES Jeffry L. Stevens, et al. Leidos...data does not license the holder or any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented...SUBTITLE Improved Modeling and Prediction of Surface Wave Amplitudes 5a. CONTRACT NUMBER FA9453-14-C-0225 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER

  7. Budget impact analysis of sFlt-1/PlGF ratio as prediction test in Italian women with suspected preeclampsia.

    Science.gov (United States)

    Frusca, Tiziana; Gervasi, Maria-Teresa; Paolini, Davide; Dionisi, Matteo; Ferre, Francesca; Cetin, Irene

    2017-09-01

    Preeclampsia (PE) is a pregnancy disease which represents a leading cause of maternal and perinatal mortality and morbidity. Accurate prediction of PE risk could provide an increase in health benefits and better patient management. To estimate the economic impact of introducing Elecsys sFlt-1/PlGF ratio test, in addition to standard practice, for the prediction of PE in women with suspected PE in the Italian National Health Service (INHS). A decision tree model has been developed to simulate the progression of a cohort of pregnant women from the first presentation of clinical suspicion of PE in the second and third trimesters until delivery. The model provides an estimation of the financial impact of introducing sFlt-1/PlGF versus standard practice. Clinical inputs have been derived from PROGNOSIS study and from literature review, and validated by National Clinical Experts. Resources and unit costs have been obtained from Italian-specific sources. Healthcare costs associated with the management of a pregnant woman with clinical suspicion of PE equal €2384 when following standard practice versus €1714 using sFlt-1/PlGF ratio test. Introduction of sFlt-1/PlGF into hospital practice is cost-saving. Savings are generated primarily through improvement in diagnostic accuracy and reduction in unnecessary hospitalization for women before PE's onset.

  8. Improving contact prediction along three dimensions.

    Directory of Open Access Journals (Sweden)

    Christoph Feinauer

    2014-10-01

    Full Text Available Correlation patterns in multiple sequence alignments of homologous proteins can be exploited to infer information on the three-dimensional structure of their members. The typical pipeline to address this task, which we in this paper refer to as the three dimensions of contact prediction, is to (i filter and align the raw sequence data representing the evolutionarily related proteins; (ii choose a predictive model to describe a sequence alignment; (iii infer the model parameters and interpret them in terms of structural properties, such as an accurate contact map. We show here that all three dimensions are important for overall prediction success. In particular, we show that it is possible to improve significantly along the second dimension by going beyond the pair-wise Potts models from statistical physics, which have hitherto been the focus of the field. These (simple extensions are motivated by multiple sequence alignments often containing long stretches of gaps which, as a data feature, would be rather untypical for independent samples drawn from a Potts model. Using a large test set of proteins we show that the combined improvements along the three dimensions are as large as any reported to date.

  9. Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects?

    Directory of Open Access Journals (Sweden)

    Lu Liping

    2011-01-01

    Full Text Available Abstract Background Obesity is associated with metabolic risk factors. Body mass index (BMI, waist circumference, waist-hip ratio (WHR and waist-height ratio (WHtR are used to predict the risk of obesity related diseases. However, it has not been examined whether these four indicators can detect the clustering of metabolic risk factors in Chinese subjects. Methods There are 772 Chinese subjects in the present study. Metabolic risk factors including high blood pressure, dyslipidemia, and glucose intolerance were identified according to the criteria from WHO. All statistical analyses were performed separately according to sex by using the SPSS 12.0. Results BMI, waist circumference and WHtR values were all significantly associated with blood pressure, glucose, triglyceride and also with the number of metabolic risk factors in both male and female subjects (all of P Conclusion The BMI, waist circumference and WHtR values can similarly predict the presence of multiple metabolic risk factors in Chinese subjects.

  10. The Torg-Pavlov ratio for the prediction of acute spinal cord injury after a minor trauma to the cervical spine.

    Science.gov (United States)

    Aebli, Nikolaus; Wicki, Anina G; Rüegg, Tabea B; Petrou, Nassos; Eisenlohr, Heidrun; Krebs, Jörg

    2013-06-01

    Acute cervical spinal cord injury (SCI) has been observed in some patients after a minor trauma to the cervical spine. The discrepancy between the severity of the trauma and the clinical symptoms has been attributed to spinal canal stenosis. However, to date, there is no universally established radiological parameter for identifying critical spinal stenosis in these patients. The spinal canal-to-vertebral body ratio (Torg-Pavlov ratio) has been proposed for assessing developmental spinal canal stenosis. The relevance of the Torg-Pavlov ratio for predicting the occurrence and severity of acute cervical SCI after a minor trauma to the cervical spine has not yet been established. To investigate the Torg-Pavlov ratio values of the cervical spine in patients suffering from acute cervical SCI after a minor trauma to the cervical spine and the use of the Torg-Pavlov ratio for identifying patients at risk of cervical SCI and predicting the severity and course of symptoms. Retrospective radiological study of consecutive patients. Forty-five patients suffering from acute cervical SCI and 68 patients showing no neurologic symptoms after a minor trauma to the cervical spine. Midvertebral sagittal cervical spinal canal diameter and the sagittal vertebral body diameter. Calculation of the Torg-Pavlov ratio values. Conventional lateral radiographs of the cervical spine (C3-C7) were analyzed to determine the Torg-Pavlov ratio values. Receiver operating characteristic curves were calculated for evaluating the classification accuracy of the Torg-Pavlov ratio for predicting SCI. The Torg-Pavlov ratio values in the SCI group were significantly (pPavlov ratio cutoff value of 0.7 yielded the greatest positive likelihood ratio for predicting the occurrence of SCI. However, there were no significant differences in the Torg-Pavlov ratio values between the different American Spinal Injury Association Impairment Score groups and between patients with complete, partial, and no recovery of

  11. Text mining improves prediction of protein functional sites.

    Directory of Open Access Journals (Sweden)

    Karin M Verspoor

    Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

  12. Text Mining Improves Prediction of Protein Functional Sites

    Science.gov (United States)

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

  13. Is The Ca + K + Mg/Al Ratio in the Soil Solution a Predictive Tool for Estimating Forest Damage?

    International Nuclear Information System (INIS)

    Goeransson, A.; Eldhuset, T. D.

    2001-01-01

    The ratio between (Ca +K +Mg) and Al in nutrient solution has been suggested as a predictive tool for estimating tree growth disturbance. However, the ratio is unspecific in the sense that it is based on several elements which are all essential for plant growth;each of these may be growth-limiting. Furthermore,aluminium retards growth at higher concentrations. Itis therefore difficult to give causal and objective biological explanations for possible growth disturbances. The importance of the proportion of base-cations to N, at a fixed base-cation/Al ratio, is evaluated with regard to growth of Picea abies.The uptake of elements was found to be selective; nutrients were taken up while most Al remained in solution. Biomass partitioning to the roots increased after aluminium addition with low proportions of basecations to nitrogen. We conclude that the low growthrates depend on nutrient limitation in these treatments. Low growth rates in the high proportion experiments may be explained by high internal Alconcentrations. The results strongly suggest that growth rate is not correlated with the ratio in the rooting medium and question the validity of using ratios as predictive tools for estimating forest damage. We suggest that growth limitation of Picea abies in the field may depend on low proportions of base cations to nitrate. It is therefore important to know the nutritional status of the plant material in relation to the growth potential and environmental limitation to be able to predict and estimate forest damage

  14. The Neutrophil to Lymphocyte Ratio May Predict Benefit from Chemotherapy in Lung Cancer

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    Dan Liu

    2018-04-01

    Full Text Available Background/Aims: The objectives of this study were to evaluate the impact of the neutrophil to lymphocyte ratio (NLR and platelet to lymphocyte ratio (PLR on overall survival (OS and to explore the value of changes in the NLR and PLR with treatment as a response indicator. Methods: A total of 934 patients were eligible for retrospective analysis between 2008 and 2014. The pretreatment and post-treatment PLR and NLR in all patients were calculated based on complete blood counts. Univariate and multivariate Cox regression analyses were performed to determine the associations of the PLR and NLR with OS. Results: The pretreatment NLR and PLR were correlated with different disease status and response to chemotherapy. Patients with lower NLR and PLR had a significantly better complete response (CR rate to chemotherapy versus those with a higher NLR and PLR (p< 0.001. The NLR and PLR were sustained in patients who obtained a CR compared with moderate or poor response patients. The lower NLR of pretreatment was independently associated with a favourable prognosis in whole patients with lung cancer (HR: 0.69, 95% CI, 0.55-0.85, p< 0.001. In the patients under control after chemotherapy, the NLR of post-chemotherapy had a greater impact on survival, and the low NLR level maintained during chemotherapy was identified a predictor for favourable survival. PLR was not an independent prognostic indicator in the whole cohort or any subgroups. Conclusion: Our results suggested that NLR was well-connected with outcomes and response to chemotherapy in patients with lung cancer. As a response indicator, NLR may predict benefit from chemotherapy and improve patient selection.

  15. Predictive value of neutrophil-to-lymphocyte ratio in diabetic wound healing.

    Science.gov (United States)

    Vatankhah, Nasibeh; Jahangiri, Younes; Landry, Gregory J; McLafferty, Robert B; Alkayed, Nabil J; Moneta, Gregory L; Azarbal, Amir F

    2017-02-01

    The neutrophil-to-lymphocyte ratio (NLR) has been used as a surrogate marker of systemic inflammation. We sought to investigate the association between NLR and wound healing in diabetic wounds. The outcomes of 120 diabetic foot ulcers in 101 patients referred from August 2011 to December 2014 were examined retrospectively. Demographic, patient-specific, and wound-specific variables as well as NLR at baseline visit were assessed. Outcomes were classified as ulcer healing, minor amputation, major amputation, and chronic ulcer. The subjects' mean age was 59.4 ± 13.0 years, and 67 (66%) were male. Final outcome was complete healing in 24 ulcers (20%), minor amputation in 58 (48%) and major amputation in 16 (13%), and 22 chronic ulcers (18%) at the last follow-up (median follow-up time, 6.8 months). In multivariate analysis, higher NLR (odds ratio, 13.61; P = .01) was associated with higher odds of nonhealing. NLR can predict odds of complete healing in diabetic foot ulcers independent of wound infection and other factors. Copyright © 2016 Society for Vascular Surgery. All rights reserved.

  16. Prediction of hole expansion ratio for various steel sheets based on uniaxial tensile properties

    Science.gov (United States)

    Kim, Jae Hyung; Kwon, Young Jin; Lee, Taekyung; Lee, Kee-Ahn; Kim, Hyoung Seop; Lee, Chong Soo

    2018-01-01

    Stretch-flangeability is one of important formability parameters of thin steel sheets used in the automotive industry. There have been many attempts to predict hole expansion ratio (HER), a typical term to evaluate stretch-flangeability, using uniaxial tensile properties for convenience. This paper suggests a new approach that uses total elongation and average normal anisotropy to predict HER of thin steel sheets. The method provides a good linear relationship between HER of the machined hole and the predictive variables in a variety of materials with different microstructures obtained using different processing methods. The HER of the punched hole was also well predicted using the similar approach, which reflected only the portion of post uniform elongation. The physical meaning drawn by our approach successfully explained the poor HER of austenitic steels despite their considerable elongation. The proposed method to predict HER is simple and cost-effective, so it will be useful in industry. In addition, the model provides a physical explanation of HER, so it will be useful in academia.

  17. Improvement of PM10 prediction in East Asia using inverse modeling

    Science.gov (United States)

    Koo, Youn-Seo; Choi, Dae-Ryun; Kwon, Hi-Yong; Jang, Young-Kee; Han, Jin-Seok

    2015-04-01

    Aerosols from anthropogenic emissions in industrialized region in China as well as dust emissions from southern Mongolia and northern China that transport along prevailing northwestern wind have a large influence on the air quality in Korea. The emission inventory in the East Asia region is an important factor in chemical transport modeling (CTM) for PM10 (particulate matters less than 10 ㎛ in aerodynamic diameter) forecasts and air quality management in Korea. Most previous studies showed that predictions of PM10 mass concentration by the CTM were underestimated when comparing with observational data. In order to fill the gap in discrepancies between observations and CTM predictions, the inverse Bayesian approach with Comprehensive Air-quality Model with extension (CAMx) forward model was applied to obtain optimized a posteriori PM10 emissions in East Asia. The predicted PM10 concentrations with a priori emission were first compared with observations at monitoring sites in China and Korea for January and August 2008. The comparison showed that PM10 concentrations with a priori PM10 emissions for anthropogenic and dust sources were generally under-predicted. The result from the inverse modeling indicated that anthropogenic PM10 emissions in the industrialized and urbanized areas in China were underestimated while dust emissions from desert and barren soil in southern Mongolia and northern China were overestimated. A priori PM10 emissions from northeastern China regions including Shenyang, Changchun, and Harbin were underestimated by about 300% (i.e., the ratio of a posteriori to a priori PM10 emission was a factor of about 3). The predictions of PM10 concentrations with a posteriori emission showed better agreement with the observations, implying that the inverse modeling minimized the discrepancies in the model predictions by improving PM10 emissions in East Asia.

  18. Efficacy of specific gravity as a tool for prediction of biodiesel-petroleum diesel blend ratio

    Science.gov (United States)

    Prediction of volumetric biodiesel/petrodiesel blend ratio (VBD) from specific gravity (SG) data was the subject of the current investigation. Fatty acid methyl esters obtained from soybean, palm, and rapeseed oils along with chicken fat (SME-1, SME-2, PME, RME, and CFME) were blended (0 to 20 volum...

  19. Improving orbit prediction accuracy through supervised machine learning

    Science.gov (United States)

    Peng, Hao; Bai, Xiaoli

    2018-05-01

    Due to the lack of information such as the space environment condition and resident space objects' (RSOs') body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs' trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO's orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.

  20. Combining gene prediction methods to improve metagenomic gene annotation

    Directory of Open Access Journals (Sweden)

    Rosen Gail L

    2011-01-01

    Full Text Available Abstract Background Traditional gene annotation methods rely on characteristics that may not be available in short reads generated from next generation technology, resulting in suboptimal performance for metagenomic (environmental samples. Therefore, in recent years, new programs have been developed that optimize performance on short reads. In this work, we benchmark three metagenomic gene prediction programs and combine their predictions to improve metagenomic read gene annotation. Results We not only analyze the programs' performance at different read-lengths like similar studies, but also separate different types of reads, including intra- and intergenic regions, for analysis. The main deficiencies are in the algorithms' ability to predict non-coding regions and gene edges, resulting in more false-positives and false-negatives than desired. In fact, the specificities of the algorithms are notably worse than the sensitivities. By combining the programs' predictions, we show significant improvement in specificity at minimal cost to sensitivity, resulting in 4% improvement in accuracy for 100 bp reads with ~1% improvement in accuracy for 200 bp reads and above. To correctly annotate the start and stop of the genes, we find that a consensus of all the predictors performs best for shorter read lengths while a unanimous agreement is better for longer read lengths, boosting annotation accuracy by 1-8%. We also demonstrate use of the classifier combinations on a real dataset. Conclusions To optimize the performance for both prediction and annotation accuracies, we conclude that the consensus of all methods (or a majority vote is the best for reads 400 bp and shorter, while using the intersection of GeneMark and Orphelia predictions is the best for reads 500 bp and longer. We demonstrate that most methods predict over 80% coding (including partially coding reads on a real human gut sample sequenced by Illumina technology.

  1. Improved Wind Speed Prediction Using Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    ZHANG, Y.

    2018-05-01

    Full Text Available Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD, the Radial Basis Function Neural Network (RBF and the Least Square Support Vector Machine (SVM, an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM, the EMD-RBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power.

  2. Improvement of gas entrainment prediction method. Introduction of surface tension effect

    International Nuclear Information System (INIS)

    Ito, Kei; Sakai, Takaaki; Ohshima, Hiroyuki; Uchibori, Akihiro; Eguchi, Yuzuru; Monji, Hideaki; Xu, Yongze

    2010-01-01

    A gas entrainment (GE) prediction method has been developed to establish design criteria for the large-scale sodium-cooled fast reactor (JSFR) systems. The prototype of the GE prediction method was already confirmed to give reasonable gas core lengths by simple calculation procedures. However, for simplification, the surface tension effects were neglected. In this paper, the evaluation accuracy of gas core lengths is improved by introducing the surface tension effects into the prototype GE prediction method. First, the mechanical balance between gravitational, centrifugal, and surface tension forces is considered. Then, the shape of a gas core tip is approximated by a quadratic function. Finally, using the approximated gas core shape, the authors determine the gas core length satisfying the mechanical balance. This improved GE prediction method is validated by analyzing the gas core lengths observed in simple experiments. Results show that the analytical gas core lengths calculated by the improved GE prediction method become shorter in comparison to the prototype GE prediction method, and are in good agreement with the experimental data. In addition, the experimental data under different temperature and surfactant concentration conditions are reproduced by the improved GE prediction method. (author)

  3. Plant water potential improves prediction of empirical stomatal models.

    Directory of Open Access Journals (Sweden)

    William R L Anderegg

    Full Text Available Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

  4. PROBABILISTIC PREDICTION OF BANK FAILURES WITH FINANCIAL RATIOS: AN EMPIRICAL STUDY ON TURKISH BANKS

    Directory of Open Access Journals (Sweden)

    Gamze Özel

    2014-02-01

    Full Text Available Banking risk management has become more important during the last 20 years in response to a worldwide increase in the number of bank failures. Turkey has experienced a series of economic and financial crisis since the declaration of Republic and banking system has the most affected sector from the results of these crises. This paper examines some bank failure prediction models using financial ratios. Survival, ordinary and conditional logistic regression models are employed in order to develop these prediction models. The empirical results indicate that the bank is more likely to go bankrupt if it is unprofitable, small, highly leveraged, and has liquidity problems and less financial flexibility to invest itself. 

  5. Triglycerides to High-Density Lipoprotein Cholesterol Ratio Can Predict Impaired Glucose Tolerance in Young Women with Polycystic Ovary Syndrome.

    Science.gov (United States)

    Song, Do Kyeong; Lee, Hyejin; Sung, Yeon Ah; Oh, Jee Young

    2016-11-01

    The triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio could be related to insulin resistance (IR). We previously reported that Korean women with polycystic ovary syndrome (PCOS) had a high prevalence of impaired glucose tolerance (IGT). We aimed to determine the cutoff value of the TG/HDL-C ratio for predicting IR and to examine whether the TG/HDL-C ratio is useful for identifying individuals at risk of IGT in young Korean women with PCOS. We recruited 450 women with PCOS (24±5 yrs) and performed a 75-g oral glucose tolerance test (OGTT). IR was assessed by a homeostasis model assessment index over that of the 95th percentile of regular-cycling women who served as the controls (n=450, 24±4 yrs). The cutoff value of the TG/HDL-C ratio for predicting IR was 2.5 in women with PCOS. Among the women with PCOS who had normal fasting glucose (NFG), the prevalence of IGT was significantly higher in the women with PCOS who had a high TG/HDL-C ratio compared with those with a low TG/HDL-C ratio (15.6% vs. 5.6%, p2.5 are recommended to be administered an OGTT to detect IGT even if they have NFG.

  6. GPS Modeling and Analysis. Summary of Research: GPS Satellite Axial Ratio Predictions

    Science.gov (United States)

    Axelrad, Penina; Reeh, Lisa

    2002-01-01

    This report outlines the algorithms developed at the Colorado Center for Astrodynamics Research to model yaw and predict the axial ratio as measured from a ground station. The algorithms are implemented in a collection of Matlab functions and scripts that read certain user input, such as ground station coordinates, the UTC time, and the desired GPS (Global Positioning System) satellites, and compute the above-mentioned parameters. The position information for the GPS satellites is obtained from Yuma almanac files corresponding to the prescribed date. The results are displayed graphically through time histories and azimuth-elevation plots.

  7. Second-to-fourth digit ratio predicts success among high-frequency financial traders.

    Science.gov (United States)

    Coates, John M; Gurnell, Mark; Rustichini, Aldo

    2009-01-13

    Prenatal androgens have important organizing effects on brain development and future behavior. The second-to-fourth digit length ratio (2D:4D) has been proposed as a marker of these prenatal androgen effects, a relatively longer fourth finger indicating higher prenatal androgen exposure. 2D:4D has been shown to predict success in highly competitive sports. Yet, little is known about the effects of prenatal androgens on an economically influential class of competitive risk taking-trading in the financial world. Here, we report the findings of a study conducted in the City of London in which we sampled 2D:4D from a group of male traders engaged in what is variously called "noise" or "high-frequency" trading. We found that 2D:4D predicted the traders' long-term profitability as well as the number of years they remained in the business. 2D:4D also predicted the sensitivity of their profitability to increases both in circulating testosterone and in market volatility. Our results suggest that prenatal androgens increase risk preferences and promote more rapid visuomotor scanning and physical reflexes. The success and longevity of traders exposed to high levels of prenatal androgens further suggests that financial markets may select for biological traits rather than rational expectations.

  8. Yearbook sectoral financial ratios in mexico for business benchmarking

    Directory of Open Access Journals (Sweden)

    Deyanira Bernal Domínguez

    2012-05-01

    Full Text Available Financial analysis through ratios is a useful tool for improving organizational performance. Databases of financial information in Mexico are limited, therefore the importance of an annual publication of financial ratios per company and industry average. The objectives of this research are: describe the financial ratios with higher predictive potential and their formulas, as well as the design of a research instrument for measuring the relevance of the publication. A descriptive methodology was applied selecting through the analysis ofempirical studies, several ratios of liquidity, leverage, asset management, business cycle, performance and self-financing. The questionnaire contains 43 reagents to be applied to a statistically representative sample of 46 entrepreneurs in Culiacan, Sinaloa, Mexico.

  9. THE RELATIVE IMPORTANCE OF FINANCIAL RATIOS AND NONFINANCIAL VARIABLES IN PREDICTING OF INSOLVENCY

    Directory of Open Access Journals (Sweden)

    Ivica Pervan

    2013-02-01

    Full Text Available One of the most important decisions in every bank is approving loans to firms, which is based on evaluated credit risk and collateral. Namely, it is necessary to evaluate the risk that client will be unable to repay the obligations according to the contract. After Beaver's (1967 and Altman's (1968 seminal papers many authors extended the initial research by changing the methodology, samples, countries, etc. But majority of business failure papers as predictors use financial ratios, while in the real life banks combine financial and nonfinancial variables. In order to test predictive power of nonfinancial variables authors in the paper compare two insolvency prediction models. The first model that used financial rations resulted with classification accuracy of 82.8%, while the combined model with financial and nonfinancial variables resulted with classification accuracy of 88.1%.

  10. Can machine-learning improve cardiovascular risk prediction using routine clinical data?

    Science.gov (United States)

    Kai, Joe; Garibaldi, Jonathan M.; Qureshi, Nadeem

    2017-01-01

    Background Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Methods Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the ‘receiver operating curve’ (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). Findings 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723–0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739–0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755–0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755–0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759–0.769). The highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Conclusions Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others

  11. Interleukin-10 to tumor necrosis factor-alpha ratio is a predictive biomarker in nonalcoholic fatty liver disease: interleukin-10 to tumor necrosis factor-alpha ratio in steatohepatitis.

    Science.gov (United States)

    Hashem, Reem M; Mahmoud, Mona F; El-Moselhy, Mohamed A; Soliman, Hala M

    2008-10-01

    Fatty liver disease is commonly associated with diabetes mellitus (DM). Insulin resistance (IR) as an investigative biomarker is only concerned with fatty liver that results from DM type 2 associated with metabolic syndrome. Irrespective of IR, DM is generally characterized by overproduction of the proinflammatory cytokine tumor necrosis factor-alpha (TNF-alpha), whereas action of the latter is modulated by the anti-inflammatory cytokine interleukin-10 (IL-10). The aim of this study was to investigate the efficacy of using TNF-alpha alone or IL-10/TNF-alpha ratio compared to IR, as a promising biomarker for fatty liver assessment in DM. Furthermore, we hypothesized that using garlic as an immunomodulator may decrease TNF-alpha and increase IL-10 production to improve steatohepatitis. DM was induced metabolically by a high-fat diet to bring about IR, or chemically by alloxan, producing insulin deficiency, in male albino rats. Garlic powder was supplemented (15 mg/kg per day) for 3 weeks. Fatty liver was depicted histologically and biochemically (aspartic aminotransferase, alanine aminotransferase, HOMA-IR, TNF-alpha, IL-10, IL-10/TNF-alpha ratio). We found that, in contrast to obese rats, garlic decreased IL-10/TNF-alpha ratio, despite decreasing TNF-alpha in alloxan diabetic rats in agreement with the histology, which revealed more prominent improvement in the obese group. Moreover, the effect of garlic was not linked to improvement of IR in obese rats. We conclude that IL-10/TNF-alpha ratio may be considered as a convenient biomarker for investigation of fatty liver of different grades, apart from being associated with IR, and immunomodulation of this ratio in favor of increasing it may exert significant improvement.

  12. Recent Improvements in IERS Rapid Service/Prediction Center Products

    National Research Council Canada - National Science Library

    Stamatakos, N; Luzum, B; Wooden, W

    2007-01-01

    ...) at USNO has made several improvements to its combination and pre- diction products. These improvements are due to the inclusion of new input data sources as well as modifications to the combination and prediction algorithms...

  13. Evaluation of NO2 predictions by the plume volume molar ratio method (PVMRM) and ozone limiting method (OLM) in AERMOD using new field observations.

    Science.gov (United States)

    Hendrick, Elizabeth M; Tino, Vincent R; Hanna, Steven R; Egan, Bruce A

    2013-07-01

    The U.S. Environmental Protection Agency (EPA) plume volume molar ratio method (PVMRM) and the ozone limiting method (OLM) are in the AERMOD model to predict the 1-hr average NO2/NO(x) concentration ratio. These ratios are multiplied by the AERMOD predicted NO(x) concentration to predict the 1-hr average NO2 concentration. This paper first briefly reviews PVMRM and OLM and points out some scientific parameterizations that could be improved (such as specification of relative dispersion coefficients) and then discusses an evaluation of the PVMRM and OLM methods as implemented in AERMOD using a new data set. While AERMOD has undergone many model evaluation studies in its default mode, PVMRM and OLM are nondefault options, and to date only three NO2 field data sets have been used in their evaluations. Here AERMOD/PVMRM and AERMOD/OLM codes are evaluated with a new data set from a northern Alaskan village with a small power plant. Hourly pollutant concentrations (NO, NO2, ozone) as well as meteorological variables were measured at a single monitor 500 m from the plant. Power plant operating parameters and emissions were calculated based on hourly operator logs. Hourly observations covering 1 yr were considered, but the evaluations only used hours when the wind was in a 60 degrees sector including the monitor and when concentrations were above a threshold. PVMRM is found to have little bias in predictions of the C(NO2)/C(NO(x)) ratio, which mostly ranged from 0.2 to 0.4 at this site. OLM overpredicted the ratio. AERMOD overpredicts the maximum NO(x) concentration but has an underprediction bias for lower concentrations. AERMOD/PVMRM overpredicts the maximum C(NO2) by about 50%, while AERMOD/OLM overpredicts by a factor of 2. For 381 hours evaluated, there is a relative mean bias in C(NO2) predictions of near zero for AERMOD/PVMRM, while the relative mean bias reflects a factor of 2 overprediction for AERMOD/OLM. This study was initiated because the new stringent 1-hr NO2

  14. Optimization of the reflux ratio for a stage distillation column based on an improved particle swarm algorithm

    DEFF Research Database (Denmark)

    Ren, Jingzheng; Tan, Shiyu; Dong, Lichun

    2010-01-01

    A mathematical model relating operation profits with reflux ratio of a stage distillation column was established. In order to optimize the reflux ratio by solving the nonlinear objective function, an improved particle swarm algorithm was developed and has been proved to be able to enhance...... the searching ability of basic particle swarm algorithm significantly. An example of utilizing the improved algorithm to solve the mathematical model was demonstrated; the result showed that it is efficient and convenient to optimize the reflux ratio for a distillation column by using the mathematical model...

  15. Predicting prey population dynamics from kill rate, predation rate and predator-prey ratios in three wolf-ungulate systems.

    Science.gov (United States)

    Vucetich, John A; Hebblewhite, Mark; Smith, Douglas W; Peterson, Rolf O

    2011-11-01

    1. Predation rate (PR) and kill rate are both fundamental statistics for understanding predation. However, relatively little is known about how these statistics relate to one another and how they relate to prey population dynamics. We assess these relationships across three systems where wolf-prey dynamics have been observed for 41 years (Isle Royale), 19 years (Banff) and 12 years (Yellowstone). 2. To provide context for this empirical assessment, we developed theoretical predictions of the relationship between kill rate and PR under a broad range of predator-prey models including predator-dependent, ratio-dependent and Lotka-Volterra dynamics. 3. The theoretical predictions indicate that kill rate can be related to PR in a variety of diverse ways (e.g. positive, negative, unrelated) that depend on the nature of predator-prey dynamics (e.g. structure of the functional response). These simulations also suggested that the ratio of predator-to-prey is a good predictor of prey growth rate. That result motivated us to assess the empirical relationship between the ratio and prey growth rate for each of the three study sites. 4. The empirical relationships indicate that PR is not well predicted by kill rate, but is better predicted by the ratio of predator-to-prey. Kill rate is also a poor predictor of prey growth rate. However, PR and ratio of predator-to-prey each explained significant portions of variation in prey growth rate for two of the three study sites. 5. Our analyses offer two general insights. First, Isle Royale, Banff and Yellowstone are similar insomuch as they all include wolves preying on large ungulates. However, they also differ in species diversity of predator and prey communities, exploitation by humans and the role of dispersal. Even with the benefit of our analysis, it remains difficult to judge whether to be more impressed by the similarities or differences. This difficulty nicely illustrates a fundamental property of ecological

  16. Improving accuracy and capabilities of X-ray fluorescence method using intensity ratios

    Energy Technology Data Exchange (ETDEWEB)

    Garmay, Andrey V., E-mail: andrew-garmay@yandex.ru; Oskolok, Kirill V.

    2017-04-15

    An X-ray fluorescence analysis algorithm is proposed which is based on a use of ratios of X-ray fluorescence lines intensities. Such an analytical signal is more stable and leads to improved accuracy. Novel calibration equations are proposed which are suitable for analysis in a broad range of matrix compositions. To apply the algorithm to analysis of samples containing significant amount of undetectable elements a use of a dependence of a Rayleigh-to-Compton intensity ratio on a total content of these elements is suggested. The technique's validity is shown by analysis of standard steel samples, model metal oxides mixture and iron ore samples.

  17. Surface area-volume ratios in insects.

    Science.gov (United States)

    Kühsel, Sara; Brückner, Adrian; Schmelzle, Sebastian; Heethoff, Michael; Blüthgen, Nico

    2017-10-01

    Body mass, volume and surface area are important for many aspects of the physiology and performance of species. Whereas body mass scaling received a lot of attention in the literature, surface areas of animals have not been measured explicitly in this context. We quantified surface area-volume (SA/V) ratios for the first time using 3D surface models based on a structured light scanning method for 126 species of pollinating insects from 4 orders (Diptera, Hymenoptera, Lepidoptera, and Coleoptera). Water loss of 67 species was measured gravimetrically at very dry conditions for 2 h at 15 and 30 °C to demonstrate the applicability of the new 3D surface measurements and relevance for predicting the performance of insects. Quantified SA/V ratios significantly explained the variation in water loss across species, both directly or after accounting for isometric scaling (residuals of the SA/V ∼ mass 2/3 relationship). Small insects with a proportionally larger surface area had the highest water loss rates. Surface scans of insects to quantify allometric SA/V ratios thus provide a promising method to predict physiological responses, improving the potential of body mass isometry alone that assume geometric similarity. © 2016 Institute of Zoology, Chinese Academy of Sciences.

  18. Neurophysiology in preschool improves behavioral prediction of reading ability throughout primary school.

    Science.gov (United States)

    Maurer, Urs; Bucher, Kerstin; Brem, Silvia; Benz, Rosmarie; Kranz, Felicitas; Schulz, Enrico; van der Mark, Sanne; Steinhausen, Hans-Christoph; Brandeis, Daniel

    2009-08-15

    More struggling readers could profit from additional help at the beginning of reading acquisition if dyslexia prediction were more successful. Currently, prediction is based only on behavioral assessment of early phonological processing deficits associated with dyslexia, but it might be improved by adding brain-based measures. In a 5-year longitudinal study of children with (n = 21) and without (n = 23) familial risk for dyslexia, we tested whether neurophysiological measures of automatic phoneme and tone deviance processing obtained in kindergarten would improve prediction of reading over behavioral measures alone. Together, neurophysiological and behavioral measures obtained in kindergarten significantly predicted reading in school. Particularly the late mismatch negativity measure that indicated hemispheric lateralization of automatic phoneme processing improved prediction of reading ability over behavioral measures. It was also the only significant predictor for long-term reading success in fifth grade. Importantly, this result also held for the subgroup of children at familial risk. The results demonstrate that brain-based measures of processing deficits associated with dyslexia improve prediction of reading and thus may be further evaluated to complement clinical practice of dyslexia prediction, especially in targeted populations, such as children with a familial risk.

  19. Plaque Structural Stress Estimations Improve Prediction of Future Major Adverse Cardiovascular Events After Intracoronary Imaging.

    Science.gov (United States)

    Brown, Adam J; Teng, Zhongzhao; Calvert, Patrick A; Rajani, Nikil K; Hennessy, Orla; Nerlekar, Nitesh; Obaid, Daniel R; Costopoulos, Charis; Huang, Yuan; Hoole, Stephen P; Goddard, Martin; West, Nick E J; Gillard, Jonathan H; Bennett, Martin R

    2016-06-01

    Although plaque rupture is responsible for most myocardial infarctions, few high-risk plaques identified by intracoronary imaging actually result in future major adverse cardiovascular events (MACE). Nonimaging markers of individual plaque behavior are therefore required. Rupture occurs when plaque structural stress (PSS) exceeds material strength. We therefore assessed whether PSS could predict future MACE in high-risk nonculprit lesions identified on virtual-histology intravascular ultrasound. Baseline nonculprit lesion features associated with MACE during long-term follow-up (median: 1115 days) were determined in 170 patients undergoing 3-vessel virtual-histology intravascular ultrasound. MACE was associated with plaque burden ≥70% (hazard ratio: 8.6; 95% confidence interval, 2.5-30.6; P<0.001) and minimal luminal area ≤4 mm(2) (hazard ratio: 6.6; 95% confidence interval, 2.1-20.1; P=0.036), although absolute event rates for high-risk lesions remained <10%. PSS derived from virtual-histology intravascular ultrasound was subsequently estimated in nonculprit lesions responsible for MACE (n=22) versus matched control lesions (n=22). PSS showed marked heterogeneity across and between similar lesions but was significantly increased in MACE lesions at high-risk regions, including plaque burden ≥70% (13.9±11.5 versus 10.2±4.7; P<0.001) and thin-cap fibroatheroma (14.0±8.9 versus 11.6±4.5; P=0.02). Furthermore, PSS improved the ability of virtual-histology intravascular ultrasound to predict MACE in plaques with plaque burden ≥70% (adjusted log-rank, P=0.003) and minimal luminal area ≤4 mm(2) (P=0.002). Plaques responsible for MACE had larger superficial calcium inclusions, which acted to increase PSS (P<0.05). Baseline PSS is increased in plaques responsible for MACE and improves the ability of intracoronary imaging to predict events. Biomechanical modeling may complement plaque imaging for risk stratification of coronary nonculprit lesions. © 2016

  20. Intensity ratio to improve black hole assessment in multiple sclerosis.

    Science.gov (United States)

    Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H

    2018-01-01

    Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Machine Learning Principles Can Improve Hip Fracture Prediction

    DEFF Research Database (Denmark)

    Kruse, Christian; Eiken, Pia; Vestergaard, Peter

    2017-01-01

    Apply machine learning principles to predict hip fractures and estimate predictor importance in Dual-energy X-ray absorptiometry (DXA)-scanned men and women. Dual-energy X-ray absorptiometry data from two Danish regions between 1996 and 2006 were combined with national Danish patient data.......89 [0.82; 0.95], but with poor calibration in higher probabilities. A ten predictor subset (BMD, biochemical cholesterol and liver function tests, penicillin use and osteoarthritis diagnoses) achieved a test AUC of 0.86 [0.78; 0.94] using an “xgbTree” model. Machine learning can improve hip fracture...... prediction beyond logistic regression using ensemble models. Compiling data from international cohorts of longer follow-up and performing similar machine learning procedures has the potential to further improve discrimination and calibration....

  2. Combined use of serum MCP-1/IL-10 ratio and uterine artery Doppler index significantly improves the prediction of preeclampsia.

    Science.gov (United States)

    Cui, Shihong; Gao, Yanan; Zhang, Linlin; Wang, Yuan; Zhang, Lindong; Liu, Pingping; Liu, Ling; Chen, Juan

    2017-10-01

    Monocyte chemotactic protein-1 (MCP-1, or CCL2) is a member of the chemokine subfamily involved in recruitment of monocytes in inflammatory tissues. IL-10 is a key regulator for maintaining the balance of anti-inflammatory and pro-inflammatory milieu at the feto-maternal interface. Doppler examination has been routinely performed for the monitoring and management of preeclampsia patients. This study evaluates the efficiency of these factors alone, or in combination, for the predication of preeclampsia. The serum levels of MCP-1 and IL-10 in 78 preeclampsia patients and 143 age-matched normal controls were measured. The Doppler ultrasonography was performed and Artery Pulsatility Index (PI) and Resistance Index (RI) were calculated for the same subjects. It was found that while the second-trimester serum MCP-1, IL-10, MCP-1/IL-10 ratio, PI, and RI showed some power in predicting preeclampsia, the combination of MCP-1/IL-10 and PI and RI accomplishes the highest efficiency, achieving an AUC of 0.973 (95% CI, 0.000-1.000, Ppreeclampsia. Future studies using a larger sample can be conducted to construct an algorithm capable of quantitative assessment on the risk of preeclampsia. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Improving urban wind flow predictions through data assimilation

    Science.gov (United States)

    Sousa, Jorge; Gorle, Catherine

    2017-11-01

    Computational fluid dynamic is fundamentally important to several aspects in the design of sustainable and resilient urban environments. The prediction of the flow pattern for example can help to determine pedestrian wind comfort, air quality, optimal building ventilation strategies, and wind loading on buildings. However, the significant variability and uncertainty in the boundary conditions poses a challenge when interpreting results as a basis for design decisions. To improve our understanding of the uncertainties in the models and develop better predictive tools, we started a pilot field measurement campaign on Stanford University's campus combined with a detailed numerical prediction of the wind flow. The experimental data is being used to investigate the potential use of data assimilation and inverse techniques to better characterize the uncertainty in the results and improve the confidence in current wind flow predictions. We consider the incoming wind direction and magnitude as unknown parameters and perform a set of Reynolds-averaged Navier-Stokes simulations to build a polynomial chaos expansion response surface at each sensor location. We subsequently use an inverse ensemble Kalman filter to retrieve an estimate for the probabilistic density function of the inflow parameters. Once these distributions are obtained, the forward analysis is repeated to obtain predictions for the flow field in the entire urban canopy and the results are compared with the experimental data. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR.

  4. White matter NAA/Cho and Cho/Cr ratios at MR spectroscopy are predictive of motor outcome in preterm infants.

    Science.gov (United States)

    Kendall, Giles S; Melbourne, Andrew; Johnson, Samantha; Price, David; Bainbridge, Alan; Gunny, Roxanna; Huertas-Ceballos, Angela; Cady, Ernest B; Ourselin, Sebastian; Marlow, Neil; Robertson, Nicola J

    2014-04-01

    To determine (a) whether diffuse white matter injury of prematurity is associated with an increased choline (Cho)-to-creatine (Cr) ratio and a reduced N-acetylaspartate (NAA)-to-Cho ratio and whether these measures can be used as biomarkers of outcome and (b) if changes in peak area metabolite ratios at magnetic resonance (MR) spectroscopy are associated with changes in T2 and fractional anisotropy (FA) at MR imaging. The local ethics committee approved this study, and informed parental consent was obtained for each infant. At term-equivalent age, 43 infants born at less than 32 weeks gestation underwent conventional and quantitative diffusion-tensor and T2-weighted MR imaging. Single-voxel point-resolved proton (hydrogen 1) MR spectroscopy was performed from a 2-cm(3) voxel centered in the posterior periventricular white matter. Outcome was evaluated by using Bayley scales at a corrected age of 1 year. Associations were investigated with Pearson product moment or Spearman rank order correlation. Differences in ratios in infants with and infants without impairment were tested by using t tests. NAA/Cho and Cho/Cr ratios correlated with the scaled gross motor score and the composite motor score, independent of gestational age (P NAA/Cho ratio (P NAA/Cho ratio (P NAA/Cho ratio predicted impaired motor outcome at a corrected age of 1 year with a sensitivity of 0.80 (95% confidence interval [CI]: 0.57, 0.94) and a specificity of 0.80 (95% CI: 0.66, 0.88). The combination of Cho/Cr and NAA/Cho ratios measured in the posterior periventricular white matter at term-equivalent age is predictive of motor outcome at 1 year in infants born at less than 32 weeks gestation. RSNA, 2013

  5. Territory Quality and Plumage Morph Predict Offspring Sex Ratio Variation in a Raptor.

    Directory of Open Access Journals (Sweden)

    Nayden Chakarov

    Full Text Available Parents may adapt their offspring sex ratio in response to their own phenotype and environmental conditions. The most significant causes for adaptive sex-ratio variation might express themselves as different distributions of fitness components between sexes along a given variable. Several causes for differential sex allocation in raptors with reversed sexual size dimorphism have been suggested. We search for correlates of fledgling sex in an extensive dataset on common buzzards Buteo buteo, a long-lived bird of prey. Larger female offspring could be more resource-demanding and starvation-prone and thus the costly sex. Prominent factors such as brood size and laying date did not predict nestling sex. Nonetheless, lifetime sex ratio (LSR, potentially indicative of individual sex allocation constraints and overall nestling sex were explained by territory quality with more females being produced in better territories. Additionally, parental plumage morphs and the interaction of morph and prey abundance tended to explain LSR and nestling sex, indicating local adaptation of sex allocation However, in a limited census of nestling mortality, not females but males tended to die more frequently in prey-rich years. Also, although females could have potentially longer reproductive careers, a subset of our data encompassing full individual life histories showed that longevity and lifetime reproductive success were similarly distributed between the sexes. Thus, a basis for adaptive sex allocation in this population remains elusive. Overall, in common buzzards most major determinants of reproductive success appeared to have no effect on sex ratio but sex allocation may be adapted to local conditions in morph-specific patterns.

  6. Preoperative Aspartate Aminotransferase-to-Platelet Ratio Index Predicts Perioperative Liver-Related Complications Following Liver Resection for Colorectal Cancer Metastases

    DEFF Research Database (Denmark)

    Amptoulach, S.; Gross, G.; Sturesson, C.

    2017-01-01

    -related). In multivariate regression analysis, the aspartate aminotransferase-to-platelet ratio index was independently associated with liver-related complications (odds ratio: 1.149, p = 0.003) and perioperative liver failure (odds ratio: 1.155, p = 0.012). The latter was also true in the subcohort of patients......Background and Aims: There are limited data on the potential role of preoperative non-invasive markers, specifically the aspartate-to-alanine aminotransferase ratio and the aspartate aminotransferase-to-platelet ratio index, in predicting perioperative liver-related complications after hepatectomy...... collected from medical records. The nontumorous liver parenchyma in the surgical specimens of 31 patients was re-evaluated. Results: Overall, 215 patients were included. In total, 40% underwent neoadjuvant chemotherapy and 47% major resection, while 47% had perioperative complications (6% liver...

  7. Quantitative structure activity relationships (QSAR) for binary mixtures at non-equitoxic ratios based on toxic ratios-effects curves.

    Science.gov (United States)

    Tian, Dayong; Lin, Zhifen; Yin, Daqiang

    2013-01-01

    The present study proposed a QSAR model to predict joint effects at non-equitoxic ratios for binary mixtures containing reactive toxicants, cyanogenic compounds and aldehydes. Toxicity of single and binary mixtures was measured by quantifying the decrease in light emission from the Photobacterium phosphoreum for 15 min. The joint effects of binary mixtures (TU sum) can thus be obtained. The results showed that the relationships between toxic ratios of the individual chemicals and their joint effects can be described by normal distribution function. Based on normal distribution equations, the joint effects of binary mixtures at non-equitoxic ratios ( [Formula: see text]) can be predicted quantitatively using the joint effects at equitoxic ratios ( [Formula: see text]). Combined with a QSAR model of [Formula: see text]in our previous work, a novel QSAR model can be proposed to predict the joint effects of mixtures at non-equitoxic ratios ( [Formula: see text]). The proposed model has been validated using additional mixtures other than the one used for the development of the model. Predicted and observed results were similar (p>0.05). This study provides an approach to the prediction of joint effects for binary mixtures at non-equitoxic ratios.

  8. Restraint status improves the predictive value of motor vehicle crash criteria for pediatric trauma team activation.

    Science.gov (United States)

    Bozeman, Andrew P; Dassinger, Melvin S; Recicar, John F; Smith, Samuel D; Rettiganti, Mallikarjuna R; Nick, Todd G; Maxson, Robert T

    2012-12-01

    Most trauma centers incorporate mechanistic criteria (MC) into their algorithm for trauma team activation (TTA). We hypothesized that characteristics of the crash are less reliable than restraint status in predicting significant injury and the need for TTA. We identified 271 patients (age, <15 y) admitted with a diagnosis of motor vehicle crash. Mechanistic criteria and restraint status of each patient were recorded. Both MC and MC plus restraint status were evaluated as separate measures for appropriately predicting TTA based on treatment outcomes and injury scores. Improper restraint alone predicted a need for TTA with an odds ratios of 2.69 (P = .002). MC plus improper restraint predicted the need for TTA with an odds ratio of 2.52 (P = .002). In contrast, the odds ratio when using MC alone was 1.65 (P = .16). When the 5 MC were evaluated individually as predictive of TTA, ejection, death of occupant, and intrusion more than 18 inches were statistically significant. Improper restraint is an independent predictor of necessitating TTA in this single-institution study. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia.

    Science.gov (United States)

    Yang, Qinglin; Su, Yingying; Hussain, Mohammed; Chen, Weibi; Ye, Hong; Gao, Daiquan; Tian, Fei

    2014-05-01

    Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10-20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97.1%), specificity (73.3%), positive predictive value (82.5%), and negative prediction value (95.0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0.8, P coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.

  10. Hypoxic Prostate/Muscle PO2 Ratio Predicts for Outcome in Patients With Localized Prostate Cancer: Long-Term Results

    International Nuclear Information System (INIS)

    Turaka, Aruna; Buyyounouski, Mark K.; Hanlon, Alexandra L.; Horwitz, Eric M.; Greenberg, Richard E.; Movsas, Benjamin

    2012-01-01

    Purpose: To correlate tumor oxygenation status with long-term biochemical outcome after prostate brachytherapy. Methods and Materials: Custom-made Eppendorf PO 2 microelectrodes were used to obtain PO 2 measurements from the prostate (P), focused on positive biopsy locations, and normal muscle tissue (M), as a control. A total of 11,516 measurements were obtained in 57 men with localized prostate cancer immediately before prostate brachytherapy was given. The Eppendorf histograms provided the median PO 2 , mean PO 2 , and % 2 ratio on BF. Results: With a median follow-up time of 8 years, 12 men had ASTRO BF and 8 had Phoenix BF. On multivariate analysis, P/M PO 2 ratio 2 ratio 2 ratio) significantly predicts for poor long-term biochemical outcome, suggesting that novel hypoxic strategies should be investigated.

  11. Ratio of Systolic Blood Pressure to Right Atrial Pressure, a Novel Marker to Predict Morbidity and Mortality in Acute Systolic Heart Failure.

    Science.gov (United States)

    Omar, Hesham R; Charnigo, Richard; Guglin, Maya

    2017-04-01

    Congestion is the main contributor to heart failure (HF) morbidity and mortality. We assessed the combined role of congestion and decreased forward flow in predicting morbidity and mortality in acute systolic HF. The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness trial data set was used to determine if the ratio of simultaneously measured systolic blood pressure (SBP)/right atrial pressure (RAP) on admission predicted HF rehospitalization and 6-month mortality. One hundred ninety-five patients (mean age 56.5 years, 75% men) who received pulmonary artery catheterization were studied. The RAP, SBP, and SBP/RAP had an area under the curve (AUC) of 0.593 (p = 0.0205), 0.585 (p = 0.0359), and 0.621 (p = 0.0026), respectively, in predicting HF rehospitalization. The SBP/RAP was a superior marker of HF rehospitalization compared with RAP alone (difference in AUC 0.0289, p = 0.0385). The optimal criterion of SBP/RAP AUC 0.622, p = 0.0108, and a cut-off value of SBP/RAP <8 had a sensitivity of 61.9% and specificity 64.1% in predicting mortality. Multivariate analysis showed that an SBP/RAP <11 independently predicted rehospitalization for HF (estimated odds ratio 3.318, 95% confidence interval 1.692 to 6.506, p = 0.0005) and an SBP/RAP <8 independently predicted mortality (estimated hazard ratio 2.025, 95% confidence interval 1.069 to 3.833, p = 0.030). In conclusion, SBP/RAP ratio is a marker that identifies a spectrum of complications after hospitalization of patients with decompensated systolic HF, starting with increased incidence of HF rehospitalization at SBP/RAP <11 to increased mortality with SBP/RAP <8. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. A low plasma 1,25(OH)2 vitamin D/PTH (1-84) ratio predicts worsening of renal function in patients with chronic heart failure.

    Science.gov (United States)

    Masson, Serge; Barlera, Simona; Colotta, Francesco; Magnoli, Michela; Bonelli, Fabrizio; Moro, Milena; Marchioli, Roberto; Tavazzi, Luigi; Tognoni, Gianni; Latini, Roberto

    2016-12-01

    Dysregulation of the vitamin D system promotes renal dysfunction and has direct detrimental effects on the heart. Progressive deterioration of renal function is common in patients with chronic heart failure (HF) and is invariably associated with unfavorable outcomes which can be improved by early identification and timely interventions. We examined the relation between two plasma markers of vitamin D metabolism and worsening of renal function (WRF) in a large cohort of patients with chronic HF. Plasma levels of 1,25-dihydroxyvitamin D (1,25(OH) 2 D) and parathyroid hormone PTH (1-84) were measured in 1237 patients with clinical evidence of chronic and stable HF enrolled in the multicentre GISSI-HF trial and followed for 3.9years. We examined the relation of 1,25(OH) 2 D, PTH(1-84), and their ratio with WRF, defined as first increase in serum creatinine concentration ≥0.3mg/dL and ≥25% at two consecutive measurements at any time during the study. Lower 1,25(OH) 2 D/PTH(1-84) ratio was associated with a higher baseline serum concentration of creatinine, winter season, female sex and older age; 335 patients (29.6%) experienced an episode of WRF. After adjustment, a lower 1,25(OH) 2 D/PTH(1-84) ratio remained significantly associated with a higher risk of WRF (HR=0.75 [0.62-0.90], p=0.002) and correctly reclassified events. This ratio also independently predicted mortality and admission to hospital for cardiovascular reasons. The plasma 1,25(OH) 2 D/PTH(1-84) ratio is a promising indicator of future risk of deterioration of renal function in patients with chronic HF and mild renal impairment, that may serve to optimize therapies and improve outcomes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Neutrophil to lymphocyte with monocyte to lymphocyte ratio and white blood cell count in prediction of lung cancer

    Directory of Open Access Journals (Sweden)

    Thang Thanh Phan

    2018-04-01

    Full Text Available Background Lung cancer is the most common cause of cancer deaths in both sexes, while it is very difficult for screenings and early detection. Aims This study aims to clarify the role of systematic inflammation markers, including white blood cell (WBC, neutrophil (NEU, monocyte (MONO, platelet (PLT, neutrophil to lymphocyte ratio (NLR, monocyte to lymphocyte ratio (MLR and platelet to lymphocyte ratio (PLR in prediction of lung cancer. Methods A case-control study was conducted on 1,315 primary lung cancer patients and 1,315 healthy adults with matched age and gender at Cho Ray hospital. NLR, MLR and PLR were calculated by using neutrophil, lymphocyte, monocyte and platelet count which were recalled from laboratory database. With 600 cases in the derivation set, the logistic regression with univariate analysis was used to identify the impacted marker, then developing the optimal prediction model for lung cancer by logistic regression with multivariate method. The diagnostic values of optimal model consisting of sensitivity (Sen, specificity (Spe, positive predictive value (PPV, negative predictive value (NPV and the area under the ROC curve (AUC value were extracted and verified on all data, in validation set. Results The median values of WBC, NEU, MONO, PLT, NLR, MLR and PLR in lung cancer were not significantly difference between histological subtypes and clinical stages (p > 0.05, but higher than the values in control group (p < 0.01. Multivariates analysis shows that NLR, MLR and WBC were three parameters that have the significant impact of the optimal prediction model (p < 0.01. The AUC value, sensitivity and specificity of the optimal model for lung cancer detection were 0.881, 73.5 per cent (95 per cent CI:70.3–76.6 and 87.7 per cent (95 per centCI:85.2–89.9, respectively. Whereas, the PPV and NPV values of prediction model were 85.7 per cent (95 per cent CI:82.8–88.2 and 76.8 (95 per centCI:73.9–79.5, respectively. Among three

  14. Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals.

    Directory of Open Access Journals (Sweden)

    Peng Ren

    Full Text Available Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD to obtain their Intrinsic Mode Functions (IMF. Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.

  15. Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

    Directory of Open Access Journals (Sweden)

    Sun Zhangzhen

    2012-08-01

    Full Text Available In this paper, an improved weighted least squares (WLS, together with autoregressive (AR model, is proposed to improve prediction accuracy of earth rotation parameters(ERP. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.

  16. Branching-ratio predictions for the iota(1440)

    International Nuclear Information System (INIS)

    Palmer, W.F.; Pinsky, S.S.

    1983-01-01

    A simple pole model is used to predict iota→deltaπ, rho#betta#, #betta##betta#, phi#betta#, rhoππ, and etaππ. The rates iota→etaππ and iota→KK-barπ are examined in detail. In the pole model the rate iota→etaππ is compared to eta'→etaππ and we have the prediction B(iota→etaππ)/B(iota→KK-barπ) = 10%. A direct calculation that takes into account the cancellation between iota→deltaπ→(etaπ)π and iota→etaepsilon→eta(ππ), the KK-bar threshold, and SU(3) violations seen in the decay of the delta, predicts 20%< or =B(iota→etaππ)/B(iota→KK-barπ),< or =110%. Both calculations are consistent with the experimental limit of 50%

  17. Hepatocellular carcinoma: IVIM diffusion quantification for prediction of tumor necrosis compared to enhancement ratios

    International Nuclear Information System (INIS)

    Kakite, Suguru; Dyvorne, Hadrien A.; Lee, Karen M.; Jajamovich, Guido H.; Knight-Greenfield, Ashley; Taouli, Bachir

    2015-01-01

    To correlate intra voxel incoherent motion (IVIM) diffusion parameters of liver parenchyma and hepatocellular carcinoma (HCC) with degree of liver/tumor enhancement and necrosis; and to assess the diagnostic performance of diffusion parameters vs. enhancement ratios (ER) for prediction of complete tumor necrosis. In this IRB approved HIPAA compliant study, we included 46 patients with HCC who underwent IVIM diffusion-weighted (DW) MRI in addition to routine sequences at 3.0 T. True diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (PF) and apparent diffusion coefficient (ADC) were quantified in tumors and liver parenchyma. Tumor ER were calculated using contrast-enhanced imaging, and degree of tumor necrosis was assessed using post-contrast image subtraction. IVIM parameters and ER were compared between HCC and background liver and between necrotic and viable tumor components. ROC analysis for prediction of complete tumor necrosis was performed. 79 HCCs were assessed (mean size 2.5 cm). D, PF and ADC were significantly higher in HCC vs. liver (p < 0.0001). There were weak significant negative/positive correlations between D/PF and ER, and significant correlations between D/PF/ADC and tumor necrosis (for D, r 0.452, p < 0.001). Among diffusion parameters, D had the highest area under the curve (AUC 0.811) for predicting complete tumor necrosis. ER outperformed diffusion parameters for prediction of complete tumor necrosis (AUC > 0.95, p < 0.002). D has a reasonable diagnostic performance for predicting complete tumor necrosis, however lower than that of contrast-enhanced imaging

  18. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  19. Theoretical study on new bias factor methods to effectively use critical experiments for improvement of prediction accuracy of neutronic characteristics

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Mori, Takamasa; Takeda, Toshikazu

    2007-01-01

    Extended bias factor methods are proposed with two new concepts, the LC method and the PE method, in order to effectively use critical experiments and to enhance the applicability of the bias factor method for the improvement of the prediction accuracy of neutronic characteristics of a target core. Both methods utilize a number of critical experimental results and produce a semifictitious experimental value with them. The LC and PE methods define the semifictitious experimental values by a linear combination of experimental values and the product of exponentiated experimental values, respectively, and the corresponding semifictitious calculation values by those of calculation values. A bias factor is defined by the ratio of the semifictitious experimental value to the semifictitious calculation value in both methods. We formulate how to determine weights for the LC method and exponents for the PE method in order to minimize the variance of the design prediction value obtained by multiplying the design calculation value by the bias factor. From a theoretical comparison of these new methods with the conventional method which utilizes a single experimental result and the generalized bias factor method which was previously proposed to utilize a number of experimental results, it is concluded that the PE method is the most useful method for improving the prediction accuracy. The main advantages of the PE method are summarized as follows. The prediction accuracy is necessarily improved compared with the design calculation value even when experimental results include large experimental errors. This is a special feature that the other methods do not have. The prediction accuracy is most effectively improved by utilizing all the experimental results. From these facts, it can be said that the PE method effectively utilizes all the experimental results and has a possibility to make a full-scale-mockup experiment unnecessary with the use of existing and future benchmark

  20. Can survival prediction be improved by merging gene expression data sets?

    Directory of Open Access Journals (Sweden)

    Haleh Yasrebi

    Full Text Available BACKGROUND: High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS: Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS: Merging did not deteriorate performance on average despite (a The diversity of microarray platforms used. (b The heterogeneity of patients cohorts. (c The heterogeneity of breast cancer disease. (d Substantial variation of time to death or relapse. (e The reduced number of genes in the merged data

  1. PCA-derived factors that may be predictive of postoperative pain in pediatric patients: a possible role for the PCA ratio.

    Science.gov (United States)

    McDonnell, Conor; Pehora, Carolyne; Crawford, Mark W

    2012-01-01

    No method exists to reliably predict which patients will develop severe postoperative pain. The authors hypothesized that data derived from patient-controlled analgesia (PCA) pumps (specifically the ratio of patient demands to pump deliveries) may predict which patients would develop severe pain after scoliosis repair. Quaternary, university-affiliated, pediatric hospital. Forty American Society of Anesthesiologists I-Il pediatric patients who had undergone elective scoliosis repair and had consented to recruitment to a randomized clinical trial investigating the effects of early morphine administration on remifentanil-induced hyperalgesia. To test the hypothesis of the current study, the authors calculated the PCA ratio of demand to delivery at every 4 hours throughout the first 24 hours after surgery for all the patients recruited to the original study. The authors compared calculated PCA ratios, numeric rating scale pain scores, and cumulative morphine consumption for those patients who developed severe postoperative pain and met the criteria for opioid rotation versus those patients who did not. Seven patients required opioid rotation from PCA morphine to PCA hydromorphone. Eight hours after surgery, the median PCA ratio for those seven patients (2.5[range, 1.8-4.3]) was significantly greater than that for all other recruited patients (1.3 [range, 0-2.7]; p PCA ratios of demand to delivery as early as 8 hours after surgery.

  2. NOAA's Strategy to Improve Operational Weather Prediction Outlooks at Subseasonal Time Range

    Science.gov (United States)

    Schneider, T.; Toepfer, F.; Stajner, I.; DeWitt, D.

    2017-12-01

    NOAA is planning to extend operational global numerical weather prediction to sub-seasonal time range under the auspices of its Next Generation Global Prediction System (NGGPS) and Extended Range Outlook Programs. A unification of numerical prediction capabilities for weather and subseasonal to seasonal (S2S) timescales is underway at NOAA using the Finite Volume Cubed Sphere (FV3) dynamical core as the basis for the emerging unified system. This presentation will overview NOAA's strategic planning and current activities to improve prediction at S2S time-scales that are ongoing in response to the Weather Research and Forecasting Innovation Act of 2017, Section 201. Over the short-term, NOAA seeks to improve the operational capability through improvements to its ensemble forecast system to extend its range to 30 days using the new FV3 Global Forecast System model, and by using this system to provide reforecast and re-analyses. In parallel, work is ongoing to improve NOAA's operational product suite for 30 day outlooks for temperature, precipitation and extreme weather phenomena.

  3. Branching-ratio predictions for the iota (1440)

    International Nuclear Information System (INIS)

    Palmer, W.F.; Pinsky, S.S.

    1982-01-01

    A simple pole model is used to predict iota → delta π, rho ν, νν, phi ν, rho ππ, and eta ππ. The rates iota → eta ππ and iota → K anti Kπ are examined in detail. In the pole model the rate iota → eta ππ is compared to eta' → eta ππ and we have the prediction B(iota → eta ππ)/B(iota → K anti Kπ) = 10%. A direct calculation that takes into account the cancellation between iota → delta π → (eta π)π and iota → eta epsilon → eta(ππ), the K anti K threshold and SU(3) violations seen in the decay of the delta, predicts 20% less than or equal to B(iota → eta ππ)/B(iota → K anti Kπ less than or equal to 110%. Both calculations are consistent with the experimental limit of 50%

  4. Neutrophil Lymphocyte Ratio Predicts Postoperative Pain after ...

    African Journals Online (AJOL)

    2018-02-07

    Feb 7, 2018 ... between preoperatively measured neutrophil-lymphocyte ratio (NLR) – as an inflammation ... analgesic (tenoxicam – as the first drug of choice, paracetamol, tramadol, or pethidine) usage ... fracture fixation). Age, sex, type of ...

  5. A comparison of between hyomental distance ratios, ratio of height to thyromental, modified Mallamapati classification test and upper lip bite test in predicting difficult laryngoscopy of patients undergoing general anesthesia

    Directory of Open Access Journals (Sweden)

    Azim Honarmand

    2014-01-01

    Full Text Available Background: Failed intubation is imperative source of anesthetic interrelated patient′s mortality. The aim of this present study was to compare the ability to predict difficult visualization of the larynx from the following pre-operative airway predictive indices, in isolation and combination: Modified Mallampati test (MMT, the ratio of height to thyromental distance (RHTMD, hyomental distance ratios (HMDR, and the upper-lip-bite test (ULBT. Materials and Methods: We collected data on 525 consecutive patients scheduled for elective surgery under general anesthesia requiring endotracheal intubation and then evaluated all four factors before surgery. A skilled anesthesiologist, not imparted of the noted pre-operative airway assessment, did the laryngoscopy and rating (as per Cormack and Lehane′s classification. Sensitivity, specificity, and positive predictive value for every airway predictor in isolation and in combination were established. Results: The most sensitive of the single tests was ULBT with a sensitivity of 90.2%. The hyomental distance extreme of head extension was the least sensitive of the single tests with a sensitivity of 56.9. The HMDR had sensitivity 86.3%. The ULBT had the highest negative predictive value: And the area under a receiver-operating characteristic curve (AUC of ROC curve among single predictors. The AUC of ROC curve for ULBT, HMDR and RHTMD was significantly more than for MMT (P 0.05. Conclusion: The HMDR is comparable with RHTMD and ULBT for prediction of difficult laryngoscopy in the general population, but was significantly more than for MMT.

  6. The Prediction of the Gas Utilization Ratio based on TS Fuzzy Neural Network and Particle Swarm Optimization.

    Science.gov (United States)

    Zhang, Sen; Jiang, Haihe; Yin, Yixin; Xiao, Wendong; Zhao, Baoyong

    2018-02-20

    Gas utilization ratio (GUR) is an important indicator that is used to evaluate the energy consumption of blast furnaces (BFs). Currently, the existing methods cannot predict the GUR accurately. In this paper, we present a novel data-driven model for predicting the GUR. The proposed approach utilized both the TS fuzzy neural network (TS-FNN) and the particle swarm algorithm (PSO) to predict the GUR. The particle swarm algorithm (PSO) is applied to optimize the parameters of the TS-FNN in order to decrease the error caused by the inaccurate initial parameter. This paper also applied the box graph (Box-plot) method to eliminate the abnormal value of the raw data during the data preprocessing. This method can deal with the data which does not obey the normal distribution which is caused by the complex industrial environments. The prediction results demonstrate that the optimization model based on PSO and the TS-FNN approach achieves higher prediction accuracy compared with the TS-FNN model and SVM model and the proposed approach can accurately predict the GUR of the blast furnace, providing an effective way for the on-line blast furnace distribution control.

  7. Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction.

    Science.gov (United States)

    Chen, Chia-Yen; Han, Jiali; Hunter, David J; Kraft, Peter; Price, Alkes L

    2015-09-01

    Polygenic prediction using genome-wide SNPs can provide high prediction accuracy for complex traits. Here, we investigate the question of how to account for genetic ancestry when conducting polygenic prediction. We show that the accuracy of polygenic prediction in structured populations may be partly due to genetic ancestry. However, we hypothesized that explicitly modeling ancestry could improve polygenic prediction accuracy. We analyzed three GWAS of hair color (HC), tanning ability (TA), and basal cell carcinoma (BCC) in European Americans (sample size from 7,440 to 9,822) and considered two widely used polygenic prediction approaches: polygenic risk scores (PRSs) and best linear unbiased prediction (BLUP). We compared polygenic prediction without correction for ancestry to polygenic prediction with ancestry as a separate component in the model. In 10-fold cross-validation using the PRS approach, the R(2) for HC increased by 66% (0.0456-0.0755; P ancestry, which prevents ancestry effects from entering into each SNP effect and being overweighted. Surprisingly, explicitly modeling ancestry produces a similar improvement when using the BLUP approach, which fits all SNPs simultaneously in a single variance component and causes ancestry to be underweighted. We validate our findings via simulations, which show that the differences in prediction accuracy will increase in magnitude as sample sizes increase. In summary, our results show that explicitly modeling ancestry can be important in both PRS and BLUP prediction. © 2015 WILEY PERIODICALS, INC.

  8. An improved method for predicting the evolution of the characteristic parameters of an information system

    Science.gov (United States)

    Dushkin, A. V.; Kasatkina, T. I.; Novoseltsev, V. I.; Ivanov, S. V.

    2018-03-01

    The article proposes a forecasting method that allows, based on the given values of entropy and error level of the first and second kind, to determine the allowable time for forecasting the development of the characteristic parameters of a complex information system. The main feature of the method under consideration is the determination of changes in the characteristic parameters of the development of the information system in the form of the magnitude of the increment in the ratios of its entropy. When a predetermined value of the prediction error ratio is reached, that is, the entropy of the system, the characteristic parameters of the system and the depth of the prediction in time are estimated. The resulting values of the characteristics and will be optimal, since at that moment the system possessed the best ratio of entropy as a measure of the degree of organization and orderliness of the structure of the system. To construct a method for estimating the depth of prediction, it is expedient to use the maximum principle of the value of entropy.

  9. The Relevance of Employee-Related Ratios for Early Detection of Corporate Crises

    Directory of Open Access Journals (Sweden)

    Mario Situm

    2014-12-01

    Full Text Available The purpose of this study was to analyse whether employee-related ratios derived from accounts have incremental predictive power for the early detection of corporate crises and bankruptcies. Based on the literature reviewed, it can be seen that not much attention has been drawn to this task, indicating that further research is justified. For empirical research purposes, a database of Austrian companies was used for the time period 2003 to 2005 in order to develop multivariate linear discriminant functions for the classification of companies into the two states; bankrupt and non-bankrupt, and to detect the contribution of employee-related ratios in explaining why firms fail. Several ratios from prior research were used as potential predictors. In addition, other separate ratios were analysed, including employee-related figures. The results of the study show that while employee-related ratios cannot contribute to an improvement in the classification performance of prediction models, signs of these ratios within the discriminant functions did show the expected directions. Efficient usage of employees seems to play an important role in decreasing the probability of insolvency. Additionally, two employee-related ratios were found which can be used as proxies for the size of the firm. This had not been identified in prior studies for this factor.

  10. CNNcon: improved protein contact maps prediction using cascaded neural networks.

    Directory of Open Access Journals (Sweden)

    Wang Ding

    Full Text Available BACKGROUNDS: Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly. METHODS: CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction. RESULTS: The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective

  11. [Value of the albumin to globulin ratio in predicting severity and prognosis in myasthenia gravis patients].

    Science.gov (United States)

    Yang, D H; Su, Z Q; Chen, Y; Chen, Z B; Ding, Z N; Weng, Y Y; Li, J; Li, X; Tong, Q L; Han, Y X; Zhang, X

    2016-03-08

    To assess the predictive value of the albumin to globulin ratio (AGR) in evaluation of disease severity and prognosis in myasthenia gravis patients. A total of 135 myasthenia gravis (MG) patients were enrolled between February 2009 and March 2015. The AGR was detected on the first day of hospitalization and ranked from lowest to highest, and the patients were divided into three equal tertiles according to the AGR values, which were T1 (AGR 1.53). The Kaplan-Meier curve was used to evaluate the prognostic value of AGR. Cox model analysis was used to evaluate the relevant factors. Multivariate Logistic regression analysis was used to find the predictors of myasthenia crisis during hospitalization. The median length of hospital stay for each tertile was: for the T1 21 days (15-35.5), T2 18 days (14-27.5), and T3 16 days (12-22.5) (Pmyasthenia gravis. At the multivariate Cox regression analysis, the AGR (Pmyasthenia gravis patients. Respectively, the hazard ratio (HR) were 4.655 (95% CI: 2.355-9.202) and 0.596 (95% CI: 0.492-0.723). Multivariate Logistic regression analysis showed the AGR (Pmyasthenia crisis. The AGR may represent a simple, potentially useful predictive biomarker for evaluating the disease severity and prognosis of patients with myasthenia gravis.

  12. Aerosol characteristics inversion based on the improved lidar ratio profile with the ground-based rotational Raman-Mie lidar

    Science.gov (United States)

    Ji, Hongzhu; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan

    2018-06-01

    An iterative method, based on a derived inverse relationship between atmospheric backscatter coefficient and aerosol lidar ratio, is proposed to invert the lidar ratio profile and aerosol extinction coefficient. The feasibility of this method is investigated theoretically and experimentally. Simulation results show the inversion accuracy of aerosol optical properties for iterative method can be improved in the near-surface aerosol layer and the optical thick layer. Experimentally, as a result of the reduced insufficiency error and incoherence error, the aerosol optical properties with higher accuracy can be obtained in the near-surface region and the region of numerical derivative distortion. In addition, the particle component can be distinguished roughly based on this improved lidar ratio profile.

  13. Improving Flash Flood Prediction in Multiple Environments

    Science.gov (United States)

    Broxton, P. D.; Troch, P. A.; Schaffner, M.; Unkrich, C.; Goodrich, D.; Wagener, T.; Yatheendradas, S.

    2009-12-01

    Flash flooding is a major concern in many fast responding headwater catchments . There are many efforts to model and to predict these flood events, though it is not currently possible to adequately predict the nature of flash flood events with a single model, and furthermore, many of these efforts do not even consider snow, which can, by itself, or in combination with rainfall events, cause destructive floods. The current research is aimed at broadening the applicability of flash flood modeling. Specifically, we will take a state of the art flash flood model that is designed to work with warm season precipitation in arid environments, the KINematic runoff and EROSion model (KINEROS2), and combine it with a continuous subsurface flow model and an energy balance snow model. This should improve its predictive capacity in humid environments where lateral subsurface flow significantly contributes to streamflow, and it will make possible the prediction of flooding events that involve rain-on-snow or rapid snowmelt. By modeling changes in the hydrologic state of a catchment before a flood begins, we can also better understand the factors or combination of factors that are necessary to produce large floods. Broadening the applicability of an already state of the art flash flood model, such as KINEROS2, is logical because flash floods can occur in all types of environments, and it may lead to better predictions, which are necessary to preserve life and property.

  14. Predictive Maintenance: One key to improved power plant availability

    International Nuclear Information System (INIS)

    Mobley; Allen, J.W.

    1986-01-01

    Recent developments in microprocessor technology has provided the ability to routinely monitor the actual mechanical condition of all rotating and reciprocating machinery and process variables (i.e. pressure, temperature, flow, etc.) of other process equipment within an operating electric power generating plant. This direct correlation between frequency domain vibration and actual mechanical condition of machinery and trending process variables of non-rotating equipment can provide the ''key'' to improving the availability and reliability, thermal efficiency and provide the baseline information necessary for developing a realistic plan for extending the useful life of power plants. The premise of utilizing microprocessor-based Predictive Maintenance to improve power plant operation has been proven by a number of utilities. This paper provides a comprehensive discussion of the TEC approach to Predictive Maintenance and examples of successful programs

  15. Digit ratio predicts sense of direction in women.

    Directory of Open Access Journals (Sweden)

    Xiaoqian J Chai

    Full Text Available The relative length of the second-to-fourth digits (2D:4D has been linked with prenatal androgen in humans. The 2D:4D is sexually dimorphic, with lower values in males than females, and appears to correlate with diverse measures of behavior. However, the relationship between digit ratio and cognition, and spatial cognition in particular, has produced mixed results. In the present study, we hypothesized that spatial tasks separating cue conditions that either favored female or male strategies would examine this structure-function correlation with greater precision. Previous work suggests that males are better in the use of directional cues than females. In the present study, participants learned a target location in a virtual landscape environment, in conditions that contained either all directional (i.e., distant or compass bearing cues, or all positional (i.e., local, small objects cues. After a short delay, participants navigated back to the target location from a novel starting location. Males had higher accuracy in initial search direction than females in environments with all directional cues. Lower digit ratio was correlated with higher accuracy of initial search direction in females in environments with all directional cues. Mental rotation scores did not correlate with digit ratio in either males or females. These results demonstrate for the first time that a sex difference in the use of directional cues, i.e., the sense of direction, is associated with more male-like digit ratio.

  16. Digit ratio predicts sense of direction in women.

    Science.gov (United States)

    Chai, Xiaoqian J; Jacobs, Lucia F

    2012-01-01

    The relative length of the second-to-fourth digits (2D:4D) has been linked with prenatal androgen in humans. The 2D:4D is sexually dimorphic, with lower values in males than females, and appears to correlate with diverse measures of behavior. However, the relationship between digit ratio and cognition, and spatial cognition in particular, has produced mixed results. In the present study, we hypothesized that spatial tasks separating cue conditions that either favored female or male strategies would examine this structure-function correlation with greater precision. Previous work suggests that males are better in the use of directional cues than females. In the present study, participants learned a target location in a virtual landscape environment, in conditions that contained either all directional (i.e., distant or compass bearing) cues, or all positional (i.e., local, small objects) cues. After a short delay, participants navigated back to the target location from a novel starting location. Males had higher accuracy in initial search direction than females in environments with all directional cues. Lower digit ratio was correlated with higher accuracy of initial search direction in females in environments with all directional cues. Mental rotation scores did not correlate with digit ratio in either males or females. These results demonstrate for the first time that a sex difference in the use of directional cues, i.e., the sense of direction, is associated with more male-like digit ratio.

  17. Mapping soil particle-size fractions: A comparison of compositional kriging and log-ratio kriging

    Science.gov (United States)

    Wang, Zong; Shi, Wenjiao

    2017-03-01

    Soil particle-size fractions (psf) as basic physical variables need to be accurately predicted for regional hydrological, ecological, geological, agricultural and environmental studies frequently. Some methods had been proposed to interpolate the spatial distributions of soil psf, but the performance of compositional kriging and different log-ratio kriging methods is still unclear. Four log-ratio transformations, including additive log-ratio (alr), centered log-ratio (clr), isometric log-ratio (ilr), and symmetry log-ratio (slr), combined with ordinary kriging (log-ratio kriging: alr_OK, clr_OK, ilr_OK and slr_OK) were selected to be compared with compositional kriging (CK) for the spatial prediction of soil psf in Tianlaochi of Heihe River Basin, China. Root mean squared error (RMSE), Aitchison's distance (AD), standardized residual sum of squares (STRESS) and right ratio of the predicted soil texture types (RR) were chosen to evaluate the accuracy for different interpolators. The results showed that CK had a better accuracy than the four log-ratio kriging methods. The RMSE (sand, 9.27%; silt, 7.67%; clay, 4.17%), AD (0.45), STRESS (0.60) of CK were the lowest and the RR (58.65%) was the highest in the five interpolators. The clr_OK achieved relatively better performance than the other log-ratio kriging methods. In addition, CK presented reasonable and smooth transition on mapping soil psf according to the environmental factors. The study gives insights for mapping soil psf accurately by comparing different methods for compositional data interpolation. Further researches of methods combined with ancillary variables are needed to be implemented to improve the interpolation performance.

  18. Neutrophil Lymphocyte Ratio Predicts Postoperative Pain after ...

    African Journals Online (AJOL)

    Background and Aim: Postoperative pain is well known and usually disturbing complication of surgery. Inflammation plays an important role in the development and progression of postoperative pain. We aimed to investigate possible relationship between preoperatively measured neutrophil‑lymphocyte ratio (NLR) – as an ...

  19. Benthic Light Availability Improves Predictions of Riverine Primary Production

    Science.gov (United States)

    Kirk, L.; Cohen, M. J.

    2017-12-01

    Light is a fundamental control on photosynthesis, and often the only control strongly correlated with gross primary production (GPP) in streams and rivers; yet it has received far less attention than nutrients. Because benthic light is difficult to measure in situ, surrogates such as open sky irradiance are often used. Several studies have now refined methods to quantify canopy and water column attenuation of open sky light in order to estimate the amount of light that actually reaches the benthos. Given the additional effort that measuring benthic light requires, we should ask if benthic light always improves our predictions of GPP compared to just open sky irradiance. We use long-term, high-resolution dissolved oxygen, turbidity, dissolved organic matter (fDOM), and irradiance data from streams and rivers in north-central Florida, US across gradients of size and color to build statistical models of benthic light that predict GPP. Preliminary results on a large, clear river show only modest model improvements over open sky irradiance, even in heavily canopied reaches with pulses of tannic water. However, in another spring-fed river with greater connectivity to adjacent wetlands - and hence larger, more frequent pulses of tannic water - the model improved dramatically with the inclusion of fDOM (model R2 improved from 0.28 to 0.68). River shade modeling efforts also suggest that knowing benthic light will greatly enhance our ability to predict GPP in narrower, forested streams flowing in particular directions. Our objective is to outline conditions where an assessment of benthic light conditions would be necessary for riverine metabolism studies or management strategies.

  20. Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios

    Science.gov (United States)

    Juarez, Alfredo; Harper, Susana Tapia

    2016-01-01

    The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.

  1. Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players.

    Science.gov (United States)

    Grygorowicz, Monika; Michałowska, Martyna; Walczak, Tomasz; Owen, Adam; Grabski, Jakub Krzysztof; Pyda, Andrzej; Piontek, Tomasz; Kotwicki, Tomasz

    2017-01-01

    To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively) the injury of hamstring muscles in professional soccer screened with knee isokinetic tests. Retrospective study. Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con) hamstring(H) and quadriceps(Q) absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658) to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar's chi2 test with Yates's correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for muscle injury detection. The use of 0.47 of Hcon/Qcon as a discriminate value resulted in significantly lower sensitivity when compared to 0.658 threshold (sensitivity of 16.7% vs

  2. Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

    Science.gov (United States)

    Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

    2018-04-01

    Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

  3. Prediction of cesium-134 and strontium-85 crop uptake based on soil properties

    International Nuclear Information System (INIS)

    Roca, M.C.; Vallejo, V.R.; Roig, M.; Tent, J.; Vidal, M.; Rauret, G.

    1997-01-01

    Nowadays, there is still the need to improve the quantification of parameters that affect radionuclide mobility. With this aim, radiocesium and radiostrontium soil-to-plant transfer was measured in lysimeters in a Calcic Luvisol, loamy soil and in a Fluvisol, loam-sandy soil, using lettuce [Lactuca sativa L. cv. Kinemontepas] and pea plants [Pisum sativum L. cv. Kelvedon Wonder]. Weighted Concentration Ratios (WCR), expressed as kg soil/kg plant, were calculated for different growth stages. Weighted Concentration Ratios were in general higher for 85Sr than for 134Cs, and also higher in the loam-sandy than in the loamy soil. To predict plant uptake, we evaluated a set of soil properties to define a prediction factor for the relative transfer in the two soils using cation exchange capacity (CEC) and radionuclide available fraction (fav) for radiostrontium, and soil solution composition, solid-liquid distribution coefficient, and radionuclide available fraction for radiocesium. The ratios of WCR in the loam-sandy and loamy soil were compared with the prediction factor. There was good agreement in lettuce for 85Sr (ratio of WCR was 5.4 for seedling and 3.9 for commercial samples, whereas prediction factor was 3.1) and for 134Cs (ratio of WCR was 5.1 for seedling and 5.5 for commercial samples, the prediction factor being 5.1), although for pea only the relative root uptake of radiocesium in seedling pea was well predicted (the ratio of WCR was 8.8, the prediction factor being 9.1). These soil parameters improved former predictions based solely on the fav, although factors depending on plant physiology should be better evaluated

  4. The Improved Estimation of Ratio of Two Population Proportions

    Science.gov (United States)

    Solanki, Ramkrishna S.; Singh, Housila P.

    2016-01-01

    In this article, first we obtained the correct mean square error expression of Gupta and Shabbir's linear weighted estimator of the ratio of two population proportions. Later we suggested the general class of ratio estimators of two population proportions. The usual ratio estimator, Wynn-type estimator, Singh, Singh, and Kaur difference-type…

  5. A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces

    Directory of Open Access Journals (Sweden)

    Yanjiao Li

    2017-08-01

    Full Text Available Gas utilization ratio (GUR is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs. In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF, depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.

  6. A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces.

    Science.gov (United States)

    Li, Yanjiao; Zhang, Sen; Yin, Yixin; Xiao, Wendong; Zhang, Jie

    2017-08-10

    Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF), depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS) to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.

  7. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

    Science.gov (United States)

    Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

    2010-07-01

    PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

  8. Improving Permafrost Hydrology Prediction Through Data-Model Integration

    Science.gov (United States)

    Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.

    2017-12-01

    The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.

  9. Neutrophil-to-lymphocyte ratio and mural nodule height as predictive factors for malignant intraductal papillary mucinous neoplasms.

    Science.gov (United States)

    Watanabe, Yusuke; Niina, Yusuke; Nishihara, Kazuyoshi; Okayama, Takafumi; Tamiya, Sadafumi; Nakano, Toru

    2018-01-15

    Accurate preoperative prediction for malignant IPMN is still challenging. The aim of this study was to investigate the validity of neutrophil-to-lymphocyte ratio (NLR) and mural nodule height (MNH) for predicting malignant intraductal papillary mucinous neoplasm (IPMN). The medical records of 60 patients who underwent pancreatectomy for IPMN were retrospectively reviewed. NLR tended to be higher in malignant IPMN (median: 2.23) than in benign IPMN (median: 2.04; p = .14). MNH was significantly greater in malignant IPMN (median: 16 mm) than in benign IPMN (median: 8 mm; p MNH were 3.60 and 11 mm, respectively. The sensitivity and specificity of NLR ≥3.60 for predicting malignant IPMN were 40% and 93%, and those of MNH ≥11 mm were 73% and 77%, respectively. Univariate analysis revealed that NLR ≥3.60 (p MNH ≥11 mm (p MNH ≥11 mm were not. NLR and MNH are suboptimal tests in predicting malignant IPMN; however, they can be useful to assist in clinical decision-making.

  10. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    Science.gov (United States)

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  11. Combining gene signatures improves prediction of breast cancer survival.

    Directory of Open Access Journals (Sweden)

    Xi Zhao

    Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves

  12. Can biomechanical variables predict improvement in crouch gait?

    Science.gov (United States)

    Hicks, Jennifer L.; Delp, Scott L.; Schwartz, Michael H.

    2011-01-01

    Many patients respond positively to treatments for crouch gait, yet surgical outcomes are inconsistent and unpredictable. In this study, we developed a multivariable regression model to determine if biomechanical variables and other subject characteristics measured during a physical exam and gait analysis can predict which subjects with crouch gait will demonstrate improved knee kinematics on a follow-up gait analysis. We formulated the model and tested its performance by retrospectively analyzing 353 limbs of subjects who walked with crouch gait. The regression model was able to predict which subjects would demonstrate ‘improved’ and ‘unimproved’ knee kinematics with over 70% accuracy, and was able to explain approximately 49% of the variance in subjects’ change in knee flexion between gait analyses. We found that improvement in stance phase knee flexion was positively associated with three variables that were drawn from knowledge about the biomechanical contributors to crouch gait: i) adequate hamstrings lengths and velocities, possibly achieved via hamstrings lengthening surgery, ii) normal tibial torsion, possibly achieved via tibial derotation osteotomy, and iii) sufficient muscle strength. PMID:21616666

  13. Evaluation of miR-182/miR-100 Ratio for Diagnosis and Survival Prediction in Bladder Cancer.

    Science.gov (United States)

    Chen, Zhanguo; Wu, Lili; Lin, Qi; Shi, Jing; Lin, Xiangyang; Shi, Liang

    2016-09-01

    Abnormal expression of microRNAs (miRNAs) plays an important role in development of several cancer types, including bladder cancer (BCa). However, the relationship between the ratio of miR-181/miR-100 and the prognosis of BCa has not been studied yet. The aim of this study was to evaluate the expression of miR-182, miR-100 and their clinical significance in BCa. Upregulation of miR-182 and down-regulation of miR-100 were validated in tissue specimens of 134 BCa cases compared with 148 normal bladder epithelia (NBE) specimens  using TaqMan-based real-time reverse transcription quantitative PCR (RT-qPCR). The diagnostic and prognostic evaluation of miR-182, miR-100, and miR-182/miR-100 ratio was also performed. miR-182 was upregulated in BCa and miR-100 was down-regulated in BCa compared with NBE (P ratio increased the diagnostic performance, yielding an AUC of 0.981 (97.01% sensitivity and 90.54% specificity). Moreover, miR-182/miR-100 ratio was associated with pT-stage, histological grade, BCa recurrence and carcinoma in situ (P analysis indicated that miR-182/miR-100 ratio was an independent prognostic factor for overall survival (Hazard ratio: 7.142; 95% CI: 2.106 - 9.891; P analysis revealed that high-level of miR-182/miR-100 ratio was significantly correlated with shortened survival time for BCa patients (P ratio may serve as a novel promising biomarker for diagnosis and survival prediction in BCa. Further studies are needed to elucidate the role of miR-182/miR-100 ratio as a non‑invasive diagnostic tool for BCa.

  14. Improving Saliency Models by Predicting Human Fixation Patches

    KAUST Repository

    Dubey, Rachit

    2015-04-16

    There is growing interest in studying the Human Visual System (HVS) to supplement and improve the performance of computer vision tasks. A major challenge for current visual saliency models is predicting saliency in cluttered scenes (i.e. high false positive rate). In this paper, we propose a fixation patch detector that predicts image patches that contain human fixations with high probability. Our proposed model detects sparse fixation patches with an accuracy of 84 % and eliminates non-fixation patches with an accuracy of 84 % demonstrating that low-level image features can indeed be used to short-list and identify human fixation patches. We then show how these detected fixation patches can be used as saliency priors for popular saliency models, thus, reducing false positives while maintaining true positives. Extensive experimental results show that our proposed approach allows state-of-the-art saliency methods to achieve better prediction performance on benchmark datasets.

  15. Improving Saliency Models by Predicting Human Fixation Patches

    KAUST Repository

    Dubey, Rachit; Dave, Akshat; Ghanem, Bernard

    2015-01-01

    There is growing interest in studying the Human Visual System (HVS) to supplement and improve the performance of computer vision tasks. A major challenge for current visual saliency models is predicting saliency in cluttered scenes (i.e. high false positive rate). In this paper, we propose a fixation patch detector that predicts image patches that contain human fixations with high probability. Our proposed model detects sparse fixation patches with an accuracy of 84 % and eliminates non-fixation patches with an accuracy of 84 % demonstrating that low-level image features can indeed be used to short-list and identify human fixation patches. We then show how these detected fixation patches can be used as saliency priors for popular saliency models, thus, reducing false positives while maintaining true positives. Extensive experimental results show that our proposed approach allows state-of-the-art saliency methods to achieve better prediction performance on benchmark datasets.

  16. Improved hybrid optimization algorithm for 3D protein structure prediction.

    Science.gov (United States)

    Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

    2014-07-01

    A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

  17. Predicting intrapartum fetal compromise using the fetal cerebro-umbilical ratio.

    Science.gov (United States)

    Sabdia, S; Greer, R M; Prior, T; Kumar, S

    2015-05-01

    The aim of this study was to explore the association between the cerebro-umbilical ratio measured at 35-37 weeks and intrapartum fetal compromise. This retrospective cross sectional study was conducted at the Mater Mothers' Hospital in Brisbane, Australia. Maternal demographics and fetal Doppler indices at 35-37 weeks gestation for 1381 women were correlated with intrapartum and neonatal outcomes. Babies born by caesarean section or instrumental delivery for fetal compromise had the lowest median cerebro-umbilical ratio 1.60 (IQR 1.22-2.08) compared to all other delivery groups (vaginal delivery, emergency delivery for failure to progress, emergency caesarean section for other reasons or elective caesarean section). The percentage of infants with a cerebro-umbilical ratio cerebro-umbilical ratio between the 10th-90th centile and 9.6% of infants with a cerebro-umbilical ratio > 90th centile required delivery for the same indication (p cerebro-umbilical ratio was associated with an increased risk of emergency delivery for fetal compromise, OR 2.03 (95% CI 1.41-2.92), p cerebro-umbilical ratio measured at 35-37 weeks is associated with a greater risk of intrapartum compromise. This is a relatively simple technique which could be used to risk stratify women in diverse healthcare settings. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Innovative predictive maintenance concepts to improve life cycle management

    NARCIS (Netherlands)

    Tinga, Tiedo

    2014-01-01

    For naval systems with typically long service lives, high sustainment costs and strict availability requirements, an effective and efficient life cycle management process is very important. In this paper four approaches are discussed to improve that process: physics of failure based predictive

  19. Two improvements on numerical simulation of 2-DOF vortex-induced vibration with low mass ratio

    Science.gov (United States)

    Kang, Zhuang; Ni, Wen-chi; Zhang, Xu; Sun, Li-ping

    2017-12-01

    Till now, there have been lots of researches on numerical simulation of vortex-induced vibration. Acceptable results have been obtained for fixed cylinders with low Reynolds number. However, for responses of 2-DOF vortex-induced vibration with low mass ratio, the accuracy is not satisfactory, especially for the maximum amplitudes. In Jauvtis and Williamson's work, the maximum amplitude of the cylinder with low mass ratio m*=2.6 can reach as large as 1.5 D to be called as the "super-upper branch", but from current literatures, few simulation results can achieve such value, even fail to capture the upper branch. Besides, it is found that the amplitude decays too fast in the lower branch with the RANS-based turbulence model. The reason is likely to be the defects of the turbulence model itself in the prediction of unsteady separated flows as well as the unreasonable setting of the numerical simulation parameters. Aiming at above issues, a modified turbulence model is proposed in this paper, and the effect of the acceleration of flow field on the response of vortex-induced vibration is studied based on OpenFOAM. By analyzing the responses of amplitude, phase and trajectory, frequency and vortex mode, it is proved that the vortex-induced vibration can be predicted accurately with the modified turbulence model under appropriate flow field acceleration.

  20. Solar radio proxies for improved satellite orbit prediction

    Science.gov (United States)

    Yaya, Philippe; Hecker, Louis; Dudok de Wit, Thierry; Fèvre, Clémence Le; Bruinsma, Sean

    2017-12-01

    Specification and forecasting of solar drivers to thermosphere density models is critical for satellite orbit prediction and debris avoidance. Satellite operators routinely forecast orbits up to 30 days into the future. This requires forecasts of the drivers to these orbit prediction models such as the solar Extreme-UV (EUV) flux and geomagnetic activity. Most density models use the 10.7 cm radio flux (F10.7 index) as a proxy for solar EUV. However, daily measurements at other centimetric wavelengths have also been performed by the Nobeyama Radio Observatory (Japan) since the 1950's, thereby offering prospects for improving orbit modeling. Here we present a pre-operational service at the Collecte Localisation Satellites company that collects these different observations in one single homogeneous dataset and provides a 30 days forecast on a daily basis. Interpolation and preprocessing algorithms were developed to fill in missing data and remove anomalous values. We compared various empirical time series prediction techniques and selected a multi-wavelength non-recursive analogue neural network. The prediction of the 30 cm flux, and to a lesser extent that of the 10.7 cm flux, performs better than NOAA's present prediction of the 10.7 cm flux, especially during periods of high solar activity. In addition, we find that the DTM-2013 density model (Drag Temperature Model) performs better with (past and predicted) values of the 30 cm radio flux than with the 10.7 flux.

  1. Solar radio proxies for improved satellite orbit prediction

    Directory of Open Access Journals (Sweden)

    Yaya Philippe

    2017-01-01

    Full Text Available Specification and forecasting of solar drivers to thermosphere density models is critical for satellite orbit prediction and debris avoidance. Satellite operators routinely forecast orbits up to 30 days into the future. This requires forecasts of the drivers to these orbit prediction models such as the solar Extreme-UV (EUV flux and geomagnetic activity. Most density models use the 10.7 cm radio flux (F10.7 index as a proxy for solar EUV. However, daily measurements at other centimetric wavelengths have also been performed by the Nobeyama Radio Observatory (Japan since the 1950's, thereby offering prospects for improving orbit modeling. Here we present a pre-operational service at the Collecte Localisation Satellites company that collects these different observations in one single homogeneous dataset and provides a 30 days forecast on a daily basis. Interpolation and preprocessing algorithms were developed to fill in missing data and remove anomalous values. We compared various empirical time series prediction techniques and selected a multi-wavelength non-recursive analogue neural network. The prediction of the 30 cm flux, and to a lesser extent that of the 10.7 cm flux, performs better than NOAA's present prediction of the 10.7 cm flux, especially during periods of high solar activity. In addition, we find that the DTM-2013 density model (Drag Temperature Model performs better with (past and predicted values of the 30 cm radio flux than with the 10.7 flux.

  2. A two-stage approach for improved prediction of residue contact maps

    Directory of Open Access Journals (Sweden)

    Pollastri Gianluca

    2006-03-01

    Full Text Available Abstract Background Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure. Although improvements have occurred over the last years, the problem of accurately predicting residue contact maps from primary sequences is still largely unsolved. Among the reasons for this are the unbalanced nature of the problem (with far fewer examples of contacts than non-contacts, the formidable challenge of capturing long-range interactions in the maps, the intrinsic difficulty of mapping one-dimensional input sequences into two-dimensional output maps. In order to alleviate these problems and achieve improved contact map predictions, in this paper we split the task into two stages: the prediction of a map's principal eigenvector (PE from the primary sequence; the reconstruction of the contact map from the PE and primary sequence. Predicting the PE from the primary sequence consists in mapping a vector into a vector. This task is less complex than mapping vectors directly into two-dimensional matrices since the size of the problem is drastically reduced and so is the scale length of interactions that need to be learned. Results We develop architectures composed of ensembles of two-layered bidirectional recurrent neural networks to classify the components of the PE in 2, 3 and 4 classes from protein primary sequence, predicted secondary structure, and hydrophobicity interaction scales. Our predictor, tested on a non redundant set of 2171 proteins, achieves classification performances of up to 72.6%, 16% above a base-line statistical predictor. We design a system for the prediction of contact maps from the predicted PE. Our results show that predicting maps through the PE yields sizeable gains especially for long-range contacts which are particularly critical for accurate protein 3D reconstruction. The final predictor's accuracy on a non-redundant set of 327 targets is 35

  3. Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Peng Lu

    2018-01-01

    Full Text Available Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively.

  4. Healthy, wealthy, and wise: retirement planning predicts employee health improvements.

    Science.gov (United States)

    Gubler, Timothy; Pierce, Lamar

    2014-09-01

    Are poor physical and financial health driven by the same underlying psychological factors? We found that the decision to contribute to a 401(k) retirement plan predicted whether an individual acted to correct poor physical-health indicators revealed during an employer-sponsored health examination. Using this examination as a quasi-exogenous shock to employees' personal-health knowledge, we examined which employees were more likely to improve their health, controlling for differences in initial health, demographics, job type, and income. We found that existing retirement-contribution patterns and future health improvements were highly correlated. Employees who saved for the future by contributing to a 401(k) showed improvements in their abnormal blood-test results and health behaviors approximately 27% more often than noncontributors did. These findings are consistent with an underlying individual time-discounting trait that is both difficult to change and domain interdependent, and that predicts long-term individual behaviors in multiple dimensions. © The Author(s) 2014.

  5. DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.

    Science.gov (United States)

    Adhikari, Badri; Hou, Jie; Cheng, Jianlin

    2018-05-01

    Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction. In this paper we discuss DNCON2, an improved protein contact map predictor based on two-level deep convolutional neural networks. It consists of six convolutional neural networks-the first five predict contacts at 6, 7.5, 8, 8.5 and 10 Å distance thresholds, and the last one uses these five predictions as additional features to predict final contact maps. On the free-modeling datasets in CASP10, 11 and 12 experiments, DNCON2 achieves mean precisions of 35, 50 and 53.4%, respectively, higher than 30.6% by MetaPSICOV on CASP10 dataset, 34% by MetaPSICOV on CASP11 dataset and 46.3% by Raptor-X on CASP12 dataset, when top L/5 long-range contacts are evaluated. We attribute the improved performance of DNCON2 to the inclusion of short- and medium-range contacts into training, two-level approach to prediction, use of the state-of-the-art optimization and activation functions, and a novel deep learning architecture that allows each filter in a convolutional layer to access all the input features of a protein of arbitrary length. The web server of DNCON2 is at http://sysbio.rnet.missouri.edu/dncon2/ where training and testing datasets as well as the predictions for CASP10, 11 and 12 free-modeling datasets can also be downloaded. Its source code is available at https://github.com/multicom-toolbox/DNCON2/. chengji@missouri.edu. Supplementary data are available at Bioinformatics online.

  6. Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The ...... process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.......A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data....... The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech...

  7. Predictions of Poisson's ratio in cross-ply laminates containing matrix cracks and delaminations

    Science.gov (United States)

    Harris, Charles E.; Allen, David H.; Nottorf, Eric W.

    1989-01-01

    A damage-dependent constitutive model for laminated composites has been developed for the combined damage modes of matrix cracks and delaminations. The model is based on the concept of continuum damage mechanics and uses second-order tensor valued internal state variables to represent each mode of damage. The internal state variables are defined as the local volume average of the relative crack face displacements. Since the local volume for delaminations is specified at the laminate level, the constitutive model takes the form of laminate analysis equations modified by the internal state variables. Model implementation is demonstrated for the laminate engineering modulus E(x) and Poisson's ratio nu(xy) of quasi-isotropic and cross-ply laminates. The model predictions are in close agreement to experimental results obtained for graphite/epoxy laminates.

  8. Improved prediction of signal peptides: SignalP 3.0

    DEFF Research Database (Denmark)

    Bendtsen, Jannick Dyrløv; Nielsen, Henrik; von Heijne, G.

    2004-01-01

    We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the ...

  9. Value of the regurgitant volume to end diastolic volume ratio to predict the regression of left ventricular dimensions after valve replacement in aortic insufficiency

    NARCIS (Netherlands)

    P.M. Fioretti (Paolo); C. Tirtaman; E. Bos (Egbert); P.W.J.C. Serruys (Patrick); J.R.T.C. Roelandt (Jos)

    1987-01-01

    textabstractThe aim of this study was to assess the value of regurgitant stroke volume (RSV) to end-diastolic volume (EDV) ratio to predict the regression of left ventricular (LV) dimensions after uncomplicated valve replacement in 34 patients with severe pure aortic insufficiency. The RSV/EDV ratio

  10. Improved core monitoring for improved plant operations

    International Nuclear Information System (INIS)

    Mueller, N.P.

    1987-01-01

    Westinghouse has recently installed a core on-line surveillance, monitoring and operations systems (COSMOS), which uses only currently available core and plant data to accurately reconstruct the core average axial and radial power distributions. This information is provided to the operator in an immediately usable, human-engineered format and is accumulated for use in application programs that provide improved core performance predictive tools and a data base for improved fuel management. Dynamic on-line real-time axial and radial core monitoring supports a variety of plant operations to provide a favorable cost/benefit ratio for such a system. Benefits include: (1) relaxation or elimination of certain technical specifications to reduce surveillance and reporting requirements and allow higher availability factors, (2) improved information displays, predictive tools, and control strategies to support more efficient core control and reduce effluent production, and (3) expanded burnup data base for improved fuel management. Such systems can be backfit into operating plants without changing the existing instrumentation and control system and can frequently be implemented on existing plant computer capacity

  11. Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics

    Science.gov (United States)

    Suzuki, Yasumasa; Tsujimura, Taku; Kusaka, Jin

    2014-08-01

    It is important to understand the mechanism of mixing and atomization of the diesel spray. In addition, the computational prediction of mixing behavior and internal structure of a diesel spray is expected to promote the further understanding about a diesel spray and development of the diesel engine including devices for fuel injection. In this study, we predicted the formation of diesel fuel spray with 3D-CFD code and validated the application by comparing experimental results of the fuel spray behavior and the equivalence ratio visualized by Layleigh-scatter imaging under some ambient, injection and fuel conditions. Using the applicable constants of KH-RT model, we can predict the liquid length spray on a quantitative level. under various fuel injection, ambient and fuel conditions. On the other hand, the change of the vapor penetration and the fuel mass fraction and equivalence ratio distribution with change of fuel injection and ambient conditions quantitatively. The 3D-CFD code used in this study predicts the spray cone angle and entrainment of ambient gas are predicted excessively, therefore there is the possibility of the improvement in the prediction accuracy by the refinement of fuel droplets breakup and evaporation model and the quantitative prediction of spray cone angle.

  12. Fatigue limit prediction of ferritic-pearlitic ductile cast iron considering stress ratio and notch size

    Science.gov (United States)

    Deguchi, T.; Kim, H. J.; Ikeda, T.

    2017-05-01

    The mechanical behavior of ductile cast iron is governed by graphite particles and casting defects in the microstructures, which can significantly decrease the fatigue strength. In our previous study, the fatigue limit of ferritic-pearlitic ductile cast iron specimens with small defects ((\\sqrt{{area}}=80˜ 1500{{μ }}{{m}})) could successfully be predicted based on the \\sqrt{{area}} parameter model by using \\sqrt{{area}} as a geometrical parameter of defect as well as the tensile strength as a material parameter. In addition, the fatigue limit for larger defects could be predicted based on the conventional fracture mechanics approach. In this study, rotating bending and tension-compression fatigue tests with ferritic-pearlitic ductile cast iron containing circumferential sharp notches as well as smooth specimens were performed to investigate quantitatively the effects of defect. The notch depths ranged 10 ˜ 2500 μm and the notch root radii were 5 and 50 μm. The stress ratios were R = -1 and 0.1. The microscopic observation of crack propagation near fatigue limit revealed that the fatigue limit was determined by the threshold condition for propagation of a small crack emanating from graphite particles. The fatigue limit could be successfully predicted as a function of R using a method proposed in this study.

  13. Assessing the Liquidity of Firms: Robust Neural Network Regression as an Alternative to the Current Ratio

    Science.gov (United States)

    de Andrés, Javier; Landajo, Manuel; Lorca, Pedro; Labra, Jose; Ordóñez, Patricia

    Artificial neural networks have proven to be useful tools for solving financial analysis problems such as financial distress prediction and audit risk assessment. In this paper we focus on the performance of robust (least absolute deviation-based) neural networks on measuring liquidity of firms. The problem of learning the bivariate relationship between the components (namely, current liabilities and current assets) of the so-called current ratio is analyzed, and the predictive performance of several modelling paradigms (namely, linear and log-linear regressions, classical ratios and neural networks) is compared. An empirical analysis is conducted on a representative data base from the Spanish economy. Results indicate that classical ratio models are largely inadequate as a realistic description of the studied relationship, especially when used for predictive purposes. In a number of cases, especially when the analyzed firms are microenterprises, the linear specification is improved by considering the flexible non-linear structures provided by neural networks.

  14. GUT Scale Fermion Mass Ratios

    International Nuclear Information System (INIS)

    Spinrath, Martin

    2014-01-01

    We present a series of recent works related to group theoretical factors from GUT symmetry breaking which lead to predictions for the ratios of quark and lepton Yukawa couplings at the unification scale. New predictions for the GUT scale ratios y μ /y s , y τ /y b and y t /y b in particular are shown and compared to experimental data. For this comparison it is important to include possibly large supersymmetric threshold corrections. Due to this reason the structure of the fermion masses at the GUT scale depends on TeV scale physics and makes GUT scale physics testable at the LHC. We also discuss how this new predictions might lead to predictions for mixing angles by discussing the example of the recently measured last missing leptonic mixing angle θ 13 making this new class of GUT models also testable in neutrino experiments

  15. Can decadal climate predictions be improved by ocean ensemble dispersion filtering?

    Science.gov (United States)

    Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

    2017-12-01

    Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http

  16. Improved method for SNR prediction in machine-learning-based test

    NARCIS (Netherlands)

    Sheng, Xiaoqin; Kerkhoff, Hans G.

    2010-01-01

    This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach,

  17. Sex allocation and secondary sex ratio in Cuban boa ( Chilabothrus angulifer): mother's body size affects the ratio between sons and daughters

    Science.gov (United States)

    Frynta, Daniel; Vejvodová, Tereza; Šimková, Olga

    2016-06-01

    Secondary sex ratios of animals with genetically determined sex may considerably deviate from equality. These deviations may be attributed to several proximate and ultimate factors. Sex ratio theory explains some of them as strategic decisions of mothers improving their fitness by selective investment in sons or daughters, e.g. local resource competition hypothesis (LRC) suggests that philopatric females tend to produce litters with male-biased sex ratios to avoid future competition with their daughters. Until now, only little attention has been paid to examine predictions of sex ratio theory in snakes possessing genetic sex determination and exhibiting large variance in allocation of maternal investment. Cuban boa is an endemic viviparous snake producing large-bodied newborns (˜200 g). Extremely high maternal investment in each offspring increases importance of sex allocation. In a captive colony, we collected breeding records of 42 mothers, 62 litters and 306 newborns and examined secondary sex ratios (SR) and sexual size dimorphism (SSD) of newborns. None of the examined morphometric traits of neonates appeared sexually dimorphic. The sex ratio was slightly male biased (174 males versus 132 females) and litter sex ratio significantly decreased with female snout-vent length. We interpret this relationship as an additional support for LRC as competition between mothers and daughters increases with similarity of body sizes between competing snakes.

  18. TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

    Science.gov (United States)

    Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

    2017-09-01

    α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD PHP, MySQL and Apache, with all major browsers supported.

  19. Improved Helicopter Rotor Performance Prediction through Loose and Tight CFD/CSD Coupling

    Science.gov (United States)

    Ickes, Jacob C.

    Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came in the form

  20. Improved prediction of aerodynamic noise from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Guidati, G.; Bareiss, R.; Wagner, S. [Univ. of Stuttgart, Inst. of Aerodynamics and Gasdynamics, Stuttgart (Germany)

    1997-12-31

    This paper focuses on an improved prediction model for inflow-turbulence noise which takes the true airfoil shape into account. Predictions are compared to the results of acoustic measurements on three 2D-models of 0.25 m chord. Two of the models have NACA-636xx airfoils of 12% and 18% relative thickness. The third airfoil was acoustically optimized by using the new prediction model. In the experiments the turbulence intensity of the flow was strongly increased by mounting a grid with 60 mm wide meshes and 12 mm thick rods onto the tunnel exhaust nozzle. The sound radiated from the airfoil was distinguished by the tunnel background noise by using an acoustic antenna consisting of a cross array of 36 microphones in total. An application of a standard beam-forming algorithm allows to determine how much noise is radiated from different parts of the models. This procedure normally results in a peak at the leading and trailing edge of the airfoil. The strength of the leading-edge peak is taken as the source strength for inflow-turbulence noise. (LN) 14 refs.

  1. BAYESIAN FORECASTS COMBINATION TO IMPROVE THE ROMANIAN INFLATION PREDICTIONS BASED ON ECONOMETRIC MODELS

    Directory of Open Access Journals (Sweden)

    Mihaela Simionescu

    2014-12-01

    Full Text Available There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian shrinkage combination approach. This methodology is used in order to improve the predictions accuracy by including information that is not captured by the econometric models. Therefore, experts’ forecasts are utilized as prior information, for Romania these predictions being provided by Institute for Economic Forecasting (Dobrescu macromodel, National Commission for Prognosis and European Commission. The empirical results for Romanian inflation show the superiority of a fixed effects model compared to other types of econometric models like VAR, Bayesian VAR, simultaneous equations model, dynamic model, log-linear model. The Bayesian combinations that used experts’ predictions as priors, when the shrinkage parameter tends to infinite, improved the accuracy of all forecasts based on individual models, outperforming also zero and equal weights predictions and naïve forecasts.

  2. Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players.

    Directory of Open Access Journals (Sweden)

    Monika Grygorowicz

    Full Text Available To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively the injury of hamstring muscles in professional soccer screened with knee isokinetic tests.Retrospective study.Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con hamstring(H and quadriceps(Q absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658 to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar's chi2 test with Yates's correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p <0.05 was used for all statistical comparisons.340 isokinetic test reports on both limbs of 66 professional soccer players were analysed. Eleven players suffered hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for

  3. Co-production of acetone and ethanol with molar ratio control enables production of improved gasoline or jet fuel blends.

    Science.gov (United States)

    Baer, Zachary C; Bormann, Sebastian; Sreekumar, Sanil; Grippo, Adam; Toste, F Dean; Blanch, Harvey W; Clark, Douglas S

    2016-10-01

    The fermentation of simple sugars to ethanol has been the most successful biofuel process to displace fossil fuel consumption worldwide thus far. However, the physical properties of ethanol and automotive components limit its application in most cases to 10-15 vol% blends with conventional gasoline. Fermentative co-production of ethanol and acetone coupled with a catalytic alkylation reaction could enable the production of gasoline blendstocks enriched in higher-chain oxygenates. Here we demonstrate a synthetic pathway for the production of acetone through the mevalonate precursor hydroxymethylglutaryl-CoA. Expression of this pathway in various strains of Escherichia coli resulted in the co-production of acetone and ethanol. Metabolic engineering and control of the environmental conditions for microbial growth resulted in controllable acetone and ethanol production with ethanol:acetone molar ratios ranging from 0.7:1 to 10.0:1. Specifically, use of gluconic acid as a substrate increased production of acetone and balanced the redox state of the system, predictively reducing the molar ethanol:acetone ratio. Increases in ethanol production and the molar ethanol:acetone ratio were achieved by co-expression of the aldehyde/alcohol dehydrogenase (AdhE) from E. coli MG1655 and by co-expression of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (AdhB) from Z. mobilis. Controlling the fermentation aeration rate and pH in a bioreactor raised the acetone titer to 5.1 g L(-1) , similar to that obtained with wild-type Clostridium acetobutylicum. Optimizing the metabolic pathway, the selection of host strain, and the physiological conditions employed for host growth together improved acetone titers over 35-fold (0.14-5.1 g/L). Finally, chemical catalysis was used to upgrade the co-produced ethanol and acetone at both low and high molar ratios to higher-chain oxygenates for gasoline and jet fuel applications. Biotechnol. Bioeng. 2016;113: 2079-2087. © 2016 Wiley

  4. Relationships between breath ratios, spirituality and health ...

    African Journals Online (AJOL)

    The aim of this retrospective, quantitative study was to investigate relationships between breath ratios, spirituality perceptions and health perceptions, with special reference to breath ratios that best predict optimal health and spirituality. Significant negative correlations were found between breath ratios and spirituality ...

  5. Value of neutrophil-to-lymphocyte ratio for predicting lung cancer prognosis: A meta-analysis of 7,219 patients.

    Science.gov (United States)

    Yu, Yu; Qian, Lei; Cui, Jiuwei

    2017-09-01

    Current evidence suggests that the neutrophil-to-lymphocyte ratio (NLR) may be a biomarker for poor prognosis in lung cancer, although this association remains controversial. Therefore, a meta-analysis was performed to evaluate the association between NLR and lung cancer outcome. A systematic literature search was performed through the PubMed, Embase and Cochrane Library databases (until July 30, 2016), to identify studies evaluating the association between NLR and overall survival (OS) and/or progression-free survival (PFS) among patients with lung cancer. Based on the results of this search, data from 18 studies involving 7,219 patients with lung cancer were evaluated. The pooled hazard ratio (HR) suggested that elevated pretreatment NLR predicted poor OS [HR=1.46, 95% confidence interval (CI): 1.30-1.64] and poor PFS (HR=1.42, 95% CI: 1.15-1.75) among patients with lung cancer. Subgroup analysis revealed that the prognostic value of NLR for predicting poor OS increased among patients who underwent surgery (HR=1.50, 95% CI: 1.21-1.84) or patients with early-stage disease (HR=1.64, 95% CI: 1.37-1.97). An NLR cut-off value of ≥4 significantly predicted poor OS (HR=1.56, 95% CI: 1.31-1.85) and PFS (HR=1.54, 95% CI: 1.13-1.82), particularly in the cases of small-cell lung cancer. Thus, the results of the present meta-analysis suggested that an elevated pretreatment NLR (e.g., ≥4) may be considered as a biomarker for poor prognosis in patients with lung cancer.

  6. Shading Ratio Impact on Photovoltaic Modules and Correlation with Shading Patterns

    Directory of Open Access Journals (Sweden)

    Alonso Gutiérrez Galeano

    2018-04-01

    Full Text Available This paper presents the study of a simplified approach to model and analyze the performance of partially shaded photovoltaic modules using the shading ratio. This approach integrates the characteristics of shaded area and shadow opacity into the photovoltaic cell model. The studied methodology is intended to improve the description of shaded photovoltaic systems by specifying an experimental procedure to quantify the shadow impact. Furthermore, with the help of image processing, the analysis of the shading ratio provides a set of rules useful for predicting the current–voltage behavior and the maximum power points of shaded photovoltaic modules. This correlation of the shading ratio and shading patterns can contribute to the supervision of actual photovoltaic installations. The experimental results validate the proposed approach in monocrystalline and polycrystalline technologies of solar panels.

  7. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.; Motwalli, Olaa Amin; Oliva, Romina; Jankovic, Boris R.; Medvedeva, Yulia; Ashoor, Haitham; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

    2018-01-01

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  8. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.

    2018-03-20

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  9. Medication possession ratio predicts antiretroviral regimens persistence in Peru.

    Science.gov (United States)

    Salinas, Jorge L; Alave, Jorge L; Westfall, Andrew O; Paz, Jorge; Moran, Fiorella; Carbajal-Gonzalez, Danny; Callacondo, David; Avalos, Odalie; Rodriguez, Martin; Gotuzzo, Eduardo; Echevarria, Juan; Willig, James H

    2013-01-01

    In developing nations, the use of operational parameters (OPs) in the prediction of clinical care represents a missed opportunity to enhance the care process. We modeled the impact of multiple measurements of antiretroviral treatment (ART) adherence on antiretroviral treatment outcomes in Peru. Retrospective cohort study including ART naïve, non-pregnant, adults initiating therapy at Hospital Nacional Cayetano Heredia, Lima-Peru (2006-2010). Three OPs were defined: 1) Medication possession ratio (MPR): days with antiretrovirals dispensed/days on first-line therapy; 2) Laboratory monitory constancy (LMC): proportion of 6 months intervals with ≥1 viral load or CD4 reported; 3) Clinic visit constancy (CVC): proportion of 6 months intervals with ≥1 clinic visit. Three multi-variable Cox proportional hazard (PH) models (one per OP) were fit for (1) time of first-line ART persistence and (2) time to second-line virologic failure. All models were adjusted for socio-demographic, clinical and laboratory variables. 856 patients were included in first-line persistence analyses, median age was 35.6 years [29.4-42.9] and most were male (624; 73%). In multivariable PH models, MPR (per 10% increase HR=0.66; 95%CI=0.61-0.71) and LMC (per 10% increase 0.83; 0.71-0.96) were associated with prolonged time on first-line therapies. Among 79 individuals included in time to second-line virologic failure analyses, MPR was the only OP independently associated with prolonged time to second-line virologic failure (per 10% increase 0.88; 0.77-0.99). The capture and utilization of program level parameters such as MPR can provide valuable insight into patient-level treatment outcomes.

  10. From a single encapsulated detector to the spectrometer for INTEGRAL satellite: predicting the peak-to-total ratio at high gamma-energies

    OpenAIRE

    Kshetri, Ritesh

    2012-01-01

    In two recent papers (R. Kshetri, JINST 2012 7 P04008; ibid., P07006), a probabilistic formalism was introduced to predict the response of encapsulated type composite germanium detectors like the SPI (spectrometer for INTEGRAL satellite). Predictions for the peak-to-total and peak-to-background ratios are given at 1.3 MeV for the addback mode of operation. The application of the formalism to clover germanium detector is discussed in two separate papers (R. Kshetri, JINST 2012 7 P07008; ibid.,...

  11. Predictive value of serum apolipoprotein B/apolipoprotein A-I ratio in metabolic syndrome risk: a Chinese cohort study.

    Science.gov (United States)

    Chou, Yu-Ching; Kuan, Jen-Chun; Bai, Chyi-Huey; Yang, Tsan; Chou, Wan-Yun; Hsieh, Po-Chien; You, San-Lin; Hwang, Lee-Ching; Chen, Chien-Hua; Wei, Cheng-Yu; Sun, Chien-An

    2015-06-01

    The purpose of this study was to evaluate whether the apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio is a promising risk predictor of metabolic syndrome (MetS) and to determine the optimal cut-off value of this ratio in detecting subjects with MetS in a Chinese population. A prospective study was conducted using a representative sample of non-institutionized people in Taiwan. A total of 3,343 participants with mean age (±SD) of 39.86 (±15.61) years old were followed up from 2002 to 2007. The primary outcome was the incidence of MetS. The MetS was defined according to a unified criterion established by several major organizations. There were 462 cases of incident MetS during a mean follow-up period of 5.26 years. A significantly stepwise increase in the incidence of MetS across quartiles of the apoB/apoA-I ratio was noted in both sexes after adjustment for potential confounders (p for trend risk of MetS in both men [adjusted hazard ratio (HR) = 6.29, 95 % confidence interval (CI) = 2.79-9.13] and women (adjusted HR = 3.82, 95 % CI = 1.06-6.63). Comparisons of receiver operating characteristics curves indicated that the predictive ability of apoB/apoA-I ratio to detect MetS was better than conventional lipid ratio measurements. Furthermore, the optimal cut-off value of apoB/apoA-I ratio for MetS diagnosis was 0.71 in men and 0.56 in women. These results suggest that an elevated apoB/apoA-I ratio might constitute a potentially crucial measure linked to the risk of developing MetS.

  12. Improving the Q:H strength ratio in women using plyometric exercises.

    Science.gov (United States)

    Tsang, Kavin K W; DiPasquale, Angela A

    2011-10-01

    Plyometric training programs have been implemented in anterior cruciate ligament injury prevention programs. Plyometric exercises are designed to aid in the improvement of muscle strength and neuromuscular control. Our purpose was to examine the effects of plyometric training on lower leg strength in women. Thirty (age = 20.3 ± 1.9 years) recreationally active women were divided into control and experimental groups. The experimental group performed a plyometric training program for 6 weeks, 3 d·wk(-1). All subjects attended 4 testing sessions: before the start of the training program and after weeks 2, 4, and 6. Concentric quadriceps and hamstring strength (dominant leg) was assessed using an isokinetic dynamometer at speeds of 60 and 120°·s(-1). Peak torque, average peak torque, and average power (AvgPower) were measured. The results revealed a significant (p plyometric group than in the control group at testing session 4 and that AvgPower was greater in the plyometric group than in the control group in testing sessions 2-4. Our results indicate that the plyometric training program increased hamstring strength while maintaining quadriceps strength, thereby improving the Q:H strength ratio.

  13. Developing Predictive Maintenance Expertise to Improve Plant Equipment Reliability

    International Nuclear Information System (INIS)

    Wurzbach, Richard N.

    2002-01-01

    On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

  14. The Facial Width-to-Height Ratio Predicts Sex Drive, Sociosexuality, and Intended Infidelity.

    Science.gov (United States)

    Arnocky, Steven; Carré, Justin M; Bird, Brian M; Moreau, Benjamin J P; Vaillancourt, Tracy; Ortiz, Triana; Marley, Nicole

    2017-09-19

    Previous research has linked the facial width-to-height ratio (FWHR) to a host of psychological and behavioral characteristics, primarily in men. In two studies, we examined novel links between FWHR and sex drive. In Study 1, a sample of 145 undergraduate students revealed that FWHR positively predicted sex drive. There were no significant FWHR × sex interactions, suggesting that FWHR is linked to sexuality among both men and women. Study 2 replicated and extended these findings in a sample of 314 students collected from a different Canadian city, which again demonstrated links between the FWHR and sex drive (also in both men and women), as well as sociosexuality and intended infidelity (men only). Internal meta-analytic results confirm the link between FWHR and sex drive among both men and women. These results suggest that FWHR may be an important morphological index of human sexuality.

  15. In-hospital and long-term outcomes of congestive heart failure: Predictive value of B-type and amino-terminal pro-B-type natriuretic peptides and their ratio.

    Science.gov (United States)

    Dai, Yuxiang; Yang, Jun; Takagi, Atsutoshi; Konishi, Hakuoh; Miyazaki, Tetsuro; Masuda, Hiroshi; Shimada, Kazunori; Miyauchi, Katsumi; Daida, Hiroyuki

    2017-08-01

    Relative changes in B-type natriuretic peptide (BNP) and amino terminal pro-BNP (NT-proBNP) levels may help to assess the risk of congestive heart failure (CHF). However, whether these levels at the time of admission enable the prediction of outcomes with acute exacerbation remains unknown. The current study determined the abilities of BNP, NT-proBNP and their ratio to predict in-hospital and long-term outcomes of patients with CHF. Patients who were admitted to the cardiac care unit of Juntendo University Hospital (Tokyo, Japan) with acute CHF onset were consecutively enrolled into the present observational study. Serum levels of BNP and NT-proBNP were immediately measured on admission, and other biomarkers and clinical data were also investigated. Of 195 enrolled patients, 16 (8.2%) succumbed to CHF in hospital and 124 (69.3%) reached the endpoint of mortality or readmission following a median follow-up of 14 months. Multiple linear regression analysis revealed body mass index, low density lipoprotein cholesterol, hemoglobin, estimated glomerular filtration rate and C-reactive protein as independent predictors of the NT-proBNP/BNP ratio. BNP, NT-proBNP and their ratio were significantly higher among those who succumbed to CHF than in those who remained alive in hospital (P<0.05). Logistic regression analysis indicated that the ratio was an independent predictor for in-hospital mortality and long-term outcomes. In conclusion, the ratio of NT-proBNP to BNP more effectively predicts in-hospital outcomes than either factor alone and it may also help to predict outcomes among patients with acute exacerbation of HF.

  16. Gating in time domain as a tool for improving the signal-to-noise ratio of beam transfer function measurements

    CERN Document Server

    Oeftiger, U; Caspers, Fritz

    1992-01-01

    For the measurement of Beam Transfer Functions the signal-to-noise ratio is of great importance. In order to get a reasonable quality of the measured data one may apply averaging and smoothing. In the following another technique called time gating to improve the quality of the measurement will be described. By this technique the measurement data are Fourier transformed and then modified in time domain. Tune gating suppresses signal contributions that are correlated to a time interval when no interesting information is expected. Afterivards an inverse Fourier transform leads to data in frequency domain with an improved signal to noise ratio.

  17. Improving Signal-to-Noise Ratio in Susceptibility Weighted Imaging: A Novel Multicomponent Non-Local Approach.

    Directory of Open Access Journals (Sweden)

    Pasquale Borrelli

    Full Text Available In susceptibility-weighted imaging (SWI, the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR. The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data.

  18. Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

    Science.gov (United States)

    Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

    2017-11-15

    Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  19. Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

    Science.gov (United States)

    Zhao, Changming; Norgia, Michele; Li, Kun

    2018-01-01

    We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.

  20. Improvement of Sodium Leaching Ratio of Ferric Bauxite Sinter after Direct Reduction

    Directory of Open Access Journals (Sweden)

    Wentao Hu

    2017-01-01

    Full Text Available The sodium leaching ratio (ηN of ferric bauxite direct reduction process is much lower than that of ordinary bauxite; thus, the former consumes more sodium than the latter. ηN can be promoted by increasing the dosage of sodium or restricted by increasing the heating temperature and time. However, the restriction effect of heating temperature is 16.67 times larger than that of heating time, and the restriction effect decreases 47.03 times faster when heating temperature increases than that process of heating time. These imply that ηN improves with the increasing sodium carbonate dosage and the decreasing heating temperature.

  1. Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

    Directory of Open Access Journals (Sweden)

    David Ardia

    2016-03-01

    Full Text Available We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior, which is shown to be equivalent to a Jeffreys’ prior, has under an orthogonal normalization for the selection of pairs of cointegrated stock prices and further, its effect for the estimation and prediction of the spread between cointegrated stock prices. We distinguish between models with a normal and Student t distribution since the latter typically provides a better description of daily changes of prices on financial markets. As an empirical application, stocks are used that are ingredients of the Dow Jones Composite Average index. The results show that normalization has little effect on the selection of pairs of cointegrated stocks on the basis of Bayes factors. However, the results stress the importance of the orthogonal normalization for the estimation and prediction of the spread—the deviation from the equilibrium relationship—which leads to better results in terms of profit per capital engagement and risk than using a standard linear normalization.

  2. Generalized financial ratios to predict the equity premium

    NARCIS (Netherlands)

    Algaba, Andres; Boudt, Kris

    2017-01-01

    Empirical evidence for the price-dividend ratio to be a predictor of the equity premium is weak. We argue that changes in the economic conditions and market composition lead to a time-varying relationship between prices, dividends and the equity premium. Exploiting the information in the rolling

  3. International normalized ratio self-testing and self-management: improving patient outcomes

    Directory of Open Access Journals (Sweden)

    Pozzi M

    2016-10-01

    Full Text Available Matteo Pozzi,1 Julia Mitchell,2 Anna Maria Henaine,3 Najib Hanna,4 Ola Safi,4 Roland Henaine2 1Department of Adult Cardiac Surgery, “Louis Pradel” Cardiologic Hospital, Lyon, France; 2Department of Congenital Cardiac Surgery, “Louis Pradel” Cardiologic Hospital, Lyon, France; 3Clinical Pharmacology Unit, Lebanese University, Beirut, Lebanon; 4Pediatric Unit, “Hotel Dieu de France” Hospital, Saint Joseph University, Beirut, Lebanon Abstract: Long term oral anti-coagulation with vitamin K antagonists is a risk factor of hemorrhagic or thromebomlic complications. Periodic laboratory testing of international normalized ratio (INR and a subsequent dose adjustment are therefore mandatory. The use of home testing devices to measure INR has been suggested as a potential way to improve the comfort and compliance of the patients and their families, the frequency of monitoring and, finally, the management and safety of long-term oral anticoagulation. In pediatric patients, increased doses to obtain and maintain the therapeutic target INR, more frequent adjustments and INR testing, multiple medication, inconstant nutritional intake, difficult venepunctures, and the need to go to the laboratory for testing (interruption of school and parents’ work attendance highlight those difficulties. After reviewing the most relevant published studies of self-testing and self-management of INR for adult patients and children on oral anticoagulation, it seems that these are valuable and effective strategies of INR control. Despite an unclear relationship between INR control and clinical effects, these self-strategies provide a better control of the anticoagulant effect, improve patients and their family quality of life, and are an appealing solution in term of cost-effectiveness. Structured education and knowledge evaluation by trained health care professionals is required for children, to be able to adjust their dose treatment safely and accurately. However

  4. Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study.

    Science.gov (United States)

    Agrawal, Swati; Cerdeira, Ana Sofia; Redman, Christopher; Vatish, Manu

    2018-02-01

    Preeclampsia is a major cause of morbidity and mortality worldwide. Numerous candidate biomarkers have been proposed for diagnosis and prediction of preeclampsia. Measurement of maternal circulating angiogenesis biomarker as the ratio of sFlt-1 (soluble FMS-like tyrosine kinase-1; an antiangiogenic factor)/PlGF (placental growth factor; an angiogenic factor) reflects the antiangiogenic balance that characterizes incipient or overt preeclampsia. The ratio increases before the onset of the disease and thus may help in predicting preeclampsia. We conducted a meta-analysis to explore the predictive accuracy of sFlt-1/PlGF ratio in preeclampsia. We included 15 studies with 534 cases with preeclampsia and 19 587 controls. The ratio has a pooled sensitivity of 80% (95% confidence interval, 0.68-0.88), specificity of 92% (95% confidence interval, 0.87-0.96), positive likelihood ratio of 10.5 (95% confidence interval, 6.2-18.0), and a negative likelihood ratio of 0.22 (95% confidence interval, 0.13-0.35) in predicting preeclampsia in both high- and low-risk patients. Most of the studies have not made a distinction between early- and late-onset disease, and therefore, the analysis for it could not be done. It can prove to be a valuable screening tool for preeclampsia and may also help in decision-making, treatment stratification, and better resource allocation. © 2017 American Heart Association, Inc.

  5. Multidimensional assessment of patient condition and mutational analysis in peripheral blood, as tools to improve outcome prediction in myelodysplastic syndromes: A prospective study of the Spanish MDS group.

    Science.gov (United States)

    Ramos, Fernando; Robledo, Cristina; Pereira, Arturo; Pedro, Carmen; Benito, Rocío; de Paz, Raquel; Del Rey, Mónica; Insunza, Andrés; Tormo, Mar; Díez-Campelo, María; Xicoy, Blanca; Salido, Eduardo; Sánchez-Del-Real, Javier; Arenillas, Leonor; Florensa, Lourdes; Luño, Elisa; Del Cañizo, Consuelo; Sanz, Guillermo F; María Hernández-Rivas, Jesús

    2017-09-01

    The International Prognostic Scoring System and its revised form (IPSS-R) are the most widely used indices for prognostic assessment of patients with myelodysplastic syndromes (MDS), but can only partially account for the observed variation in patient outcomes. This study aimed to evaluate the relative contribution of patient condition and mutational status in peripheral blood when added to the IPSS-R, for estimating overall survival and the risk of leukemic transformation in patients with MDS. A prospective cohort (2006-2015) of 200 consecutive patients with MDS were included in the study series and categorized according to the IPSS-R. Patients were further stratified according to patient condition (assessed using the multidimensional Lee index for older adults) and genetic mutations (peripheral blood samples screened using next-generation sequencing). The change in likelihood-ratio was tested in Cox models after adding individual covariates. The addition of the Lee index to the IPSS-R significantly improved prediction of overall survival [hazard ratio (HR) 3.02, 95% confidence interval (CI) 1.96-4.66, P < 0.001), and mutational analysis significantly improved prediction of leukemic evolution (HR 2.64, 1.56-4.46, P < 0.001). Non-leukemic death was strongly linked to patient condition (HR 2.71, 1.72-4.25, P < 0.001), but not to IPSS-R score (P = 0.35) or mutational status (P = 0.75). Adjustment for exposure to disease-modifying therapy, evaluated as a time-dependent covariate, had no effect on the proposed model's predictive ability. In conclusion, patient condition, assessed by the multidimensional Lee index and patient mutational status can improve the prediction of clinical outcomes of patients with MDS already stratified by IPSS-R. © 2017 Wiley Periodicals, Inc.

  6. Tumor-stroma ratio predicts recurrence in patients with colon cancer treated with neoadjuvant chemotherapy

    DEFF Research Database (Denmark)

    Hansen, Torben Frøstrup; Kjær-Frifeldt, Sanne; Lindebjerg, Jan

    2017-01-01

    BACKGROUND: Neoadjuvant chemotherapy represents a new treatment approach to locally advanced colon cancer. The aim of this study was to analyze the ability of tumor-stroma ratio (TSR) to predict disease recurrence in patients with locally advanced colon cancer treated with neoadjuvant chemotherapy....... MATERIAL AND METHODS: This study included 65 patients with colon cancer treated with neoadjuvant chemotherapy in a phase II trial. All patients were planned for three cycles of capecitabine and oxaliplatin before surgery. Hematoxylin and eosin stained tissue sections from surgically resected primary tumors...... was 55%, compared to 94% in the group of patients with a high TSR. CONCLUSIONS: TSR assessed in the surgically resected primary tumor from patients with locally advanced colon cancer treated with neoadjuvant chemotherapy provides prognostic value and may serve as a relevant parameter in selecting...

  7. Landslide Prediction Capability by Comparison of Frequency Ratio ...

    Indian Academy of Sciences (India)

    8

    3.2.2.1.4 Curvature: The surface curvature at a point is the curvature of a line formed .... (Pham et al, 2017) or by saturating the lower part of the material in a .... In order to fuzzy analysis, at first, the weights of frequency ratio was standardized.

  8. A note on trader Sharpe Ratios.

    Science.gov (United States)

    Coates, John M; Page, Lionel

    2009-11-25

    Traders in the financial world are assessed by the amount of money they make and, increasingly, by the amount of money they make per unit of risk taken, a measure known as the Sharpe Ratio. Little is known about the average Sharpe Ratio among traders, but the Efficient Market Hypothesis suggests that traders, like asset managers, should not outperform the broad market. Here we report the findings of a study conducted in the City of London which shows that a population of experienced traders attain Sharpe Ratios significantly higher than the broad market. To explain this anomaly we examine a surrogate marker of prenatal androgen exposure, the second-to-fourth finger length ratio (2D:4D), which has previously been identified as predicting a trader's long term profitability. We find that it predicts the amount of risk taken by traders but not their Sharpe Ratios. We do, however, find that the traders' Sharpe Ratios increase markedly with the number of years they have traded, a result suggesting that learning plays a role in increasing the returns of traders. Our findings present anomalous data for the Efficient Markets Hypothesis.

  9. A note on trader Sharpe Ratios.

    Directory of Open Access Journals (Sweden)

    John M Coates

    Full Text Available Traders in the financial world are assessed by the amount of money they make and, increasingly, by the amount of money they make per unit of risk taken, a measure known as the Sharpe Ratio. Little is known about the average Sharpe Ratio among traders, but the Efficient Market Hypothesis suggests that traders, like asset managers, should not outperform the broad market. Here we report the findings of a study conducted in the City of London which shows that a population of experienced traders attain Sharpe Ratios significantly higher than the broad market. To explain this anomaly we examine a surrogate marker of prenatal androgen exposure, the second-to-fourth finger length ratio (2D:4D, which has previously been identified as predicting a trader's long term profitability. We find that it predicts the amount of risk taken by traders but not their Sharpe Ratios. We do, however, find that the traders' Sharpe Ratios increase markedly with the number of years they have traded, a result suggesting that learning plays a role in increasing the returns of traders. Our findings present anomalous data for the Efficient Markets Hypothesis.

  10. Impact of the Triglyceride/High-Density Lipoprotein Cholesterol Ratio and the Hypertriglyceremic-Waist Phenotype to Predict the Metabolic Syndrome and Insulin Resistance.

    Science.gov (United States)

    von Bibra, Helene; Saha, Sarama; Hapfelmeier, Alexander; Müller, Gabriele; Schwarz, Peter E H

    2017-07-01

    Insulin resistance is the underlying mechanism for the metabolic syndrome and associated dyslipidaemia that theoretically implies a practical tool for identifying individuals at risk for cardiovascular disease and type-2-diabetes. Another screening tool is the hypertriglyceremic-waist phenotype (HTW). There is important impact of the ethnic background but a lack of studied European populations for the association of the triglyceride/high-density lipoprotein cholesterol (HDL-C) ratio and insulin resistance. This observational, retrospective study evaluated lipid ratios and the HTW for predicting the metabolic syndrome/insulin resistance in 1932 non-diabetic individuals from Germany in the fasting state and during a glucose tolerance test. The relations of triglyceride/HDL-C, total-cholesterol/HDL-C, and low-density lipoprotein cholesterol/HDL-C with 5 surrogate estimates of insulin resistance/sensitivity and metabolic syndrome were analysed by linear regression analysis and receiver operating characteristics (ROC) in participants with normal (n=1 333) or impaired fasting glucose (n=599), also for the impact of gender. Within the lipid ratios, triglyceride/HDL-C had the strongest associations with insulin resistance/sensitivity markers. In the prediction of metabolic syndrome, diagnostic accuracy was good for triglyceride/HDL-C (area under the ROC curve 0.817) with optimal cut-off points (in mg/dl units) of 2.8 for men (80% sensitivity, 71% specificity) and 1.9 for women (80% sensitivity, 75% specificity) and fair for HTW and HOMA-IR (area under the curve 0.773 and 0.761). These data suggest the triglyceride/HDL-C ratio as a physiologically relevant and practical index for predicting the concomitant presence of metabolic syndrome, insulin resistance and dyslipidaemia for therapeutic and preventive care in apparently healthy European populations. © Georg Thieme Verlag KG Stuttgart · New York.

  11. Appropriate NH4+: NO3- ratio improves low light tolerance of mini Chinese cabbage seedlings.

    Science.gov (United States)

    Hu, Linli; Liao, Weibiao; Dawuda, Mohammed Mujitaba; Yu, Jihua; Lv, Jian

    2017-01-23

    In northwest of China, mini Chinese cabbage (Brassica pekinensis) is highly valued by consumers, and is widely cultivated during winter in solar-greenhouses where low light (LL) fluence (between 85 and 150 μmol m -2 s -1 in day) is a major abiotic stress factor limiting plant growth and crop productivity. The mechanisms with which various NH 4 + : NO 3 - ratios affected growth and photosynthesis of mini Chinese cabbage under normal (200 μmol m -2 s -1 ) and low (100 μmol m -2 s -1 ) light conditions was investigated. The four solutions with different ratios of NH 4 + : NO 3 - applied were 0:100, 10:90, 15:85 and 25:75 with the set up in a glasshouse in hydroponic culture. The most appropriate NH 4 + : NO 3 - ratio that improved the tolerance of mini Chinese cabbage seedlings to LL was found in our current study. Under low light, the application of NH 4 + : NO 3 - (10:90) significantly stimulated growth compared to only NO 3 - by increasing leaf area, canopy spread, biomass accumulation, and net photosynthetic rate. The increase in net photosynthetic rate was associated with an increase in: 1) maximum and effective quantum yield of PSII; 2) activities of Calvin cycle enzymes; and 3) levels of mRNA relative expression of several genes involved in Calvin cycle. In addition, glucose, fructose, sucrose, starch and total carbohydrate, which are the products of CO 2 assimilation, accumulated most in the cabbage leaves that were supplied with NH 4 + : NO 3 - (10:90) under LL condition. Low light reduced the carbohydrate: nitrogen (C: N) ratio while the application of NH 4 + : NO 3 - (10:90) alleviated the negative effect of LL on C: N ratio mainly by increasing total carbohydrate contents. The application of NH 4 + :NO 3 - (10:90) increased rbcL, rbcS, FBA, FBPase and TK expression and/or activities, enhanced photosynthesis, carbohydrate accumulation and improved the tolerance of mini Chinese cabbage seedlings to LL. The results of this study would provide

  12. Filling high aspect ratio trenches by superconformal chemical vapor deposition: Predictive modeling and experiment

    Science.gov (United States)

    Wang, Wenjiao B.; Abelson, John R.

    2014-11-01

    Complete filling of a deep recessed structure with a second material is a challenge in many areas of nanotechnology fabrication. A newly discovered superconformal coating method, applicable in chemical vapor deposition systems that utilize a precursor in combination with a co-reactant, can solve this problem. However, filling is a dynamic process in which the trench progressively narrows and the aspect ratio (AR) increases. This reduces species diffusion within the trench and may drive the component partial pressures out of the regime for superconformal coating. We therefore derive two theoretical models that can predict the possibility for filling. First, we recast the diffusion-reaction equation for the case of a sidewall with variable taper angle. This affords a definition of effective AR, which is larger than the nominal AR due to the reduced species transport. We then derive the coating profile, both for superconformal and for conformal coating. The critical (most difficult) step in the filling process occurs when the sidewalls merge at the bottom of the trench to form the V shape. Experimentally, for the Mg(DMADB)2/H2O system and a starting AR = 9, this model predicts that complete filling will not be possible, whereas experimentally we do obtain complete filling. We then hypothesize that glancing-angle, long-range transport of species may be responsible for the better than predicted filling. To account for the variable range of species transport, we construct a ballistic transport model. This incorporates the incident flux from outside the structure, cosine law re-emission from surfaces, and line-of-sight transport between internal surfaces. We cast the transport probability between all positions within the trench into a matrix that represents the redistribution of flux after one cycle of collisions. Matrix manipulation then affords a computationally efficient means to determine the steady-state flux distribution and growth rate for a given taper angle. The

  13. Improved steamflood analytical model

    Energy Technology Data Exchange (ETDEWEB)

    Chandra, S.; Mamora, D.D. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas A and M Univ., TX (United States)

    2005-11-01

    Predicting the performance of steam flooding can help in the proper execution of enhanced oil recovery (EOR) processes. The Jones model is often used for analytical steam flooding performance prediction, but it does not accurately predict oil production peaks. In this study, an improved steam flood model was developed by modifying 2 of the 3 components of the capture factor in the Jones model. The modifications were based on simulation results from a Society of Petroleum Engineers (SPE) comparative project case model. The production performance of a 5-spot steamflood pattern unit was simulated and compared with results obtained from the Jones model. Three reservoir types were simulated through the use of 3-D Cartesian black oil models. In order to correlate the simulation and the Jones analytical model results for the start and height of the production peak, the dimensionless steam zone size was modified to account for a decrease in oil viscosity during steam flooding and its dependence on the steam injection rate. In addition, the dimensionless volume of displaced oil produced was modified from its square-root format to an exponential form. The modified model improved results for production performance by up to 20 years of simulated steam flooding, compared to the Jones model. Results agreed with simulation results for 13 different cases, including 3 different sets of reservoir and fluid properties. Reservoir engineers will benefit from the improved accuracy of the model. Oil displacement calculations were based on methods proposed in earlier research, in which the oil displacement rate is a function of cumulative oil steam ratio. The cumulative oil steam ratio is a function of overall thermal efficiency. Capture factor component formulae were presented, as well as charts of oil production rates and cumulative oil-steam ratios for various reservoirs. 13 refs., 4 tabs., 29 figs.

  14. Improved prediction of genetic predisposition to psychiatric disorders using genomic feature best linear unbiased prediction models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders

    is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia.......6% for the null model). Conclusion: The improvement in predictive ability for schizophrenia was marginal, however, greater improvement is expected for the larger ADHD data....

  15. Incorporating Scale-Dependent Fracture Stiffness for Improved Reservoir Performance Prediction

    Science.gov (United States)

    Crawford, B. R.; Tsenn, M. C.; Homburg, J. M.; Stehle, R. C.; Freysteinson, J. A.; Reese, W. C.

    2017-12-01

    We present a novel technique for predicting dynamic fracture network response to production-driven changes in effective stress, with the potential for optimizing depletion planning and improving recovery prediction in stress-sensitive naturally fractured reservoirs. A key component of the method involves laboratory geomechanics testing of single fractures in order to develop a unique scaling relationship between fracture normal stiffness and initial mechanical aperture. Details of the workflow are as follows: tensile, opening mode fractures are created in a variety of low matrix permeability rocks with initial, unstressed apertures in the micrometer to millimeter range, as determined from image analyses of X-ray CT scans; subsequent hydrostatic compression of these fractured samples with synchronous radial strain and flow measurement indicates that both mechanical and hydraulic aperture reduction varies linearly with the natural logarithm of effective normal stress; these stress-sensitive single-fracture laboratory observations are then upscaled to networks with fracture populations displaying frequency-length and length-aperture scaling laws commonly exhibited by natural fracture arrays; functional relationships between reservoir pressure reduction and fracture network porosity, compressibility and directional permeabilities as generated by such discrete fracture network modeling are then exported to the reservoir simulator for improved naturally fractured reservoir performance prediction.

  16. A lower ratio of omega-6 to omega-3 fatty acids predicts better hippocampus-dependent spatial memory and cognitive status in older adults.

    Science.gov (United States)

    Andruchow, Nadia D; Konishi, Kyoko; Shatenstein, Bryna; Bohbot, Véronique D

    2017-10-01

    Evidence from several cross-sectional studies indicates that an increase in omega-6 to omega-3 fatty acids (FAs) may negatively affect cognition in old age. The hippocampus is among the first neural structures affected by age and atrophy in this brain region is associated with cognitive decline. Therefore, we hypothesized that a lower omega-6:3 FA ratio would predict better hippocampus-dependent spatial memory, and a higher general cognitive status. Fifty-two healthy older adults completed a Food Frequency Questionnaire, the Montreal Cognitive Assessment test (MoCA; a test of global cognition) and virtual navigation tasks that assess navigational strategies and spatial memory. In this cross-sectional study, a lower ratio of omega-6 to omega-3 FA intake strongly predicted more accurate hippocampus-dependent spatial memory and faster learning on our virtual navigation tasks, as well as higher cognitive status overall. These results may help elucidate why certain dietary patterns with a lower omega-6:3 FA ratio, like the Mediterranean diet, are associated with reduced risk of cognitive decline. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  17. Adiposity to muscle ratio predicts incident physical limitation in a cohort of 3,153 older adults--an alternative measurement of sarcopenia and sarcopenic obesity.

    Science.gov (United States)

    Auyeung, Tung Wai; Lee, Jenny Shun Wah; Leung, Jason; Kwok, Timothy; Woo, Jean

    2013-08-01

    Conventionally, sarcopenia is defined by muscle mass and physical performance. We hypothesized that the disability caused by sarcopenia and sarcopenic obesity was related to the amount of adiposity or body weight bearing on a unit of muscle mass, or the adiposity to muscle ratio. We therefore examined whether this ratio could predict physical limitation by secondary analysis of the data in our previous study. We recruited 3,153 community-dwelling adults aged >65 years and their body composition was measured by dual-energy X-ray absorptiometry. Assessment of physical limitation was undertaken 4 years later. The relationship between baseline adiposity to muscle ratio and incident physical limitation was examined by logistic regression. In men, the adiposity to muscle ratios, namely total body fat to lower-limb muscle mass, total body fat to fat-free mass (FFM), and body weight to FFM, were predictive of physical limitation before and after adjustment for the covariates: age, Mini-mental Status Examination score, Geriatric Depression Scale score >8, and the diagnosis of chronic obstructive pulmonary disease, diabetes mellitus, hypertension, heart disease, and stroke (all p values physical limitation 4 years later both before and after adjustment for the same set of covariates (all p values physical limitation in older women across the entire range of the total body fat to lower-limb muscle mass ratio; and in older men when this ratio was equal to or greater than 0.75.

  18. Improving the accuracy of protein secondary structure prediction using structural alignment

    Directory of Open Access Journals (Sweden)

    Gallin Warren J

    2006-06-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

  19. Clonal Evaluation of Prostate Cancer by ERG/SPINK1 Status to Improve Prognosis Prediction

    Science.gov (United States)

    2017-12-01

    19 NIH Exploiting drivers of androgen receptor signaling negative prostate cancer for precision medicine Goal(s): Identify novel potential drivers...AWARD NUMBER: W81XWH-14-1-0466 TITLE: Clonal evaluation of prostate cancer by ERG/SPINK1 status to improve prognosis prediction PRINCIPAL...Sept 2017 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Clonal Evaluation of Prostate Cancer by ERG/SPINK1 Status to Improve Prognosis Prediction 5b

  20. From a single encapsulated detector to the spectrometer for INTEGRAL satellite: predicting the peak-to-total ratio at high γ-energies

    International Nuclear Information System (INIS)

    Kshetri, R

    2012-01-01

    In two recent papers (R. Kshetri, JINST 2012 7 P04008; ibid., P07006), a probabilistic formalism was introduced to predict the response of encapsulated type composite germanium detectors like the SPI (spectrometer for INTEGRAL satellite). Predictions for the peak-to-total and peak-to-background ratios are given at 1.3 MeV for the addback mode of operation. The application of the formalism to clover germanium detector is discussed in two separate papers (R. Kshetri, JINST 2012 7 P07008; ibid., P08015). Using the basic approach developed in those papers, for the first time we present a procedure for calculating the peak-to-total ratio of the cluster detector for γ-energies up to 8 MeV. Results are shown for both bare and suppressed detectors as well as for the single crystal and addback modes of operation. We have considered the experimental data of (i) peak-to-total ratio at 1.3 MeV, and (ii) single detector efficiency and addback factor for other energies up to 8 MeV. Using this data, an approximate method of calculating the peak-to-total ratio of other composite detectors, is shown. Experimental validation of our approach (for energies up to 8 MeV) has been confirmed considering the data of the SPI spectrometer. We have discussed about comparisons between various modes of operation and suppression cases. The present paper is the fifth in the series of papers on composite germanium detectors and for the first time discusses about the change in fold distribution and peak-to-total ratio for sophisticated detectors consisting of several modules of miniball, cluster and SPI detectors. Our work could provide a guidance in designing new composite detectors and in performing experimental studies with the existing detectors for high energy gamma-rays.

  1. From a single encapsulated detector to the spectrometer for INTEGRAL satellite: predicting the peak-to-total ratio at high γ-energies

    Science.gov (United States)

    Kshetri, R.

    2012-12-01

    In two recent papers (R. Kshetri, JINST 2012 7 P04008; ibid., P07006), a probabilistic formalism was introduced to predict the response of encapsulated type composite germanium detectors like the SPI (spectrometer for INTEGRAL satellite). Predictions for the peak-to-total and peak-to-background ratios are given at 1.3 MeV for the addback mode of operation. The application of the formalism to clover germanium detector is discussed in two separate papers (R. Kshetri, JINST 2012 7 P07008; ibid., P08015). Using the basic approach developed in those papers, for the first time we present a procedure for calculating the peak-to-total ratio of the cluster detector for γ-energies up to 8 MeV. Results are shown for both bare and suppressed detectors as well as for the single crystal and addback modes of operation. We have considered the experimental data of (i) peak-to-total ratio at 1.3 MeV, and (ii) single detector efficiency and addback factor for other energies up to 8 MeV. Using this data, an approximate method of calculating the peak-to-total ratio of other composite detectors, is shown. Experimental validation of our approach (for energies up to 8 MeV) has been confirmed considering the data of the SPI spectrometer. We have discussed about comparisons between various modes of operation and suppression cases. The present paper is the fifth in the series of papers on composite germanium detectors and for the first time discusses about the change in fold distribution and peak-to-total ratio for sophisticated detectors consisting of several modules of miniball, cluster and SPI detectors. Our work could provide a guidance in designing new composite detectors and in performing experimental studies with the existing detectors for high energy gamma-rays.

  2. Lidar signal-to-noise ratio improvements: Considerations and techniques

    Science.gov (United States)

    Hassebo, Yasser Y.

    The primary objective of this study is to improve lidar signal-to-noise ratio (SNR) and hence extend attainable lidar ranges through reduction of the sky background noise (BGP), which dominates other sources of noise in daytime operations. This is particularly important for Raman lidar techniques where the Raman backscattered signal of interest is relatively weak compared with the elastic backscatter lidars. Two approaches for reduction of sky background noise are considered: (1) Improvements in lidar SNR by optimization of the design of the lidar receiver were examined by a series of simulations. This part of the research concentrated on biaxial lidar systems, where overlap between laser beam and receiver field of view (FOV) is an important aspect of noise considerations. The first optimized design evolved is a wedge shaped aperture. While this design has the virtue of greatly reducing background light, it is difficult to implement practically, requiring both changes in area and position with lidar range. A second more practical approach, which preserves some of the advantages of the wedge design, was also evolved. This uses a smaller area circular aperture optimally located in the image plane for desired ranges. Simulated numerical results for a biaxial lidar have shown that the best receiver parameters selection is one using a small circular aperture (field stop) with a small telescope focal length f, to ensure the minimum FOV that accepts all return signals over the entire lidar range while at the same time minimizing detected BGP and hence maximizing lidar SNR and attainable lidar ranges. The improvement in lidar SNR was up to 18%. (2) A polarization selection technique was implemented to reduce sky background signal for linearly polarized monostatic elastic backscatter lidar measurements. The technique takes advantage of naturally occurring polarization properties in scattered sky light, and then ensures that both the lidar transmitter and receiver track and

  3. Temperature prediction model of asphalt pavement in cold regions based on an improved BP neural network

    International Nuclear Information System (INIS)

    Xu, Bo; Dan, Han-Cheng; Li, Liang

    2017-01-01

    Highlights: • Pavement temperature prediction model is presented with improved BP neural network. • Dynamic and static methods are presented to predict pavement temperature. • Pavement temperature can be excellently predicted in next 3 h. - Abstract: Ice cover on pavement threatens traffic safety, and pavement temperature is the main factor used to determine whether the wet pavement is icy or not. In this paper, a temperature prediction model of the pavement in winter is established by introducing an improved Back Propagation (BP) neural network model. Before the application of the BP neural network model, many efforts were made to eliminate chaos and determine the regularity of temperature on the pavement surface (e.g., analyze the regularity of diurnal and monthly variations of pavement temperature). New dynamic and static prediction methods are presented by improving the algorithms to intelligently overcome the prediction inaccuracy at the change point of daily temperature. Furthermore, some scenarios have been compared for different dates and road sections to verify the reliability of the prediction model. According to the analysis results, the daily pavement temperatures can be accurately predicted for the next 3 h from the time of prediction by combining the dynamic and static prediction methods. The presented method in this paper can provide technical references for temperature prediction of the pavement and the development of an early-warning system for icy pavements in cold regions.

  4. Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency.

    Science.gov (United States)

    Mohamed, Omar; Wang, Jihong; Khalil, Ashraf; Limhabrash, Marwan

    2016-01-01

    This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load-frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.

  5. Improved Trust Prediction in Business Environments by Adaptive Neuro Fuzzy Inference Systems

    Directory of Open Access Journals (Sweden)

    Ali Azadeh

    2015-06-01

    Full Text Available Trust prediction turns out to be an important challenge when cooperation among intelligent agents with an impression of trust in their mind, is investigated. In other words, predicting trust values for future time slots help partners to identify the probability of continuing a relationship. Another important case to be considered is the context of trust, i.e. the services and business commitments for which a relationship is defined. Hence, intelligent agents should focus on improving trust to provide a stable and confident context. Modelling of trust between collaborating parties seems to be an important component of the business intelligence strategy. In this regard, a set of metrics have been considered by which the value of confidence level for predicted trust values has been estimated. These metrics are maturity, distance and density (MD2. Prediction of trust for future mutual relationships among agents is a problem that is addressed in this study. We introduce a simulation-based model which utilizes linguistic variables to create various scenarios. Then, future trust values among agents are predicted by the concept of adaptive neuro-fuzzy inference system (ANFIS. Mean absolute percentage errors (MAPEs resulted from ANFIS are compared with confidence levels which are determined by applying MD2. Results determine the efficiency of MD2 for forecasting trust values. This is the first study that utilizes the concept of MD2 for improvement of business trust prediction.

  6. Ambient organic carbon to elemental carbon ratios: Influence of the thermal–optical temperature protocol and implications

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Yuan, E-mail: ycheng@mail.tsinghua.edu.cn [State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing (China); He, Ke-bin, E-mail: hekb@tsinghua.edu.cn [State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing (China); State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing (China); Duan, Feng-kui; Du, Zhen-yu [State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing (China); Zheng, Mei [College of Environmental Sciences and Engineering, Peking University, Beijing (China); Ma, Yong-liang [State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing (China)

    2014-01-01

    Ambient organic carbon (OC) to elemental carbon (EC) ratios are strongly associated with not only the radiative forcing due to aerosols but also the extent of secondary organic aerosol (SOA) formation. An inter-comparison study was conducted based on fine particulate matter samples collected during summer in Beijing to investigate the influence of the thermal–optical temperature protocol on the OC to EC ratio. Five temperature protocols were used such that the NIOSH (National Institute for Occupational Safety and Health) and EUSAAR (European Supersites for Atmospheric Aerosol Research) protocols were run by the Sunset carbon analyzer while the IMPROVE (the Interagency Monitoring of Protected Visual Environments network)-A protocol and two alternative protocols designed based on NIOSH and EUSAAR were run by the DRI analyzer. The optical attenuation measured by the Sunset carbon analyzer was more easily biased by the shadowing effect, whereas total carbon agreed well between the Sunset and DRI analyzers. The EC{sub IMPROVE-A} (EC measured by the IMPROVE-A protocol; similar hereinafter) to EC{sub NIOSH} ratio and the EC{sub IMPROVE-A} to EC{sub EUSAAR} ratio averaged 1.36 ± 0.21 and 0.91 ± 0.10, respectively, both of which exhibited little dependence on the biomass burning contribution. Though the temperature protocol had substantial influence on the OC to EC ratio, the contributions of secondary organic carbon (SOC) to OC, which were predicted by the EC-tracer method, did not differ significantly among the five protocols. Moreover, the SOC contributions obtained in this study were comparable with previous results based on field observation (typically between 45 and 65%), but were substantially higher than the estimation provided by an air quality model (only 18%). The comparison of SOC and WSOC suggests that when using the transmittance charring correction, all of the three common protocols (i.e., IMPROVE-A, NIOSH and EUSAAR) could be reliable for the estimation

  7. Ambient organic carbon to elemental carbon ratios: Influence of the thermal–optical temperature protocol and implications

    International Nuclear Information System (INIS)

    Cheng, Yuan; He, Ke-bin; Duan, Feng-kui; Du, Zhen-yu; Zheng, Mei; Ma, Yong-liang

    2014-01-01

    Ambient organic carbon (OC) to elemental carbon (EC) ratios are strongly associated with not only the radiative forcing due to aerosols but also the extent of secondary organic aerosol (SOA) formation. An inter-comparison study was conducted based on fine particulate matter samples collected during summer in Beijing to investigate the influence of the thermal–optical temperature protocol on the OC to EC ratio. Five temperature protocols were used such that the NIOSH (National Institute for Occupational Safety and Health) and EUSAAR (European Supersites for Atmospheric Aerosol Research) protocols were run by the Sunset carbon analyzer while the IMPROVE (the Interagency Monitoring of Protected Visual Environments network)-A protocol and two alternative protocols designed based on NIOSH and EUSAAR were run by the DRI analyzer. The optical attenuation measured by the Sunset carbon analyzer was more easily biased by the shadowing effect, whereas total carbon agreed well between the Sunset and DRI analyzers. The EC IMPROVE-A (EC measured by the IMPROVE-A protocol; similar hereinafter) to EC NIOSH ratio and the EC IMPROVE-A to EC EUSAAR ratio averaged 1.36 ± 0.21 and 0.91 ± 0.10, respectively, both of which exhibited little dependence on the biomass burning contribution. Though the temperature protocol had substantial influence on the OC to EC ratio, the contributions of secondary organic carbon (SOC) to OC, which were predicted by the EC-tracer method, did not differ significantly among the five protocols. Moreover, the SOC contributions obtained in this study were comparable with previous results based on field observation (typically between 45 and 65%), but were substantially higher than the estimation provided by an air quality model (only 18%). The comparison of SOC and WSOC suggests that when using the transmittance charring correction, all of the three common protocols (i.e., IMPROVE-A, NIOSH and EUSAAR) could be reliable for the estimation of SOC by the EC

  8. The ratio of CRP to prealbumin levels predict mortality in patients with hospital-acquired acute kidney injury

    Directory of Open Access Journals (Sweden)

    Hao Chuanming

    2011-06-01

    Full Text Available Abstract Background Animal and human studies suggest that inflammation and malnutrition are common in acute kidney injury (AKI patients. However, only a few studies reported CRP, a marker of inflammation, albumin, prealbumin and cholesterol, markers of nutritional status were associated with the prognosis of AKI patients. No study examined whether the combination of inflammatory and nutritional markers could predict the mortality of AKI patients. Methods 155 patients with hospital-acquired AKI were recruited to this prospective cohort study according to RIFLE (Risk, Injury, Failure, Lost or End Stage Kidney criteria. C-reactive protein (CRP, and the nutritional markers (albumin, prealbumin and cholesterol measured at nephrology consultation were analyzed in relation to all cause mortality of these patients. In addition, CRP and prealbumin were also measured in healthy controls (n = 45, maintenance hemodialysis (n = 70 and peritoneal dialysis patients (n = 50 and then compared with AKI patients. Results Compared with healthy controls and end-stage renal disease patients on maintenance hemodialysis or peritoneal dialysis, patients with AKI had significantly higher levels of CRP/prealbumin (p 28 days. Similarly, the combined factors including the ratio of CRP to albumin (CRP/albumin, CRP/prealbumin and CRP/cholesterol were also significantly higher in the former group (p p = 0.027 while the others (CRP, albumin, prealbumin, cholesterol, CRP/albumin and CRP/cholesterol became non-significantly associated. The hazard ratio was 1.00 (reference, 1.85, 2.25 and 3.89 for CRP/prealbumin increasing according to quartiles (p = 0.01 for the trend. Conclusions Inflammation and malnutrition were common in patients with AKI. Higher level of the ratio of CRP to prealbumin was associated with mortality of AKI patients independent of the severity of illness and it may be a valuable addition to SOFA score to independent of the severity of illness and it may be a

  9. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model

    OpenAIRE

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2017-01-01

    Purpose The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. Materials and Methods This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC m...

  10. Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  11. Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia.

    Science.gov (United States)

    Menéndez, R; Martínez, R; Reyes, S; Mensa, J; Filella, X; Marcos, M A; Martínez, A; Esquinas, C; Ramirez, P; Torres, A

    2009-07-01

    Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor alpha (TNFalpha) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, > or = 65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, > or = 65 years of age) scales. A total of 453 hospitalised CAP patients were included. The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

  12. Improving consensus contact prediction via server correlation reduction.

    Science.gov (United States)

    Gao, Xin; Bu, Dongbo; Xu, Jinbo; Li, Ming

    2009-05-06

    Protein inter-residue contacts play a crucial role in the determination and prediction of protein structures. Previous studies on contact prediction indicate that although template-based consensus methods outperform sequence-based methods on targets with typical templates, such consensus methods perform poorly on new fold targets. However, we find out that even for new fold targets, the models generated by threading programs can contain many true contacts. The challenge is how to identify them. In this paper, we develop an integer linear programming model for consensus contact prediction. In contrast to the simple majority voting method assuming that all the individual servers are equally important and independent, the newly developed method evaluates their correlation by using maximum likelihood estimation and extracts independent latent servers from them by using principal component analysis. An integer linear programming method is then applied to assign a weight to each latent server to maximize the difference between true contacts and false ones. The proposed method is tested on the CASP7 data set. If the top L/5 predicted contacts are evaluated where L is the protein size, the average accuracy is 73%, which is much higher than that of any previously reported study. Moreover, if only the 15 new fold CASP7 targets are considered, our method achieves an average accuracy of 37%, which is much better than that of the majority voting method, SVM-LOMETS, SVM-SEQ, and SAM-T06. These methods demonstrate an average accuracy of 13.0%, 10.8%, 25.8% and 21.2%, respectively. Reducing server correlation and optimally combining independent latent servers show a significant improvement over the traditional consensus methods. This approach can hopefully provide a powerful tool for protein structure refinement and prediction use.

  13. Improving consensus contact prediction via server correlation reduction

    Directory of Open Access Journals (Sweden)

    Xu Jinbo

    2009-05-01

    Full Text Available Abstract Background Protein inter-residue contacts play a crucial role in the determination and prediction of protein structures. Previous studies on contact prediction indicate that although template-based consensus methods outperform sequence-based methods on targets with typical templates, such consensus methods perform poorly on new fold targets. However, we find out that even for new fold targets, the models generated by threading programs can contain many true contacts. The challenge is how to identify them. Results In this paper, we develop an integer linear programming model for consensus contact prediction. In contrast to the simple majority voting method assuming that all the individual servers are equally important and independent, the newly developed method evaluates their correlation by using maximum likelihood estimation and extracts independent latent servers from them by using principal component analysis. An integer linear programming method is then applied to assign a weight to each latent server to maximize the difference between true contacts and false ones. The proposed method is tested on the CASP7 data set. If the top L/5 predicted contacts are evaluated where L is the protein size, the average accuracy is 73%, which is much higher than that of any previously reported study. Moreover, if only the 15 new fold CASP7 targets are considered, our method achieves an average accuracy of 37%, which is much better than that of the majority voting method, SVM-LOMETS, SVM-SEQ, and SAM-T06. These methods demonstrate an average accuracy of 13.0%, 10.8%, 25.8% and 21.2%, respectively. Conclusion Reducing server correlation and optimally combining independent latent servers show a significant improvement over the traditional consensus methods. This approach can hopefully provide a powerful tool for protein structure refinement and prediction use.

  14. Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

    Science.gov (United States)

    Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

    2017-01-01

    Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  15. Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

    Science.gov (United States)

    Aghakouchak, Amir; Tourian, Mohammad J.

    2015-04-01

    Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

  16. Procalcitonin Improves the Glasgow Prognostic Score for Outcome Prediction in Emergency Patients with Cancer: A Cohort Study

    Directory of Open Access Journals (Sweden)

    Anna Christina Rast

    2015-01-01

    Full Text Available The Glasgow Prognostic Score (GPS is useful for predicting long-term mortality in cancer patients. Our aim was to validate the GPS in ED patients with different cancer-related urgency and investigate whether biomarkers would improve its accuracy. We followed consecutive medical patients presenting with a cancer-related medical urgency to a tertiary care hospital in Switzerland. Upon admission, we measured procalcitonin (PCT, white blood cell count, urea, 25-hydroxyvitamin D, corrected calcium, C-reactive protein, and albumin and calculated the GPS. Of 341 included patients (median age 68 years, 61% males, 81 (23.8% died within 30 days after admission. The GPS showed moderate prognostic accuracy (AUC 0.67 for mortality. Among the different biomarkers, PCT provided the highest prognostic accuracy (odds ratio 1.6 (95% confidence interval 1.3 to 1.9, P<0.001, AUC 0.69 and significantly improved the GPS to a combined AUC of 0.74 (P=0.007. Considering all investigated biomarkers, the AUC increased to 0.76 (P<0.001. The GPS performance was significantly improved by the addition of PCT and other biomarkers for risk stratification in ED cancer patients. The benefit of early risk stratification by the GPS in combination with biomarkers from different pathways should be investigated in further interventional trials.

  17. An Improved Manufacturing Approach for Discrete Silicon Microneedle Arrays with Tunable Height-Pitch Ratio

    Directory of Open Access Journals (Sweden)

    Renxin Wang

    2016-10-01

    Full Text Available Silicon microneedle arrays (MNAs have been widely studied due to their potential in various transdermal applications. However, discrete MNAs, as a preferred choice to fabricate flexible penetrating devices that could adapt curved and elastic tissue, are rarely reported. Furthermore, the reported discrete MNAs have disadvantages lying in uniformity and height-pitch ratio. Therefore, an improved technique is developed to manufacture discrete MNA with tunable height-pitch ratio, which involves KOH-dicing-KOH process. The detailed process is sketched and simulated to illustrate the formation of microneedles. Furthermore, the undercutting of convex mask in two KOH etching steps are mathematically analyzed, in order to reveal the relationship between etching depth and mask dimension. Subsequently, fabrication results demonstrate KOH-dicing-KOH process. {321} facet is figured out as the surface of octagonal pyramid microneedle. MNAs with diverse height and pitch are also presented to identify the versatility of this approach. At last, the metallization is realized via successive electroplating.

  18. Guinea pig ascorbate status predicts tetrahydrobiopterin plasma concentration and oxidation ratio in vivo.

    Science.gov (United States)

    Mortensen, Alan; Hasselholt, Stine; Tveden-Nyborg, Pernille; Lykkesfeldt, Jens

    2013-10-01

    Tetrahydrobiopterin (BH₄) is an essential co-factor of nitric oxide synthases and is easily oxidized to dihydrobiopterin (BH₂) which promotes endothelial nitric oxide synthase uncoupling and deleterious superoxide production. Vitamin C has been shown to improve endothelial function by different mechanisms, some involving BH₄. The hypothesis of the present study was that vitamin C status, in particular low levels, influences biopterin redox status in vivo. Like humans, the guinea pig lacks the ability to synthesize vitamin C and was therefore used as model. Seven day old animals (n = 10/group) were given a diet containing 100, 250, 500, 750, 1000, or 1500 ppm vitamin C until euthanasia at age 60-64 days. Blood samples were drawn from the heart and analyzed for ascorbate, dehydroascorbic acid (DHA), BH₄ and BH₂ by high-performance liquid chromatography. Plasma BH₄ levels were found to be significantly lower in animals fed 100 ppm vitamin C compared to all other groups (P < .05 or less). BH₂ levels were not significantly different between groups but the BH₂-to-BH₄ ratio was higher in the group fed 100 ppm vitamin C (P < .001 all cases). Significant positive correlations between BH4 and ascorbate and between BH₂-to-BH₄ ratio and DHA were observed (P < .0001 both cases). Likewise, BH₂-to-BH₄ ratio was negatively correlated with ascorbate (P < .0001) as was BH₄ and DHA (P < .005). In conclusion, the redox status of plasma biopterins, essentially involved in vasodilation, depends on the vitamin C status in vivo. Thus, ingestion of insufficient quantities of vitamin C not only leads to vitamin C deficiency but also to increased BH₄ oxidation which may promote endothelial dysfunction. © 2013 Elsevier Inc. All rights reserved.

  19. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu

    2017-02-16

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

  20. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

    2017-01-01

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

  1. Key financial ratios can foretell hospital closures.

    Science.gov (United States)

    Lynn, M L; Wertheim, P

    1993-11-01

    An analysis of various financial ratios sampled from open and closed hospitals shows that certain leverage, liquidity, capital efficiency, and resource availability ratios can predict hospital closure up to two years in advance of the closure with an accuracy of nearly 75 percent.

  2. The efficiency of the crude oil markets: Evidence from variance ratio tests

    Energy Technology Data Exchange (ETDEWEB)

    Charles, Amelie, E-mail: acharles@audencia.co [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier, E-mail: olivier.darne@univ-nantes.f [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

    2009-11-15

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable.

  3. The efficiency of the crude oil markets. Evidence from variance ratio tests

    International Nuclear Information System (INIS)

    Charles, Amelie; Darne, Olivier

    2009-01-01

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

  4. The efficiency of the crude oil markets. Evidence from variance ratio tests

    Energy Technology Data Exchange (ETDEWEB)

    Charles, Amelie [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

    2009-11-15

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

  5. Evaluation of waist-to-height ratio to predict 5 year cardiometabolic risk in sub-Saharan African adults.

    Science.gov (United States)

    Ware, L J; Rennie, K L; Kruger, H S; Kruger, I M; Greeff, M; Fourie, C M T; Huisman, H W; Scheepers, J D W; Uys, A S; Kruger, R; Van Rooyen, J M; Schutte, R; Schutte, A E

    2014-08-01

    Simple, low-cost central obesity measures may help identify individuals with increased cardiometabolic disease risk, although it is unclear which measures perform best in African adults. We aimed to: 1) cross-sectionally compare the accuracy of existing waist-to-height ratio (WHtR) and waist circumference (WC) thresholds to identify individuals with hypertension, pre-diabetes, or dyslipidaemia; 2) identify optimal WC and WHtR thresholds to detect CVD risk in this African population; and 3) assess which measure best predicts 5-year CVD risk. Black South Africans (577 men, 942 women, aged >30years) were recruited by random household selection from four North West Province communities. Demographic and anthropometric measures were taken. Recommended diagnostic thresholds (WC > 80 cm for women, >94 cm for men; WHtR > 0.5) were evaluated to predict blood pressure, fasting blood glucose, lipids, and glycated haemoglobin measured at baseline and 5 year follow up. Women were significantly more overweight than men at baseline (mean body mass index (BMI) women 27.3 ± 7.4 kg/m(2), men 20.9 ± 4.3 kg/m(2)); median WC women 81.9 cm (interquartile range 61-103), men 74.7 cm (63-87 cm), all P women, both WC and WHtR significantly predicted all cardiometabolic risk factors after 5 years. In men, even after adjusting WC threshold based on ROC analysis, WHtR better predicted overall 5-year risk. Neither measure predicted hypertension in men. The WHtR threshold of >0.5 appears to be more consistently supported and may provide a better predictor of future cardiometabolic risk in sub-Saharan Africa. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Advanced Materials Test Methods for Improved Life Prediction of Turbine Engine Components

    National Research Council Canada - National Science Library

    Stubbs, Jack

    2000-01-01

    Phase I final report developed under SBIR contract for Topic # AF00-149, "Durability of Turbine Engine Materials/Advanced Material Test Methods for Improved Use Prediction of Turbine Engine Components...

  7. Improved model predictive control for high voltage quality in microgrid applications

    DEFF Research Database (Denmark)

    Dragicevic, T.; Al hasheem, Mohamed; Lu, M.

    2017-01-01

    This paper proposes an improvement of the finite control set model predictive control (FCS-MPC) strategy for enhancing the voltage regulation performance of a voltage source converter (VSC) used for standalone microgrid and uninterrupted power supply (UPS) applications. The modification is based...

  8. Velocity ratio predicts outcomes in patients with low gradient severe aortic stenosis and preserved EF

    DEFF Research Database (Denmark)

    Jander, Nikolaus; Hochholzer, Willibald; Kaufmann, Beat A

    2014-01-01

    OBJECTIVE: To evaluate the usefulness of velocity ratio (VR) in patients with low gradient severe aortic stenosis (LGSAS) and preserved EF. BACKGROUND: LGSAS despite preserved EF represents a clinically challenging entity. Reliance on mean pressure gradient (MPG) may underestimate stenosis severity...... for severe stenosis. We hypothesised that VR may have conceptual advantages over MPG and AVA, predict clinical outcomes and thereby be useful in the management of patients with LGSAS. METHODS: Patients from the prospective Simvastatin and Ezetimibe in Aortic Stenosis (SEAS) study with an AVA...≤40 mm Hg and EF≥55% and asymptomatic at baseline were stratified according to VR with a cut-off value of 0.25. Outcomes were evaluated according to aortic valve-related events and cardiovascular death. RESULTS: Of 435 patients with LGSAS, 197 (45%) had VRVR≥0...

  9. Data Prediction for Public Events in Professional Domains Based on Improved RNN- LSTM

    Science.gov (United States)

    Song, Bonan; Fan, Chunxiao; Wu, Yuexin; Sun, Juanjuan

    2018-02-01

    The traditional data services of prediction for emergency or non-periodic events usually cannot generate satisfying result or fulfill the correct prediction purpose. However, these events are influenced by external causes, which mean certain a priori information of these events generally can be collected through the Internet. This paper studied the above problems and proposed an improved model—LSTM (Long Short-term Memory) dynamic prediction and a priori information sequence generation model by combining RNN-LSTM and public events a priori information. In prediction tasks, the model is qualified for determining trends, and its accuracy also is validated. This model generates a better performance and prediction results than the previous one. Using a priori information can increase the accuracy of prediction; LSTM can better adapt to the changes of time sequence; LSTM can be widely applied to the same type of prediction tasks, and other prediction tasks related to time sequence.

  10. Correlation techniques for the improvement of signal-to-noise ratio in measurements with stochastic processes

    CERN Document Server

    Reddy, V R; Reddy, T G; Reddy, P Y; Reddy, K R

    2003-01-01

    An AC modulation technique is described to convert stochastic signal variations into an amplitude variation and its retrieval through Fourier analysis. It is shown that this AC detection of signals of stochastic processes when processed through auto- and cross-correlation techniques improve the signal-to-noise ratio; the correlation techniques serve a similar purpose of frequency and phase filtering as that of phase-sensitive detection. A few model calculations applied to nuclear spectroscopy measurements such as Angular Correlations, Mossbauer spectroscopy and Pulse Height Analysis reveal considerable improvement in the sensitivity of signal detection. Experimental implementation of the technique is presented in terms of amplitude variations of harmonics representing the derivatives of normal spectra. Improved detection sensitivity to spectral variations is shown to be significant. These correlation techniques are general and can be made applicable to all the fields of particle counting where measurements ar...

  11. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  12. Methods to improve genomic prediction and GWAS using combined Holstein populations

    DEFF Research Database (Denmark)

    Li, Xiujin

    The thesis focuses on methods to improve GWAS and genomic prediction using combined Holstein populations and investigations G by E interaction. The conclusions are: 1) Prediction reliabilities for Brazilian Holsteins can be increased by adding Nordic and Frensh genotyped bulls and a large G by E...... interaction exists between populations. 2) Combining data from Chinese and Danish Holstein populations increases the power of GWAS and detects new QTL regions for milk fatty acid traits. 3) The novel multi-trait Bayesian model efficiently estimates region-specific genomic variances, covariances...

  13. The Combination of Platelet Count and Neutrophil Lymphocyte Ratio Is a Predictive Factor in Patients with Esophageal Squamous Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Ji-Feng Feng

    2014-10-01

    Full Text Available OBJECTIVE: The prognostic value of inflammation indexes in esophageal cancer was not established. In this study, therefore, both prognostic values of Glasgow prognostic score (GPS and combination of platelet count and neutrophil lymphocyte ratio (COP-NLR in patients with esophageal squamous cell carcinoma (ESCC were investigated and compared. METHODS: This retrospective study included 375 patients who underwent esophagectomy for ESCC. The cancer-specific survival (CSS was calculated by the Kaplan-Meier method, and the difference was assessed by the log-rank test. The GPS was calculated as follows: patients with elevated C-reactive protein (>10 mg/l and hypoalbuminemia (300 × 109/l and neutrophil lymphocyte ratio (>3 were assigned to COP-NLR2. Patients with one or no abnormal value were assigned to COP-NLR1 or COP-NLR0, respectively. RESULTS: The 5-year CSS in patients with GPS0, 1, and 2 was 50.0%, 27.0%, and 12.5%, respectively (P < .001. The 5-year CSS in patients with COP-NLR0, 1, and 2 was 51.8%, 27.0%, and 11.6%, respectively (P < .001. Multivariate analysis showed that both GPS (P = .003 and COP-NLR (P = .003 were significant predictors in such patients. In addition, our study demonstrated a similar hazard ratio (HR between COP-NLR and GPS (HR = 1.394 vs HR = 1.367. CONCLUSIONS: COP-NLR is an independent predictive factor in patients with ESCC. We conclude that COP-NLR predicts survival in ESCC similar to GPS.

  14. The combination of platelet count and neutrophil lymphocyte ratio is a predictive factor in patients with esophageal squamous cell carcinoma.

    Science.gov (United States)

    Feng, Ji-Feng; Huang, Ying; Chen, Qi-Xun

    2014-10-01

    The prognostic value of inflammation indexes in esophageal cancer was not established. In this study, therefore, both prognostic values of Glasgow prognostic score (GPS) and combination of platelet count and neutrophil lymphocyte ratio (COP-NLR) in patients with esophageal squamous cell carcinoma (ESCC) were investigated and compared. This retrospective study included 375 patients who underwent esophagectomy for ESCC. The cancer-specific survival (CSS) was calculated by the Kaplan-Meier method, and the difference was assessed by the log-rank test. The GPS was calculated as follows: patients with elevated C-reactive protein (> 10 mg/l) and hypoalbuminemia (l) were assigned to GPS2. Patients with one or no abnormal value were assigned to GPS1 or GPS0, respectively. The COP-NLR was calculated as follows: patients with elevated platelet count (> 300 × 10(9)/l) and neutrophil lymphocyte ratio (> 3) were assigned to COP-NLR2. Patients with one or no abnormal value were assigned to COP-NLR1 or COP-NLR0, respectively. The 5-year CSS in patients with GPS0, 1, and 2 was 50.0%, 27.0%, and 12.5%, respectively (P GPS (P = .003) and COP-NLR (P = .003) were significant predictors in such patients. In addition, our study demonstrated a similar hazard ratio (HR) between COP-NLR and GPS (HR = 1.394 vs HR = 1.367). COP-NLR is an independent predictive factor in patients with ESCC. We conclude that COP-NLR predicts survival in ESCC similar to GPS.

  15. Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.

    Science.gov (United States)

    Zhang, Hua; Kurgan, Lukasz

    2014-12-01

    Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.

  16. Prognostic durability of liver fibrosis tests and improvement in predictive performance for mortality by combining tests.

    Science.gov (United States)

    Bertrais, Sandrine; Boursier, Jérôme; Ducancelle, Alexandra; Oberti, Frédéric; Fouchard-Hubert, Isabelle; Moal, Valérie; Calès, Paul

    2017-06-01

    There is currently no recommended time interval between noninvasive fibrosis measurements for monitoring chronic liver diseases. We determined how long a single liver fibrosis evaluation may accurately predict mortality, and assessed whether combining tests improves prognostic performance. We included 1559 patients with chronic liver disease and available baseline liver stiffness measurement (LSM) by Fibroscan, aspartate aminotransferase to platelet ratio index (APRI), FIB-4, Hepascore, and FibroMeter V2G . Median follow-up was 2.8 years during which 262 (16.8%) patients died, with 115 liver-related deaths. All fibrosis tests were able to predict mortality, although APRI (and FIB-4 for liver-related mortality) showed lower overall discriminative ability than the other tests (differences in Harrell's C-index: P fibrosis, 1 year in patients with significant fibrosis, and liver disease (MELD) score testing sets. In the training set, blood tests and LSM were independent predictors of all-cause mortality. The best-fit multivariate model included age, sex, LSM, and FibroMeter V2G with C-index = 0.834 (95% confidence interval, 0.803-0.862). The prognostic model for liver-related mortality included the same covariates with C-index = 0.868 (0.831-0.902). In the testing set, the multivariate models had higher prognostic accuracy than FibroMeter V2G or LSM alone for all-cause mortality and FibroMeter V2G alone for liver-related mortality. The prognostic durability of a single baseline fibrosis evaluation depends on the liver fibrosis level. Combining LSM with a blood fibrosis test improves mortality risk assessment. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  17. Scale invariance properties of intracerebral EEG improve seizure prediction in mesial temporal lobe epilepsy.

    Directory of Open Access Journals (Sweden)

    Kais Gadhoumi

    Full Text Available Although treatment for epilepsy is available and effective for nearly 70 percent of patients, many remain in need of new therapeutic approaches. Predicting the impending seizures in these patients could significantly enhance their quality of life if the prediction performance is clinically practical. In this study, we investigate the improvement of the performance of a seizure prediction algorithm in 17 patients with mesial temporal lobe epilepsy by means of a novel measure. Scale-free dynamics of the intracerebral EEG are quantified through robust estimates of the scaling exponents--the first cumulants--derived from a wavelet leader and bootstrap based multifractal analysis. The cumulants are investigated for the discriminability between preictal and interictal epochs. The performance of our recently published patient-specific seizure prediction algorithm is then out-of-sample tested on long-lasting data using combinations of cumulants and state similarity measures previously introduced. By using the first cumulant in combination with state similarity measures, up to 13 of 17 patients had seizures predicted above chance with clinically practical levels of sensitivity (80.5% and specificity (25.1% of total time under warning for prediction horizons above 25 min. These results indicate that the scale-free dynamics of the preictal state are different from those of the interictal state. Quantifiers of these dynamics may carry a predictive power that can be used to improve seizure prediction performance.

  18. Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

    Science.gov (United States)

    Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

    2017-07-01

    To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

  19. Prediction of Microcystis Blooms Based on TN:TP Ratio and Lake Origin

    Directory of Open Access Journals (Sweden)

    Yoshimasa Amano

    2008-01-01

    Full Text Available We evaluated the relationship between TN:TP ratio and Microcystis growth via a database that includes worldwide lakes based on four types of lake origin (dammed, tectonic, coastal, and volcanic lakes. We used microcosm and mesocosm for the nutrient elution tests with lake water and four kinds of sediment (nontreated, MgO sprinkling treated, dissolved air flotation [DAF] treated, and combined treated sediment in order to control TN:TP ratio and to suppress Microcystis growth. Microcystis growth was related to TN:TP ratio, with the maximum value at an optimum TN:TP ratio and the minimum values when the TN:TP ratios reached to 0 or ∞. The kurtosis of the distribution curve varied with the type of lake origin; the lowest kurtosis was found in dammed lakes, while the highest was found in volcanic lakes. The lake trophic state could affect the change in the kurtosis, providing much lower kurtosis at eutrophic lakes (dammed lakes than that at oligotrophic lakes (volcanic lakes. The relationship between TN:TP ratio and Microcystis growth could be explained by the nutrient elution tests under controlled TN:TP ratios through the various sediment treatments. A significant suppression of Microcystis growth of 70% could be achieved when the TN:TP ratios exceeded 21. Lake origin could be regarded as an index including morphological and geographical factors, and controlling the trophic state in lakes. The origin rather than trophic state for lakes could be considered as an important factor of TN:TP influences on Microcystis growth.

  20. Detecting isotopic ratio outliers

    Science.gov (United States)

    Bayne, C. K.; Smith, D. H.

    An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers.

  1. Detecting isotopic ratio outliers

    International Nuclear Information System (INIS)

    Bayne, C.K.; Smith, D.H.

    1986-01-01

    An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers

  2. Strain ratio ultrasound elastography increases the accuracy of colour-Doppler ultrasound in the evaluation of Thy-3 nodules. A bi-centre university experience.

    Science.gov (United States)

    Cantisani, Vito; Maceroni, Piero; D'Andrea, Vito; Patrizi, Gregorio; Di Segni, Mattia; De Vito, Corrado; Grazhdani, Hektor; Isidori, Andrea M; Giannetta, Elisa; Redler, Adriano; Frattaroli, Fabrizio; Giacomelli, Laura; Di Rocco, Giorgio; Catalano, Carlo; D'Ambrosio, Ferdinando

    2016-05-01

    To assess whether ultrasound elastography (USE) with strain ratio increases diagnostic accuracy of Doppler ultrasound in further characterisation of cytologically Thy3 thyroid nodules. In two different university diagnostic centres, 315 patients with indeterminate cytology (Thy3) in thyroid nodules aspirates were prospectively evaluated with Doppler ultrasound and strain ratio USE before surgery. Ultrasonographic features were analysed separately and together as ultrasound score, to assess sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Receiver operating characteristic (ROC) curves to identify optimal cut-off value of the strain ratio were also provided. Diagnosis on a surgical specimen was considered the standard of reference. Higher strain ratio values were found in malignant nodules, with an optimum strain ratio cut-off of 2.09 at ROC analysis. USE with strain ratio showed 90.6% sensitivity, 93% specificity, 82.8% PPV, 96.4% NPV, while US score yielded a sensitivity of 52.9%, specificity of 84.3%, PPV 55.6% and NPV 82.9%. The diagnostic gain with strain ratio was statistically significant as proved by ROC areas, which was 0.9182 for strain ratio and 0.6864 for US score. USE with strain ratio should be considered a useful additional tool to colour-Doppler US, since it improves characterisation of thyroid nodules with indeterminate cytology. • Strain ratio measurements improve differentiation of thyroid nodules with indeterminate cytology • Elastography with strain ratio is more reliable than ultrasound features and ultrasound score • Strain ratio may help to better select patients with Thy 3 nodules candidate for surgery.

  3. Development of equations to predict the influence of floor space on average daily gain, average daily feed intake and gain : feed ratio of finishing pigs.

    Science.gov (United States)

    Flohr, J R; Dritz, S S; Tokach, M D; Woodworth, J C; DeRouchey, J M; Goodband, R D

    2018-05-01

    Floor space allowance for pigs has substantial effects on pig growth and welfare. Data from 30 papers examining the influence of floor space allowance on the growth of finishing pigs was used in a meta-analysis to develop alternative prediction equations for average daily gain (ADG), average daily feed intake (ADFI) and gain : feed ratio (G : F). Treatment means were compiled in a database that contained 30 papers for ADG and 28 papers for ADFI and G : F. The predictor variables evaluated were floor space (m2/pig), k (floor space/final BW0.67), Initial BW, Final BW, feed space (pigs per feeder hole), water space (pigs per waterer), group size (pigs per pen), gender, floor type and study length (d). Multivariable general linear mixed model regression equations were used. Floor space treatments within each experiment were the observational and experimental unit. The optimum equations to predict ADG, ADFI and G : F were: ADG, g=337.57+(16 468×k)-(237 350×k 2)-(3.1209×initial BW (kg))+(2.569×final BW (kg))+(71.6918×k×initial BW (kg)); ADFI, g=833.41+(24 785×k)-(388 998×k 2)-(3.0027×initial BW (kg))+(11.246×final BW (kg))+(187.61×k×initial BW (kg)); G : F=predicted ADG/predicted ADFI. Overall, the meta-analysis indicates that BW is an important predictor of ADG and ADFI even after computing the constant coefficient k, which utilizes final BW in its calculation. This suggests including initial and final BW improves the prediction over using k as a predictor alone. In addition, the analysis also indicated that G : F of finishing pigs is influenced by floor space allowance, whereas individual studies have concluded variable results.

  4. Combining Spot Sign and Intracerebral Hemorrhage Score to Estimate Functional Outcome: Analysis From the PREDICT Cohort.

    Science.gov (United States)

    Schneider, Hauke; Huynh, Thien J; Demchuk, Andrew M; Dowlatshahi, Dar; Rodriguez-Luna, David; Silva, Yolanda; Aviv, Richard; Dzialowski, Imanuel

    2018-06-01

    The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0-3 versus 4-6). Performance of (1) the ICH score and (2) the spot sign ICH score-a scoring scale combining ICH score and spot sign number-was tested. Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2-4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1-7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2-17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). In the PREDICT cohort, a prognostic score adding the computed tomographic angiography-based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score. © 2018 American Heart Association, Inc.

  5. Prediction of saturation using the carbon/oxygen log

    Energy Technology Data Exchange (ETDEWEB)

    Horner, S.C.; Sanyal, S.K.

    1984-09-01

    This project investigates the nature of Dresser-Atlas Carbon/Oxygen Log gamma ray spectra. It presents an attempt to improve the signal-to-noise ratio of the C/O and Si/Ca parameters used by Dresser-Atlas to determine oil saturation. Two techniques were developed to subtract the Compton background from the spectral data. Neither technique significantly improves the accuracy of the cased-hole prediction of oil saturation. However, it has been shown that it is possible to develop a satisfactory correlation for oil saturation on a well-by-well basis. This correlation can then be used to generate oil-in-place from the C/O and Si/Ca ratios. 17 references.

  6. Postoperative Elevation of the Neutrophil: Lymphocyte Ratio Predicts Complications Following Esophageal Resection.

    Science.gov (United States)

    Vulliamy, Paul; McCluney, Simon; Mukherjee, Samrat; Ashby, Luke; Amalesh, Thangadorai

    2016-06-01

    Complications following esophagectomy are a significant source of morbidity. The aim of this study was to investigate the utility of the neutrophil:lymphocyte ratio (NLR) in the early identification of complications following esophagectomy, as compared to other routinely available parameters. We performed a retrospective cohort study of patients undergoing Ivor-Lewis esophagectomy at a single centre. Baseline characteristics and complications occurring within the first 30 days of surgery were recorded. White blood cell counts and C-reactive protein (CRP) levels immediately following surgery (day 0) and over the subsequent three postoperative days were analysed. Sixty-five patients were included, of whom 29 (45 %) developed complications. The median NLR was similar among patients with and without a complicated recovery on day 0 (12.7 vs 13.6, p = 0.70) and day 1 (10.0 vs 9.3, p = 0.29). Patients who subsequently developed complications had a higher NLR on day 2 (11.8 vs 7.5, p 8.3 on day 2 had a sensitivity of 93 % and a specificity of 72 % for predicting complications. The NLR is a simple and routinely available parameter which has a high sensitivity in the early detection of complications following esophagectomy.

  7. Respiratory sinus arrhythmia reactivity to a sad film predicts depression symptom improvement and symptomatic trajectory.

    Science.gov (United States)

    Panaite, Vanessa; Hindash, Alexandra Cowden; Bylsma, Lauren M; Small, Brent J; Salomon, Kristen; Rottenberg, Jonathan

    2016-01-01

    Respiratory sinus arrhythmia (RSA) reactivity, an index of cardiac vagal tone, has been linked to self-regulation and the severity and course of depression (Rottenberg, 2007). Although initial data supports the proposition that RSA withdrawal during a sad film is a specific predictor of depression course (Fraguas, 2007; Rottenberg, 2005), the robustness and specificity of this finding are unclear. To provide a stronger test, RSA reactivity to three emotion films (happy, sad, fear) and to a more robust stressor, a speech task, were examined in currently depressed individuals (n=37), who were assessed for their degree of symptomatic improvement over 30weeks. Robust RSA reactivity to the sad film uniquely predicted overall symptom improvement over 30weeks. RSA reactivity to both sad and stressful stimuli predicted the speed and maintenance of symptomatic improvement. The current analyses provide the most robust support to date that RSA withdrawal to sad stimuli (but not stressful) has specificity in predicting the overall symptomatic improvement. In contrast, RSA reactivity to negative stimuli (both sad and stressful) predicted the trajectory of depression course. Patients' engagement with sad stimuli may be an important sign to attend to in therapeutic settings. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Catchment coevolution: A useful framework for improving predictions of hydrological change?

    Science.gov (United States)

    Troch, Peter A.

    2017-04-01

    The notion that landscape features have co-evolved over time is well known in the Earth sciences. Hydrologists have recently called for a more rigorous connection between emerging spatial patterns of landscape features and the hydrological response of catchments, and have termed this concept catchment coevolution. In this presentation we present a general framework of catchment coevolution that could improve predictions of hydrologic change. We first present empirical evidence of the interaction and feedback of landscape evolution and changes in hydrological response. From this review it is clear that the independent drivers of catchment coevolution are climate, geology, and tectonics. We identify common currency that allows comparing the levels of activity of these independent drivers, such that, at least conceptually, we can quantify the rate of evolution or aging. Knowing the hydrologic age of a catchment by itself is not very meaningful without linking age to hydrologic response. Two avenues of investigation have been used to understand the relationship between (differences in) age and hydrological response: (i) one that is based on relating present landscape features to runoff processes that are hypothesized to be responsible for the current fingerprints in the landscape; and (ii) one that takes advantage of an experimental design known as space-for-time substitution. Both methods have yielded significant insights in the hydrologic response of landscapes with different histories. If we want to make accurate predictions of hydrologic change, we will also need to be able to predict how the catchment will further coevolve in association with changes in the activity levels of the drivers (e.g., climate). There is ample evidence in the literature that suggests that whole-system prediction of catchment coevolution is, at least in principle, plausible. With this imperative we outline a research agenda that implements the concepts of catchment coevolution for building

  9. The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.

    Science.gov (United States)

    Thiels, Cornelius A; Yu, Denny; Abdelrahman, Amro M; Habermann, Elizabeth B; Hallbeck, Susan; Pasupathy, Kalyan S; Bingener, Juliane

    2017-01-01

    Reliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration. We reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842). A total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R 2  = 0.001) compared to the patient factors model (R 2  = 0.08). The model remained predictive on external validation (R 2  = 0.14).The addition of surgeon as a variable in the institutional model further improved predictive ability of the model (R 2  = 0.18). The use of routinely available pre-operative patient factors improves the prediction of operative

  10. Adjusting the Stems Regional Forest Growth Model to Improve Local Predictions

    Science.gov (United States)

    W. Brad Smith

    1983-01-01

    A simple procedure using double sampling is described for adjusting growth in the STEMS regional forest growth model to compensate for subregional variations. Predictive accuracy of the STEMS model (a distance-independent, individual tree growth model for Lake States forests) was improved by using this procedure

  11. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

    DEFF Research Database (Denmark)

    Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.

    2012-01-01

    Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing...... methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used nc...

  12. Clinical value of spleen acoustic radiation force impulse, aspartate aminotransferase-to-platelet ratio index, and aspartate aminotransferase/alanine aminotransferase ratio in predicting esophageal varices in patients with liver cirrhosis

    Directory of Open Access Journals (Sweden)

    ZHANG Dakun

    2018-03-01

    Full Text Available ObjectiveTo investigate the spleen stiffness of patients with chronic hepatitis and liver cirrhosis by spleen acoustic radiation force impulse (ARFI, aspartate aminotransferase-to-platelet ratio index (APRI, and aspartate aminotransferase/alanine aminotransferase ratio (AAR, as well as the clinical value of these three noninvasive techniques in predicting esophageal varices (EV in patients with liver cirrhosis. MethodsA total of 247 patients with chronic hepatitis and liver cirrhosis were enrolled, and ARFI was used to measure real-time spleen stiffness. APRI and AAR were calculated. Gastroscopy was performed within one week before and after measurement to clarify the degree of EV. With the results of gastroscopy as the gold standard, the receiver operating characteristic (ROC curve was used to compare the clinical value of spleen ARFI value, APRI, and AAR in the diagnosis of EV in patients with liver cirrhosis. The t-test was used for comparison of continuous data between two groups. ResultsThere were significant differences between the EV group (n=169 and the non-EV group (n=78 in spleen ARFI stiffness (3.64±0.53 m/s vs 2.97±0.65 m/s, t=-7.93, P<0.001, APRI (0.87±091 vs 0.52±0.80, t=-2.90, P=0.004, and AAR (1.54±0.67 vs 1.29±0.55, t=-2.93, P=0.004. Spleen ARFI, APRI, and AAR had an area under the ROC curve of 0.80, 0.72, and 0.63, respectively, in predicting EV in patients with liver cirrhosis, there was a significant difference between spleen ARFI stiffness and AAR (P=0.005, while there was no significant difference between spleen ARFI stiffness and APRI (P=0.10. ConclusionARFI is a real-time ultrasound elastography technique, and compared with APRI and AAR, spleen stiffness measured by ARFI can predict EV in patients with chronic hepatitis and liver cirrhosis more accurately and noninvasively and thus holds promise for clinical application.

  13. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

    Science.gov (United States)

    Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

    2017-11-24

    Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

  14. Predictive modelling of interventions to improve iodine intake in New Zealand.

    Science.gov (United States)

    Schiess, Sonja; Cressey, Peter J; Thomson, Barbara M

    2012-10-01

    The potential effects of four interventions to improve iodine intakes of six New Zealand population groups are assessed. A model was developed to estimate iodine intake when (i) bread is manufactured with or without iodized salt, (ii) recommended foods are consumed to augment iodine intake, (iii) iodine supplementation as recommended for pregnant women is taken and (iv) the level of iodization for use in bread manufacture is doubled from 25-65 mg to 100 mg iodine/kg salt. New Zealanders have low and decreasing iodine intakes and low iodine status. Predictive modelling is a useful tool to assess the likely impact, and potential risk, of nutrition interventions. Food consumption information was sourced from 24 h diet recall records for 4576 New Zealanders aged over 5 years. Most consumers (73-100 %) are predicted to achieve an adequate iodine intake when salt iodized at 25-65 mg iodine/kg salt is used in bread manufacture, except in pregnant females of whom 37 % are likely to meet the estimated average requirement. Current dietary advice to achieve estimated average requirements is challenging for some consumers. Pregnant women are predicted to achieve adequate but not excessive iodine intakes when 150 μg of supplemental iodine is taken daily, assuming iodized salt in bread. The manufacture of bread with iodized salt and supplemental iodine for pregnant women are predicted to be effective interventions to lift iodine intakes in New Zealand. Current estimations of iodine intake will be improved with information on discretionary salt and supplemental iodine usage.

  15. Elevated Neutrophil Lymphocyte Ratio in Recurrent Optic Neuritis

    Directory of Open Access Journals (Sweden)

    Hande Guclu

    2015-01-01

    Full Text Available Purpose. To demonstrate the relation between optic neuritis (ON and systemic inflammation markers as neutrophil lymphocyte ratio (N/L ratio, platelet count, mean platelet volume (MPV, and red cell distribution width (RDW and furthermore to evaluate the utilization of these markers to predict the frequency of the ON episodes. Methods. Forty-two patients with acute ON and forty healthy subjects were enrolled into the study. The medical records were reviewed for age, sex, hemoglobin (Hb, Haematocrit (Htc, RDW, platelet count, MPV, white blood cell count (WBC, neutrophil and lymphocyte count, and neutrophil lymphocyte ratio (N/L ratio. Results. The mean N/L ratio, platelet counts, and RDW were significantly higher in ON group (p=0.000, p=0.048, and p=0.002. There was a significant relation between N/L ratio and number of episodes (r=0.492, p=0.001. There was a statistically significant difference for MPV between one episode group and recurrent ON group (p=0.035. Conclusions. Simple and inexpensive laboratory methods could help us show systemic inflammation and monitor ON patients. Higher N/L ratio can be a useful marker for predicting recurrent attacks.

  16. Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

    Science.gov (United States)

    Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

    2015-12-01

    Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be

  17. Factors predicting visual improvement post pars plana vitrectomy for proliferative diabetic retinopathy

    Directory of Open Access Journals (Sweden)

    Evelyn Tai Li Min

    2017-08-01

    Full Text Available AIM: To identify factors predicting visual improvement post vitrectomy for sequelae of proliferative diabetic retinopathy(PDR.METHODS: This was a retrospective analysis of pars plana vitrectomy indicated for sequelae of PDR from Jan. to Dec. 2014 in Hospital Sultanah Bahiyah, Alor Star, Kedah, Malaysia. Data collected included patient demographics, baseline visual acuity(VAand post-operative logMAR best corrected VA at 1y. Data analysis was performed with IBM SPSS Statistics Version 22.0. RESULTS: A total of 103 patients were included. The mean age was 51.2y. On multivariable analysis, each pre-operative positive deviation of 1 logMAR from a baseline VA of 0 logMAR was associated with a post-operative improvement of 0.859 logMAR(P0.001. Likewise, an attached macula pre-operatively was associated with a 0.374(P=0.003logMAR improvement post vitrectomy. Absence of iris neovascularisation and absence of post-operative complications were associated with a post vitrectomy improvement in logMAR by 1.126(P=0.001and 0.377(P=0.005respectively. Absence of long-acting intraocular tamponade was associated with a 0.302(P=0.010improvement of logMAR post vitrectomy.CONCLUSION: Factors associated with visual improvement after vitrectomy are poor pre-operative VA, an attached macula, absence of iris neovascularisation, absence of post-operative complications and abstaining from use of long-acting intraocular tamponade. A thorough understanding of the factors predicting visual improvement will facilitate decision-making in vitreoretinal surgery.

  18. A Model Suggestion to Predict Leverage Ratio for Construction Projects

    Directory of Open Access Journals (Sweden)

    Özlem Tüz

    2013-12-01

    Full Text Available Due to the nature, construction is an industry with high uncertainty and risk. Construction industry carries high leverage ratios. Firms with low equities work in big projects through progress payment system, but in this case, even a small negative in the planned cash flows constitute a major risk for the company.The use of leverage, with a small investment to achieve profit targets large-scale, high-profit, but also brings a high risk with it. Investors may lose all or the portion of the money. In this study, monitoring and measuring of the leverage ratio because of the displacement in cash inflows of construction projects which uses high leverage and low cash to do business in the sector is targeted. Cash need because of drifting the cash inflows may be seen due to the model. Work should be done in the early stages of the project with little capital but in the later stages, rapidly growing capital need arises.The values obtained from the model may be used to supply the capital held in the right time by anticipating the risks because of the delay in cashflow of construction projects which uses high leverage ratio.

  19. Neutrophil to lymphocyte ratio as a reliable marker to predict insulin resistance and fibrosis stage in chronic hepatitis C virus infection.

    Science.gov (United States)

    Abdel-Razik, Ahmed; Mousa, Nasser; Besheer, Tarek A; Eissa, Mohamed; Elhelaly, Rania; Arafa, Mohammad; El-Wakeel, Niveen; Eldars, Waleed

    2015-12-01

    Hepatitis C virus (HCV) is one of the most noxious infectious diseases. Chronic hepatitis C (CHC) had biochemical evidence of insulin resistance (IR). The neutrophil/lymphocyte ratio (NLR) integrates information on the inflammatory milieu and physiological stress. We aimed to investigate the clinical utility of NLR to predict the presence of IR and fibrosis in CHCvirus infection. The study included 234 CHC patients and 50 healthy controls. The CHC group was divided into two subgroups ; CHC with HOMA-IR>3 and CHC with HOMA-IR≤3. Liver biopsy, homeostasis model assessment-IR (HOMA-IR), neutrophil and lymphocyte counts were recorded ; and NLR was calculated. Proinflammatory cytokines [tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6)] were measured by an enzyme-linked immunosorbent assay. Patients with HOMA-IR>3 had a higher NLR compared with patients with HOMA-IR≤3 [2.61±0.95 and 1.92±0.86, respectively, PC-reactive protein, TNF-α and IL-6 cytokines ; P3 and advanced fibrosis. This ratio can be used as a novel noninvasive marker to predict IR and advanced disease. © Acta Gastro-Enterologica Belgica.

  20. Power Efficiency Improvements through Peak-to-Average Power Ratio Reduction and Power Amplifier Linearization

    Directory of Open Access Journals (Sweden)

    Zhou G Tong

    2007-01-01

    Full Text Available Many modern communication signal formats, such as orthogonal frequency-division multiplexing (OFDM and code-division multiple access (CDMA, have high peak-to-average power ratios (PARs. A signal with a high PAR not only is vulnerable in the presence of nonlinear components such as power amplifiers (PAs, but also leads to low transmission power efficiency. Selected mapping (SLM and clipping are well-known PAR reduction techniques. We propose to combine SLM with threshold clipping and digital baseband predistortion to improve the overall efficiency of the transmission system. Testbed experiments demonstrate the effectiveness of the proposed approach.

  1. Cutoff value of pharyngeal residue in prognosis prediction after neuromuscular electrical stimulation therapy for Dysphagia in subacute stroke patients.

    Science.gov (United States)

    Park, Jeong Mee; Yong, Sang Yeol; Kim, Ji Hyun; Jung, Hong Sun; Chang, Sei Jin; Kim, Ki Young; Kim, Hee

    2014-10-01

    To determine the cutoff value of the pharyngeal residue for predicting reduction of aspiration, by measuring the residue of valleculae and pyriformis sinuses through videofluoroscopic swallowing studies (VFSS) after treatment with neuromuscular electrical stimulator (VitalStim) in stroke patients with dysphagia. VFSS was conducted on first-time stroke patients before and after the VitalStim therapy. The results were analyzed for comparison of the pharyngeal residue in the improved group and the non-improved group. A total of 59 patients concluded the test, in which 42 patients improved well enough to change the dietary methods while 17 did not improve sufficiently. Remnant area to total area (R/T) ratios of the valleculae before treatment in the improved group were 0.120, 0.177, and 0.101 for solid, soft, and liquid foods, respectively, whereas the ratios for the non-improved group were 0.365, 0.396, and 0.281, respectively. The ratios of the pyriformis sinuses were 0.126, 0.159, and 0.121 for the improved group and 0.315, 0.338, and 0.244 for the non-improved group. The R/T ratios of valleculae and pyriformis sinus were significantly lower in the improved group than the non-improved group in all food types before treatment. The R/T ratio cutoff values were 0.267, 0.250, and 0.185 at valleculae and 0.228, 0.218, and 0.185 at pyriformis sinuses. In dysphagia after stroke, less pharyngeal residue before treatment serves as a factor for predicting greater improvement after VitalStim treatment.

  2. Detecting isotopic ratio outliers

    International Nuclear Information System (INIS)

    Bayne, C.K.; Smith, D.H.

    1985-01-01

    An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers. 6 refs., 3 figs., 3 tabs

  3. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2015-01-01

    Full Text Available To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS model based on an outliers detection method is proposed in this paper. An improved radial basis function network (RBFN is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM is applied to detect the outliers. After outliers are removed away, a more robust dynamic PLS model is obtained. In addition, an improved generalized predictive control (GPC with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch. The results of two simulations demonstrate the effectiveness of proposed method.

  4. Whey protein improves HDL/non-HDL ratio and body weight gain in rats subjected to the resistance exercise

    Directory of Open Access Journals (Sweden)

    Kely Raspante Teixeira

    2012-12-01

    Full Text Available The aim of this study was to evaluate the effects of resistance exercise, such as weight-lifting (WL on the biochemical parameters of lipid metabolism and cardiovascular disease risk in the rats fed casein (control or whey protein (WP diets. Thirty-two male Fisher rats were randomly assigned to sedentary or exercise-trained groups and were fed control or WP diets. The WL program consisted of inducing the animals to perform the sets of jumps with weights attached to the chest. After seven weeks, arteriovenous blood samples were collected for analysis. The WL or WP ingestion were able to improve the lipid profile, reducing the TC and non-HDL cholesterol concentrations, but only WP treatment significantly increased the serum HDL concentrations, thereby also affecting the TC/HDL and HDL/non-HDL ratios. However, WL plus WP was more effective in improving the HDL/non-HDL ratio than the exercise or WP ingestion alone and the body weight gain than exercise without WP ingestion.

  5. A study on improvement of analytical prediction model for spacer grid pressure loss coefficients

    International Nuclear Information System (INIS)

    Lim, Jonh Seon

    2002-02-01

    Nuclear fuel assemblies used in the nuclear power plants consist of the nuclear fuel rods, the control rod guide tubes, an instrument guide tube, spacer grids,a bottom nozzle, a top nozzle. The spacer grid is the most important component of the fuel assembly components for thermal hydraulic and mechanical design and analyses. The spacer grids fixed with the guide tubes support the fuel rods and have the very important role to activate thermal energy transfer by the coolant mixing caused to the turbulent flow and crossflow in the subchannels. In this paper, the analytical spacer grid pressure loss prediction model has been studied and improved by considering the test section wall to spacer grid gap pressure loss independently and applying the appropriate friction drag coefficient to predict pressure loss more accurately at the low Reynolds number region. The improved analytical model has been verified based on the hydraulic pressure drop test results for the spacer grids of three types with 5x5, 16x16, 17x17 arrays, respectively. The pressure loss coefficients predicted by the improved analytical model are coincident with those test results within ±12%. This result shows that the improved analytical model can be used for research and design change of the nuclear fuel assembly

  6. Improved failure prediction in forming simulations through pre-strain mapping

    Science.gov (United States)

    Upadhya, Siddharth; Staupendahl, Daniel; Heuse, Martin; Tekkaya, A. Erman

    2018-05-01

    The sensitivity of sheared edges of advanced high strength steel (AHSS) sheets to cracking during subsequent forming operations and the difficulty to predict this failure with any degree of accuracy using conventionally used FLC based failure criteria is a major problem plaguing the manufacturing industry. A possible method that allows for an accurate prediction of edge cracks is the simulation of the shearing operation and carryover of this model into a subsequent forming simulation. But even with an efficient combination of a solid element shearing operation and a shell element forming simulation, the need for a fine mesh, and the resulting high computation time makes this approach not viable from an industry point of view. The crack sensitivity of sheared edges is due to work hardening in the shear-affected zone (SAZ). A method to predict plastic strains induced by the shearing process is to measure the hardness after shearing and calculate the ultimate tensile strength as well as the flow stress. In combination with the flow curve, the relevant strain data can be obtained. To eliminate the time-intensive shearing simulation necessary to obtain the strain data in the SAZ, a new pre-strain mapping approach is proposed. The pre-strains to be mapped are, hereby, determined from hardness values obtained in the proximity of the sheared edge. To investigate the performance of this approach the ISO/TS 16630 hole expansion test was simulated with shell elements for different materials, whereby the pre-strains were mapped onto the edge of the hole. The hole expansion ratios obtained from such pre-strain mapped simulations are in close agreement with the experimental results. Furthermore, the simulations can be carried out with no increase in computation time, making this an interesting and viable solution for predicting edge failure due to shearing.

  7. 2D:4D digit ratio predicts delay of gratification in preschoolers.

    Directory of Open Access Journals (Sweden)

    Sergio Da Silva

    Full Text Available We replicate the Stanford marshmallow experiment with a sample of 141 preschoolers and find a correlation between lack of self-control and 2D:4D digit ratio. Children with low 2D:4D digit ratio are less likely to delay gratification. Low 2D:4D digit ratio may indicate high fetal testosterone. If this hypothesis is true, our finding means high fetal testosterone children are less likely to delay gratification.

  8. Optic nerve magnetisation transfer ratio after acute optic neuritis predicts axonal and visual outcomes.

    Directory of Open Access Journals (Sweden)

    Yejun Wang

    Full Text Available Magnetisation transfer ratio (MTR can reveal the degree of proton exchange between free water and macromolecules and was suggested to be pathological informative. We aimed to investigate changes in optic nerve MTR over 12 months following acute optic neuritis (ON and to determine whether MTR measurements can predict clinical and paraclinical outcomes at 6 and 12 months. Thirty-seven patients with acute ON were studied within 2 weeks of presentation and at 1, 3, 6 and 12 months. Assessments included optic nerve MTR, retinal nerve fibre layer (RNFL thickness, multifocal visual evoked potential (mfVEP amplitude and latency and high (100% and low (2.5% contrast letter acuity. Eleven healthy controls were scanned twice four weeks apart for comparison with patients. Patient unaffected optic nerve MTR did not significantly differ from controls at any time-point. Compared to the unaffected nerve, affected optic nerve MTR was significantly reduced at 3 months (mean percentage interocular difference = -9.24%, p = 0.01, 6 months (mean = -12.48%, p<0.0001 and 12 months (mean = -7.61%, p = 0.003. Greater reduction in MTR at 3 months in patients was associated with subsequent loss of high contrast letter acuity at 6 (ρ = 0.60, p = 0.0003 and 12 (ρ = 0.44, p = 0.009 months, low contrast letter acuity at 6 (ρ = 0.35, p = 0.047 months, and RNFL thinning at 12 (ρ = 0.35, p = 0.044 months. Stratification of individual patient MTR time courses based on flux over 12 months (stable, putative remyelination and putative degeneration predicted RNFL thinning at 12 months (F(2,32 = 3.59, p = 0.02. In conclusion, these findings indicate that MTR flux after acute ON is predictive of axonal degeneration and visual disability outcomes.

  9. Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

    Science.gov (United States)

    Dedes, I.; Dudek, J.

    2018-03-01

    We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

  10. Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

    Directory of Open Access Journals (Sweden)

    Douglas Halamay

    2014-09-01

    Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

  11. Improving Predictive Modeling in Pediatric Drug Development: Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Slikker, William; Young, John F.; Corley, Rick A.; Dorman, David C.; Conolly, Rory B.; Knudsen, Thomas; Erstad, Brian L.; Luecke, Richard H.; Faustman, Elaine M.; Timchalk, Chuck; Mattison, Donald R.

    2005-07-26

    A workshop was conducted on November 18?19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adultlike in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

  12. Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

    Science.gov (United States)

    Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

    2013-05-01

    Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

  13. An improved FT-TIMS method of measuring uranium isotope ratios in the uranium-bearing particles

    International Nuclear Information System (INIS)

    Chen, Yan; Wang, Fan; Zhao, Yong-Gang; Li, Li-Li; Zhang, Yan; Shen, Yan; Chang, Zhi-Yuan; Guo, Shi-Lun; Wang, Xiao-Ming; Cui, Jian-Yong; Liu, Yu-Ang

    2015-01-01

    An improved method of Fission Track technique combined with Thermal Ionization Mass Spectrometry (FT-TIMS) was established in order to determine isotope ratio of uranium-bearing particle. Working standard of uranium oxide particles with a defined diameter and isotopic composition were prepared and used to review the method. Results showed an excellent agreement with certified values. The developed method was used to analyze isotope ratio of single uranium-bearing particle in swipe samples successfully. The analysis results of uranium-bearing particles in swipe samples accorded with the operation history of the origin. - Highlights: • The developed method was successfully applied in the analysis of real swipe sample. • Uranium-bearing particles were confined in the middle of track detector. • The fission tracks of collodion film and PC film could be confirmed each other. • The thickness of collodion film should be no more than about 60 μm. • The method could avoid losing uranium-bearing particles in the etching step.

  14. Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening.

    Science.gov (United States)

    Ain, Qurrat Ul; Aleksandrova, Antoniya; Roessler, Florian D; Ballester, Pedro J

    2015-01-01

    Docking tools to predict whether and how a small molecule binds to a target can be applied if a structural model of such target is available. The reliability of docking depends, however, on the accuracy of the adopted scoring function (SF). Despite intense research over the years, improving the accuracy of SFs for structure-based binding affinity prediction or virtual screening has proven to be a challenging task for any class of method. New SFs based on modern machine-learning regression models, which do not impose a predetermined functional form and thus are able to exploit effectively much larger amounts of experimental data, have recently been introduced. These machine-learning SFs have been shown to outperform a wide range of classical SFs at both binding affinity prediction and virtual screening. The emerging picture from these studies is that the classical approach of using linear regression with a small number of expert-selected structural features can be strongly improved by a machine-learning approach based on nonlinear regression allied with comprehensive data-driven feature selection. Furthermore, the performance of classical SFs does not grow with larger training datasets and hence this performance gap is expected to widen as more training data becomes available in the future. Other topics covered in this review include predicting the reliability of a SF on a particular target class, generating synthetic data to improve predictive performance and modeling guidelines for SF development. WIREs Comput Mol Sci 2015, 5:405-424. doi: 10.1002/wcms.1225 For further resources related to this article, please visit the WIREs website.

  15. Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors

    International Nuclear Information System (INIS)

    Jain, Ankit; Alam, Muhammad Ashraful

    2014-01-01

    A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (SNR) and the limit-of-detection (LOD) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate SNR and establish LOD of critical-point flexure sensors. We find that a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved SNR and LOD. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.

  16. Potential of right to left ventricular volume ratio measured on chest CT for the prediction of pulmonary hypertension: correlation with pulmonary arterial systolic pressure estimated by echocardiography

    International Nuclear Information System (INIS)

    Lee, Heon; Kim, Seok Yeon; Lee, Soo Jeong; Kim, Jae Kyun; Reddy, Ryan P.; Schoepf, U.J.

    2012-01-01

    To investigate the correlation of right ventricular (RV) to left ventricular (LV) volume ratio measured by chest CT with pulmonary arterial systolic pressure (PASP) estimated by echocardiography. 104 patients (72.47 ± 13.64 years; 39 male) who had undergone chest CT and echocardiography were divided into two groups (hypertensive and normotensive) based upon an echocardiography-derived PASP of 25 mmHg. RV to LV volume ratios (RV V /LV V ) were calculated. RV V /LV V was then correlated with PASP using regression analysis. The Area Under the Curve (AUC) for predicting pulmonary hypertension on chest CT was calculated. In the hypertensive group, the mean PASP was 46.29 ± 14.42 mmHg (29-98 mmHg) and there was strong correlation between the RV V /LV V and PASP (R = 0.82, p V /LV V were 0.990 and 0.892. RV V /LV V was 1.01 ± 0.44 (0.51-2.77) in the hypertensive and 0.72 ± 0.14 (0.52-1.11) in the normotensive group (P V /LV V , sensitivity and specificity for predicting pulmonary hypertension over 40 mmHg were 79.5 % and 90 %, respectively. The AUC for predicting pulmonary hypertension was 0.87 RV/LV volume ratios on chest CT correlate well with PASP estimated by echocardiography and can be used to predict pulmonary hypertension over 40 mmHg with high sensitivity and specificity. (orig.)

  17. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

    Directory of Open Access Journals (Sweden)

    Assaf Gottlieb

    2017-11-01

    Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

  18. Reliable B cell epitope predictions: impacts of method development and improved benchmarking

    DEFF Research Database (Denmark)

    Kringelum, Jens Vindahl; Lundegaard, Claus; Lund, Ole

    2012-01-01

    biomedical applications such as; rational vaccine design, development of disease diagnostics and immunotherapeutics. However, experimental mapping of epitopes is resource intensive making in silico methods an appealing complementary approach. To date, the reported performance of methods for in silico mapping...... evaluation data set improved from 0.712 to 0.727. Our results thus demonstrate that given proper benchmark definitions, B-cell epitope prediction methods achieve highly significant predictive performances suggesting these tools to be a powerful asset in rational epitope discovery. The updated version...

  19. Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

    Science.gov (United States)

    Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

    2014-12-01

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper

  20. A national-scale model of linear features improves predictions of farmland biodiversity.

    Science.gov (United States)

    Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

    2017-12-01

    Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

  1. Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller

    OpenAIRE

    Pak Kin Wong; Hang Cheong Wong; Chi Man Vong; Tong Meng Iong; Ka In Wong; Xianghui Gao

    2015-01-01

    Effective air-ratio control is desirable to maintain the best engine performance. However, traditional air-ratio control assumes the lambda sensor located at the tail pipe works properly and relies strongly on the air-ratio feedback signal measured by the lambda sensor. When the sensor is warming up during cold start or under failure, the traditional air-ratio control no longer works. To address this issue, this paper utilizes an advanced modelling technique, kernel extreme learning machine (...

  2. Waist-Hip Ratio Surrogate Is More Predictive Than Body Mass Index of Wound Complications After Pelvic and Acetabulum Surgery.

    Science.gov (United States)

    Jaeblon, Todd; Perry, Kevin J; Kufera, Joseph A

    2018-04-01

    To determine whether a novel surrogate of waist-hip ratio (WHR) is more predictive of wound complications after pelvis or acetabulum stabilization than body mass index (BMI) and describe the method of measuring a WHR proxy (WHRp). Retrospective review. One Level 1 Trauma Center. One hundred sixty-one patients after operative repair of pelvis and acetabulum fractures. Operative stabilization of a pelvic ring injury or acetabular fracture. Infection (pin, superficial, and deep) and wound healing complication. We retrospectively reviewed 161 subjects after operative repair of pelvic and acetabular fractures. Primary outcome was any wound complication. BMI was acquired from medical records. WHRp was derived from anteroposterior and lateral computed tomography scout images. BMI and WHRp results were analyzed as continuous and categorical variables. BMI was grouped into high-risk categories of ≥30 and ≥40. WHRp data were grouped utilizing the WHO's high-risk profile for females (>0.85) and males (>0.90). An alternative optimal WHR was also assessed. Covariate analysis included demographic data, Injury Severity Score, mechanism, tobacco use, presence and types of open approach, injury type, associated injuries and comorbidities, failure of fixation, and thromboembolism. The mean follow-up was 15.9 months. Twenty-four (15%) patients developed wound complications. Increasing BMI (P < 0.007) and WHRp (P < 0.001) as continuous variables and female sex (P < 0.009) were associated with wound complications. Applying unadjusted continuous data to a receiver operating characteristic curve revealed a greater area under the curve for WHRp than for BMI (P < 0.001). The optimal predictive WHRp was ≥1.0 (P < 0.001, odds ratio 43.11). The receiver operating characteristic curve from adjusted data demonstrated a greater area under the curve for WHRp ≥1.0 (0.93) compared with BMI ≥30 (0.78) or ≥40 (0.75) and WHO WHRp (0.82). Computed tomography generated WHRp demonstrated

  3. Aspartate aminotransferase-to-platelet ratio index for fibrosis and cirrhosis prediction in chronic hepatitis C patients

    Directory of Open Access Journals (Sweden)

    Roberto Gomes da Silva Junior

    Full Text Available In chronic hepatitis C (CHC, liver biopsy is the gold standard method for assessing liver histology, however it is invasive and can have complications. Non-invasive markers have been proposed and aspartate aminotransferase (AST-to-platelet ratio index (APRI has been shown as an easy and inexpensive marker of liver fibrosis. This study evaluated the diagnostic performance of APRI for significant fibrosis and cirrhosis prediction in CHC patients. This study included treatment-naive CHC patients who had undergone liver biopsy from January 2000 to August 2006. All histological slides were reviewed according to the METAVIR system. APRI was calculated based on laboratory results performed within four months from the biopsy. Twenty-eight (56% patients had significant fibrosis (F2-F4 and 13 (26% had cirrhosis (F4. The area under ROC curves of APRI for predicting significant fibrosis and cirrhosis were 0.92 (0.83-1.00 and 0.92 (0.85-1.00, respectively. Using cut-off values recommended by prior studies, significant fibrosis could be identified, in accordance with liver biopsy, in 44% and cirrhosis in 66% of patients. APRI could identify significant fibrosis and cirrhosis at a high degree of accuracy in studied patients.

  4. [Use of sFlt-1/PlGF ratio in preeclampsia : a monocentric retrospective analysis].

    Science.gov (United States)

    Verbeurgt, L; Chantraine, F; De Marchin, J; Minon, J-M; Nisolle, M

    2017-09-01

    Soluble Fms-like tyrosine kinase 1 (sFlt-1) is an anti-angiogenic factor released in higher amounts in preeclampsia and implicated in endothelial dysfunction. sFlt-1/PlGF ratio is used in the prediction of preeclampsia. An sFlt-1/PlGF ratio inferior to 38 predicts the short-term absence of preeclampsia. A ratio ? 85 (early-onset PE) or ? 110 (late-onset of PE) could diagnose preeclampsia. In this study, sFlt-1/PlGF ratio has been measured in 183 patients. Sixty-seven preeclampsia have been diagnosed preeclamptic at delivery. The median sFlt-1/PlGF ratio was 100.3. The median ratio among women with preeclampsia (N=67) versus no preeclampsia (N=116) was 212.7 versus 35.4. In accordance with this analysis, an sFlt-1/PlGF ratio ? 38 has a sensibility of 95,5 % and a specificity of 73.3 %. The positive predictive value and the negative predictive value were 67.4 % and 96.6 %, respectively. These results suggest that sFlt-1/PlGF ratio is helpful in the diagnosis of preeclampsia.

  5. A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios

    Science.gov (United States)

    Kranabetter, J. Marty; McLauchlan, Kendra K.; Enders, Sara K.; Fraterrigo, Jennifer M.; Higuera, Philip E.; Morris, Jesse L.; Rastetter, Edward B.; Barnes, Rebecca; Buma, Brian; Gavin, Daniel G.; Gerhart, Laci M.; Gillson, Lindsey; Hietz, Peter; Mack, Michelle C.; McNeil, Brenden; Perakis, Steven

    2016-01-01

    Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.

  6. Improved nucleic acid descriptors for siRNA efficacy prediction.

    Science.gov (United States)

    Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

    2013-02-01

    Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

  7. The role of B/D ratio and A/D ratio to defferentiate malignancy from benignancy in distal extrahepatic bile duct obstruction

    International Nuclear Information System (INIS)

    Rhim, Hyun Chul; Baek, JUng Hwan; Jeon, Eui Yong; Koh, Byung Hee; Cho, On Koo; Kim, Young Hwan

    1994-01-01

    To determine wheter bilirubin/extrahepatic bile duct diameter ratio(B/D ratio) or alkalinephosphatase/extrahepatic bile duct diameter ratio (A/D ratio) can be used to differentiate malignant from benigndisease in distal extrahepatic bile duct obstruction during ultrasonographic examination. We retrospectively reviewed the sonograms and laboratory data of 100 patients with obstructive jaundice (benign : n=50, malignant: : n=50). The diagnosis was confirmed either surgically (n=66) or clinically (n=34). The B/D ratio and A/D radio were calculated by means of dividing total bilirubin (mg/dl) and alkaline phosphatase (I.U.)respectively by maximum extrahepatic bile duct diameter(mm) on ultrasonogram. Significant difference in B/D ratio was found between the benignancy (0.28+0.25) and malignancy (0.98+0.84) groups (P<0.001). Significant difference in A/D ratio was also found between the benignancy (15.00+10.22) and malignancy (32.44+30.28) groups(P<0.001) Accuracies to predict malignancy according to criteria of B/D and A/D ratios were less than 75% and 65%respectively. On the other hand, the positive predictive value and specificity were relatively high. The B/D ratio and A/D ratio calculated from ultrasonograms can be used as a valuable screening index todifferentiate malignancy from benignacy in patients with distal extrahepatic bile duct obstruction, especially when the sonography is difficult because of the interposition of bowel gas or obesity

  8. Utilizing multiple scale models to improve predictions of extra-axial hemorrhage in the immature piglet.

    Science.gov (United States)

    Scott, Gregory G; Margulies, Susan S; Coats, Brittany

    2016-10-01

    Traumatic brain injury (TBI) is a leading cause of death and disability in the USA. To help understand and better predict TBI, researchers have developed complex finite element (FE) models of the head which incorporate many biological structures such as scalp, skull, meninges, brain (with gray/white matter differentiation), and vasculature. However, most models drastically simplify the membranes and substructures between the pia and arachnoid membranes. We hypothesize that substructures in the pia-arachnoid complex (PAC) contribute substantially to brain deformation following head rotation, and that when included in FE models accuracy of extra-axial hemorrhage prediction improves. To test these hypotheses, microscale FE models of the PAC were developed to span the variability of PAC substructure anatomy and regional density. The constitutive response of these models were then integrated into an existing macroscale FE model of the immature piglet brain to identify changes in cortical stress distribution and predictions of extra-axial hemorrhage (EAH). Incorporating regional variability of PAC substructures substantially altered the distribution of principal stress on the cortical surface of the brain compared to a uniform representation of the PAC. Simulations of 24 non-impact rapid head rotations in an immature piglet animal model resulted in improved accuracy of EAH prediction (to 94 % sensitivity, 100 % specificity), as well as a high accuracy in regional hemorrhage prediction (to 82-100 % sensitivity, 100 % specificity). We conclude that including a biofidelic PAC substructure variability in FE models of the head is essential for improved predictions of hemorrhage at the brain/skull interface.

  9. Stress ratio determination from the core-disking phenomenon

    International Nuclear Information System (INIS)

    Lehnhoff, T.F.; Stefansson, B.; Thirumalai, K.

    1982-08-01

    The ability to predict in situ stress conditions from standard core samples offers planning and site-selection advantages for most underground facilities. This paper presents an empirical relation for estimating the horizontal to vertical stress ratio in basalt. The resulting estimates can then be used to help assess the extent to which measurement of in situ stress is required. The core disking phenomenon has long been used as an indicator of high in situ stress. It is concluded that disks form as the result of tensile failure initiation rather than shear failure initiation of the core. It is deduced that the tensile failure begins at the edge of the core and propagates toward the center in shear rather than beginning at the center and propagating outward. An empirical relation for horizontal to vertical stress ratio variation with depth has been developed and is shown to agree substantially with previous measured horizontal to vertical stress ratios for locations in several areas of the world. The stress-ratio predictions are justified based on finite-element studies using linear elastic analysis and also nonlinear (tension cut-off) analysis. Indications of fracture propagation paths were determined from the analyses. The shape of the predicted propagation path agrees well with physical observations

  10. [Prognostic prediction of the functional capacity and effectiveness of functional improvement program of the musculoskeletal system among users of preventive care service under long-term care insurance].

    Science.gov (United States)

    Sone, Toshimasa; Nakaya, Naoki; Tomata, Yasutake; Aida, Jun; Okubo, Ichiro; Ohara, Satoko; Obuchi, Shuichi; Sugiyama, Michiko; Yasumura, Seiji; Suzuki, Takao; Tsuji, Ichiro

    2013-01-01

    The purpose of this study was to examine the effectiveness of the Functional Improvement Program of the Musculoskeletal System among users of Preventive Care Service under Long-Term Care Insurance. A total of 3,073 subjects were analyzed. We used the prediction formula to estimate the predicted value of the Kihon Checklist after one year, and calculated the measured value minus the predicted value. The subjects were divided into two groups according to the measured value minus predicted value tertiles: the lowest and middle tertile (good-to-fair measured value) and the highest tertile (poor measured value). We used a multiple logistic regression model to calculate the odds ratio (OR) and 95% confidence interval (CI) of the good-to-fair measured values of the Kihon Checklist after one year, according to the Functional Improvement Program of the Musculoskeletal System. In potentially dependent elderly, the multivariate adjusted ORs (95% CI) of the good-to-fair measured values were 2.4 (1.3-4.4) for those who attended the program eight times or more in a month (vs those who attended it three times or less in a month), 1.3 (1.0-1.8) for those who engaged in strength training using machines (vs those who did not train), and 1.4 (1.0-1.9) for those who engaged in endurance training. In this study, among potentially dependent elderly, those who attended the program eight times or more in a month and those who engaged in strength training using machines or endurance training showed a significant improvement of their functional capacity.

  11. Predictive value of elevated neutrophil to lymphocyte ratio in patients undergoing primary angioplasty for ST-segment elevation myocardial infarction.

    Science.gov (United States)

    Ergelen, Mehmet; Uyarel, Huseyin; Altay, Servet; Kul, Şeref; Ayhan, Erkan; Isık, Turgay; Kemaloğlu, Tuba; Gül, Mehmet; Sönmez, Osman; Erdoğan, Ercan; Turfan, Murat

    2014-05-01

    The neutrophil to lymphocyte ratio (NLR) has been investigated as a new predictor for cardiovascular risk. Admission NLR would be predictive of adverse outcomes after primary angioplasty for ST-segment elevation myocardial infarction (STEMI). A total of 2410 patients with STEMI undergoing primary angioplasty were retrospectively enrolled. The study population was divided into tertiles based on the NLR values. A high NLR (n = 803) was defined as a value in the third tertile (>6.97), and a low NLR (n = 1607) was defined as a value in the lower 2 tertiles (≤6.97). High NLR group had higher incidence of inhospital and long-term cardiovascular mortality (5% vs 1.4%, P 6.97) was found as an independent predictor of inhospital cardiovascular mortality (odds ratio: 2.8, 95% confidence interval: 1.37-5.74, P = .005). High NLR level is associated with increased inhospital and long-term cardiovascular mortality in patients with STEMI undergoing primary angioplasty.

  12. Changes in Income at Macro Level Predict Sex Ratio at Birth in OECD Countries.

    Science.gov (United States)

    Kanninen, Ohto; Karhula, Aleksi

    2016-01-01

    The human sex ratio at birth (SRB) is approximately 107 boys for every 100 girls. SRB was rising until the World War II and has been declining slightly after the 1950s in several industrial countries. Recent studies have shown that SRB varies according to exposure to disasters and socioeconomic conditions. However, it remains unknown whether changes in SRB can be explained by observable macro-level socioeconomic variables across multiple years and countries. Here we show that changes in disposable income at the macro level positively predict SRB in OECD countries. A one standard deviation increase in the change of disposable income is associated with an increase of 1.03 male births per 1000 female births. The relationship is possibly nonlinear and driven by extreme changes. The association varies from country to country being particular strong in Estonia. This is the first evidence to show that economic and social conditions are connected to SRB across countries at the macro level. This calls for further research on the effects of societal conditions on general characteristics at birth.

  13. Improved prediction and tracking of volcanic ash clouds

    Science.gov (United States)

    Mastin, Larry G.; Webley, Peter

    2009-01-01

    During the past 30??years, more than 100 airplanes have inadvertently flown through clouds of volcanic ash from erupting volcanoes. Such encounters have caused millions of dollars in damage to the aircraft and have endangered the lives of tens of thousands of passengers. In a few severe cases, total engine failure resulted when ash was ingested into turbines and coating turbine blades. These incidents have prompted the establishment of cooperative efforts by the International Civil Aviation Organization and the volcanological community to provide rapid notification of eruptive activity, and to monitor and forecast the trajectories of ash clouds so that they can be avoided by air traffic. Ash-cloud properties such as plume height, ash concentration, and three-dimensional ash distribution have been monitored through non-conventional remote sensing techniques that are under active development. Forecasting the trajectories of ash clouds has required the development of volcanic ash transport and dispersion models that can calculate the path of an ash cloud over the scale of a continent or a hemisphere. Volcanological inputs to these models, such as plume height, mass eruption rate, eruption duration, ash distribution with altitude, and grain-size distribution, must be assigned in real time during an event, often with limited observations. Databases and protocols are currently being developed that allow for rapid assignment of such source parameters. In this paper, we summarize how an interdisciplinary working group on eruption source parameters has been instigating research to improve upon the current understanding of volcanic ash cloud characterization and predictions. Improved predictions of ash cloud movement and air fall will aid in making better hazard assessments for aviation and for public health and air quality. ?? 2008 Elsevier B.V.

  14. Rivastigmine Improves Appetite by Increasing the Plasma Acyl/Des-Acyl Ghrelin Ratio and Cortisol in Alzheimer Disease

    Directory of Open Access Journals (Sweden)

    Yoshiko Furiya

    2018-03-01

    Full Text Available Background: Weight loss accelerates cognitive decline and increases mortality in patients with dementia. While acetylcholinesterase (AChE inhibitors are known to cause appetite loss, we sometimes encounter patients in whom switching from donepezil (AChE inhibitor to rivastigmine (AChE and butyrylcholinesterase [BuChE] inhibitor improves appetite. Since BuChE inactivates ghrelin, a potent orexigenic hormone, we speculated that rivastigmine improves appetite by inhibiting BuChE-mediated ghrelin inactivation. Methods: The subjects were patients with mild to moderate Alzheimer disease treated with either rivastigmine patch (n = 11 or donepezil (n = 11 for 6 months. Before and after treatment, we evaluated appetite (0, decreased; 1, slightly decreased; 2, normal; 3, slightly increased; 4, increased, cognitive function, and blood biochemical variables, including various hormones. Results: Rivastigmine treatment significantly improved appetite (from 1.6 ± 0.5 to 2.6 ± 0.7, whereas donepezil treatment did not (from 2.0 ± 0.0 to 1.8 ± 0.4. Simultaneously, rivastigmine, but not donepezil, significantly decreased the serum cholinesterase activity (from 304.3 ± 60.5 to 246.8 ± 78.5 IU/L and increased the cortisol level (from 11.86 ± 3.12 to 14.61 ± 3.29 μg/dL and the acyl/des-acyl ghrelin ratio (from 4.03 ± 2.96 to 5.28 ± 2.72. The levels of leptin, insulin, total ghrel­in, and cognitive function were not significantly affected by either treatment. Conclusions: Our results suggest that compared with donepezil, rivastigmine has the advantage of improving appetite by increasing the acyl/des-acyl ghrelin ratio and cortisol level, thereby preventing weight loss.

  15. The Study on Grinding Ratio in Form Grinding with White Fused Alumina (WA) Grinding Wheels

    Science.gov (United States)

    Junming, Wang; Jiong, Wang; Deyuan, Lou

    2018-03-01

    The study is carried out based on an experiment of form grinding spur rack with white fused alumina (WA) grinding wheels. In the experiment, SOV-3020A type tri-axial image mapper is utilized to measure the profile of the tooth space in the rack, and the curve equations between the sectional area of the tooth space and the tooth sequence under different grinding depths are established by nonlinear curve regress using software of origin8.0. Then, it deduces the prediction equations for current grinding ratio and cumulative grinding ratio under different grinding depths. The result shows that the grinding ratio is exponential decline relationship with the increase of the number of the tooth to be ground under the same grinding depth, and the decline speed is fast in the initial stage. With the increase of grinding depth, the grinding ratio increases gradually. The cumulative grinding ratio is about twice as high as the current grinding ratio. Thus, large grinding depth is generally used in rough grinding to improve grinding efficiency.

  16. Load-Unload Response Ratio and Accelerating Moment/Energy Release Critical Region Scaling and Earthquake Prediction

    Science.gov (United States)

    Yin, X. C.; Mora, P.; Peng, K.; Wang, Y. C.; Weatherley, D.

    The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

  17. Creation of a predictive equation to estimate fat-free mass and the ratio of fat-free mass to skeletal size using morphometry in lean working farm dogs.

    Science.gov (United States)

    Leung, Y M; Cave, N J; Hodgson, B A S

    2018-06-27

    To develop an equation that accurately estimates fat-free mass (FFM) and the ratio of FFM to skeletal size or mass, using morphometric measurements in lean working farm dogs, and to examine the association between FFM derived from body condition score (BCS) and FFM measured using isotope dilution. Thirteen Huntaway and seven Heading working dogs from sheep and beef farms in the Waikato region of New Zealand were recruited based on BCS (BCS 4) using a nine-point scale. Bodyweight, BCS, and morphometric measurements (head length and circumference, body length, thoracic girth, and fore and hind limb length) were recorded for each dog, and body composition was measured using an isotopic dilution technique. A new variable using morphometric measurements, termed skeletal size, was created using principal component analysis. Models for predicting FFM, leanST (FFM minus skeletal mass) and ratios of FFM and leanST to skeletal size or mass were generated using multiple linear regression analysis. Mean FFM of the 20 dogs, measured by isotope dilution, was 22.1 (SD 4.4) kg and the percentage FFM of bodyweight was 87.0 (SD 5.0)%. Median BCS was 3.0 (min 1, max 6). Bodyweight, breed, age and skeletal size or mass were associated with measured FFM (pFFM and measured FFM (R 2 =0.96), and for the ratio of predicted FFM to skeletal size and measured values (R 2 =0.99). Correlation coefficients were higher for the ratio FFM and leanST to skeletal size than for ratios using skeletal mass. There was a positive correlation between BCS-derived fat mass as a percentage of bodyweight and fat mass percentage determined using isotope dilution (R 2 =0.65). As expected, the predictive equation was accurate in estimating FFM when tested on the same group of dogs used to develop the equation. The significance of breed, independent of skeletal size, in predicting FFM indicates that individual breed formulae may be required. Future studies that apply these equations on a greater population of

  18. Improvement of energy expenditure prediction from heart rate during running

    International Nuclear Information System (INIS)

    Charlot, Keyne; Borne, Rachel; Richalet, Jean-Paul; Chapelot, Didier; Pichon, Aurélien; Cornolo, Jérémy; Brugniaux, Julien Vincent

    2014-01-01

    We aimed to develop new equations that predict exercise-induced energy expenditure (EE) more accurately than previous ones during running by including new parameters as fitness level, body composition and/or running intensity in addition to heart rate (HR). Original equations predicting EE were created from data obtained during three running intensities (25%, 50% and 70% of HR reserve) performed by 50 subjects. Five equations were conserved according to their accuracy assessed from error rates, interchangeability and correlations analyses: one containing only basic parameters, two containing VO 2max  or speed at VO 2max  and two including running speed with or without HR. Equations accuracy was further tested in an independent sample during a 40 min validation test at 50% of HR reserve. It appeared that: (1) the new basic equation was more accurate than pre-existing equations (R 2  0.809 versus. 0,737 respectively); (2) the prediction of EE was more accurate with the addition of VO 2max  (R 2  = 0.879); and (3) the equations containing running speed were the most accurate and were considered to have good agreement with indirect calorimetry. In conclusion, EE estimation during running might be significantly improved by including running speed in the predictive models, a parameter readily available with treadmill or GPS. (paper)

  19. Mid- and long-term runoff predictions by an improved phase-space reconstruction model

    International Nuclear Information System (INIS)

    Hong, Mei; Wang, Dong; Wang, Yuankun; Zeng, Xiankui; Ge, Shanshan; Yan, Hengqian; Singh, Vijay P.

    2016-01-01

    In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall–runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ‘‘wet years and dry years predictability barrier,’’ to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff. - Highlights: • The improved phase-space reconstruction model of monthly runoff is established. • Two variables (temperature and rainfall) are incorporated

  20. Mid- and long-term runoff predictions by an improved phase-space reconstruction model

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Mei [Research Center of Ocean Environment Numerical Simulation, Institute of Meteorology and oceanography, PLA University of Science and Technology, Nanjing (China); Wang, Dong, E-mail: wangdong@nju.edu.cn [Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Collaborative Innovation Center of South China Sea Studies, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210093 (China); Wang, Yuankun; Zeng, Xiankui [Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Collaborative Innovation Center of South China Sea Studies, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210093 (China); Ge, Shanshan; Yan, Hengqian [Research Center of Ocean Environment Numerical Simulation, Institute of Meteorology and oceanography, PLA University of Science and Technology, Nanjing (China); Singh, Vijay P. [Department of Biological and Agricultural Engineering Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843 (United States)

    2016-07-15

    In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall–runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ‘‘wet years and dry years predictability barrier,’’ to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff. - Highlights: • The improved phase-space reconstruction model of monthly runoff is established. • Two variables (temperature and rainfall) are incorporated

  1. The effects of convergence ratio on the implosion behavior of DT layered inertial confinement fusion capsules

    Science.gov (United States)

    Haines, Brian M.; Yi, S. A.; Olson, R. E.; Khan, S. F.; Kyrala, G. A.; Zylstra, A. B.; Bradley, P. A.; Peterson, R. R.; Kline, J. L.; Leeper, R. J.; Shah, R. C.

    2017-07-01

    The wetted foam capsule design for inertial confinement fusion capsules, which includes a foam layer wetted with deuterium-tritium liquid, enables layered capsule implosions with a wide range of hot-spot convergence ratios (CR) on the National Ignition Facility. We present a full-scale wetted foam capsule design that demonstrates high gain in one-dimensional simulations. In these simulations, increasing the convergence ratio leads to an improved capsule yield due to higher hot-spot temperatures and increased fuel areal density. High-resolution two-dimensional simulations of this design are presented with detailed and well resolved models for the capsule fill tube, support tent, surface roughness, and predicted asymmetries in the x-ray drive. Our modeling of these asymmetries is validated by comparisons with available experimental data. In 2D simulations of the full-scale wetted foam capsule design, jetting caused by the fill tube is prevented by the expansion of the tungsten-doped shell layer due to preheat. While the impacts of surface roughness and predicted asymmetries in the x-ray drive are enhanced by convergence effects, likely underpredicted in 2D at high CR, simulations predict that the capsule is robust to these features. Nevertheless, the design is highly susceptible to the effects of the capsule support tent, which negates all of the one-dimensional benefits of increasing the convergence ratio. Indeed, when the support tent is included in simulations, the yield decreases as the convergence ratio is increased for CR > 20. Nevertheless, the results suggest that the full-scale wetted foam design has the potential to outperform ice layer capsules given currently achievable levels of asymmetries when fielded at low convergence ratios (CR < 20).

  2. Improved modified energy ratio method using a multi-window approach for accurate arrival picking

    Science.gov (United States)

    Lee, Minho; Byun, Joongmoo; Kim, Dowan; Choi, Jihun; Kim, Myungsun

    2017-04-01

    To identify accurately the location of microseismic events generated during hydraulic fracture stimulation, it is necessary to detect the first break of the P- and S-wave arrival times recorded at multiple receivers. These microseismic data often contain high-amplitude noise, which makes it difficult to identify the P- and S-wave arrival times. The short-term-average to long-term-average (STA/LTA) and modified energy ratio (MER) methods are based on the differences in the energy densities of the noise and signal, and are widely used to identify the P-wave arrival times. The MER method yields more consistent results than the STA/LTA method for data with a low signal-to-noise (S/N) ratio. However, although the MER method shows good results regardless of the delay of the signal wavelet for signals with a high S/N ratio, it may yield poor results if the signal is contaminated by high-amplitude noise and does not have the minimum delay. Here we describe an improved MER (IMER) method, whereby we apply a multiple-windowing approach to overcome the limitations of the MER method. The IMER method contains calculations of an additional MER value using a third window (in addition to the original MER window), as well as the application of a moving average filter to each MER data point to eliminate high-frequency fluctuations in the original MER distributions. The resulting distribution makes it easier to apply thresholding. The proposed IMER method was applied to synthetic and real datasets with various S/N ratios and mixed-delay wavelets. The results show that the IMER method yields a high accuracy rate of around 80% within five sample errors for the synthetic datasets. Likewise, in the case of real datasets, 94.56% of the P-wave picking results obtained by the IMER method had a deviation of less than 0.5 ms (corresponding to 2 samples) from the manual picks.

  3. Improving surface acousto-optical interaction by high aspect ratio electrodes

    DEFF Research Database (Denmark)

    Dühring, Maria Bayard; Laude, Vincent; Khelif, Abdelkrim

    2009-01-01

    The acousto-optical interaction of an optical wave confined inside a waveguide and a surface acoustic wave launched by an interdigital transducer (IDT) at the surface of a piezoelectric material is considered. The IDT with high aspect ratio electrodes supports several acoustic modes that are stro......The acousto-optical interaction of an optical wave confined inside a waveguide and a surface acoustic wave launched by an interdigital transducer (IDT) at the surface of a piezoelectric material is considered. The IDT with high aspect ratio electrodes supports several acoustic modes...

  4. Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

    Science.gov (United States)

    Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

    2016-01-01

    Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

  5. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

    Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

    2017-12-01

    Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

  6. An integrated approach to improved toxicity prediction for the safety assessment during preclinical drug development using Hep G2 cells

    International Nuclear Information System (INIS)

    Noor, Fozia; Niklas, Jens; Mueller-Vieira, Ursula; Heinzle, Elmar

    2009-01-01

    Efficient and accurate safety assessment of compounds is extremely important in the preclinical development of drugs especially when hepatotoxicty is in question. Multiparameter and time resolved assays are expected to greatly improve the prediction of toxicity by assessing complex mechanisms of toxicity. An integrated approach is presented in which Hep G2 cells and primary rat hepatocytes are compared in frequently used cytotoxicity assays for parent compound toxicity. The interassay variability was determined. The cytotoxicity assays were also compared with a reliable alternative time resolved respirometric assay. The set of training compounds consisted of well known hepatotoxins; amiodarone, carbamazepine, clozapine, diclofenac, tacrine, troglitazone and verapamil. The sensitivity of both cell systems in each tested assay was determined. Results show that careful selection of assay parameters and inclusion of a kinetic time resolved assay improves prediction for non-metabolism mediated toxicity using Hep G2 cells as indicated by a sensitivity ratio of 1. The drugs with EC 50 values 100 μM or lower were considered toxic. The difference in the sensitivity of the two cell systems to carbamazepine which causes toxicity via reactive metabolites emphasizes the importance of human cell based in-vitro assays. Using the described system, primary rat hepatocytes do not offer advantage over the Hep G2 cells in parent compound toxicity evaluation. Moreover, respiration method is non invasive, highly sensitive and allows following the time course of toxicity. Respiration assay could serve as early indicator of changes that subsequently lead to toxicity.

  7. Optimized thick-wall cylinders by virtue of Poisson's ratio selection

    International Nuclear Information System (INIS)

    Whitty, J.P.M.; Henderson, B.; Francis, J.; Lloyd, N.

    2011-01-01

    The principal stress distributions in thick-wall cylinders due to variation in the Poisson's ratio are predicted using analytical and finite element methods. Analyses of appropriate brittle and ductile failure criteria show that under the isochoric pressure conditions investigated that auextic (i.e. those possessing a negative Poisson's ratio) materials act as stress concentrators; hence they are predicted to fail before their conventional (i.e. possessing a positive Poisson's ratio) material counterparts. The key finding of the work presented shows that for constrained thick-wall cylinders the maximum tensile principal stress can vanish at a particular Poisson's ratio and aspect ratio. This phenomenon is exploited in order to present an optimized design criterion for thick-wall cylinders. Moreover, via the use of a cogent finite element model, this criterion is also shown to be applicable for the design of micro-porous materials.

  8. Hypoxic Prostate/Muscle PO{sub 2} Ratio Predicts for Outcome in Patients With Localized Prostate Cancer: Long-Term Results

    Energy Technology Data Exchange (ETDEWEB)

    Turaka, Aruna [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Buyyounouski, Mark K., E-mail: mark.buyyounouski@fccc.edu [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Hanlon, Alexandra L. [School of Nursing, University of Pennsylvania, Philadelphia, PA (United States); Horwitz, Eric M. [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Greenberg, Richard E. [Department of Surgery, Fox Chase Cancer Center, Philadelphia, PA (United States); Movsas, Benjamin [Department of Radiation Oncology, Henry Ford Hospital, Detroit, MI (United States)

    2012-03-01

    Purpose: To correlate tumor oxygenation status with long-term biochemical outcome after prostate brachytherapy. Methods and Materials: Custom-made Eppendorf PO{sub 2} microelectrodes were used to obtain PO{sub 2} measurements from the prostate (P), focused on positive biopsy locations, and normal muscle tissue (M), as a control. A total of 11,516 measurements were obtained in 57 men with localized prostate cancer immediately before prostate brachytherapy was given. The Eppendorf histograms provided the median PO{sub 2}, mean PO{sub 2}, and % <5 mm Hg or <10 mm Hg. Biochemical failure (BF) was defined using both the former American Society of Therapeutic Radiation Oncology (ASTRO) (three consecutive raises) and the current Phoenix (prostate-specific antigen nadir + 2 ng/mL) definitions. A Cox proportional hazards regression model evaluated the influence of hypoxia using the P/M mean PO{sub 2} ratio on BF. Results: With a median follow-up time of 8 years, 12 men had ASTRO BF and 8 had Phoenix BF. On multivariate analysis, P/M PO{sub 2} ratio <0.10 emerged as the only significant predictor of ASTRO BF (p = 0.043). Hormonal therapy (p = 0.015) and P/M PO{sub 2} ratio <0.10 (p = 0.046) emerged as the only independent predictors of the Phoenix BF. Kaplan-Meier freedom from BF for P/M ratio <0.10 vs. {>=}0.10 at 8 years for ASTRO BF was 46% vs. 78% (p = 0.03) and for the Phoenix BF was 66% vs. 83% (p = 0.02). Conclusions: Hypoxia in prostate cancer (low mean P/M PO{sub 2} ratio) significantly predicts for poor long-term biochemical outcome, suggesting that novel hypoxic strategies should be investigated.

  9. Improvement of ethanol production from crystalline cellulose via optimizing cellulase ratios in cellulolytic Saccharomyces cerevisiae.

    Science.gov (United States)

    Liu, Zhuo; Inokuma, Kentaro; Ho, Shih-Hsin; den Haan, Riaan; van Zyl, Willem H; Hasunuma, Tomohisa; Kondo, Akihiko

    2017-06-01

    Crystalline cellulose is one of the major contributors to the recalcitrance of lignocellulose to degradation, necessitating high dosages of cellulase to digest, thereby impeding the economic feasibility of cellulosic biofuels. Several recombinant cellulolytic yeast strains have been developed to reduce the cost of enzyme addition, but few of these strains are able to efficiently degrade crystalline cellulose due to their low cellulolytic activities. Here, by combining the cellulase ratio optimization with a novel screening strategy, we successfully improved the cellulolytic activity of a Saccharomyces cerevisiae strain displaying four different synergistic cellulases on the cell surface. The optimized strain exhibited an ethanol yield from Avicel of 57% of the theoretical maximum, and a 60% increase of ethanol titer from rice straw. To our knowledge, this work is the first optimization of the degradation of crystalline cellulose by tuning the cellulase ratio in a cellulase cell-surface display system. This work provides key insights in engineering the cellulase cocktail in a consolidated bioprocessing yeast strain. Biotechnol. Bioeng. 2017;114: 1201-1207. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

    OpenAIRE

    Chan, Kin Wai; Meng, Xiao-Li

    2017-01-01

    Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard $F$ distribution; (ii) it is not invariant to re-parametrization; ...

  11. Prognostic value of serum heavy/light chain ratios in patients with POEMS syndrome.

    Science.gov (United States)

    Wang, Chen; Su, Wei; Cai, Qian-Qian; Cai, Hao; Ji, Wei; Di, Qian; Duan, Ming-Hui; Cao, Xin-Xin; Zhou, Dao-Bin; Li, Jian

    2016-07-01

    POEMS syndrome is a rare plasma cell dyscrasia. Serum concentrations of the monoclonal protein in this disorder are typically low, and inapplicable to monitor disease activity in most cases, resulting in limited practical and prognostic values. Novel immunoassays measuring isotype-specific heavy/light chain (HLC) pairs showed its utility in disease monitoring and outcome prediction in several plasma cell dyscrasias. We report results of HLC measurements in 90 patients with POEMS syndrome. Sixty-six patients (73%; 95% confidence interval, 63-82%) had an abnormal HLC ratio at baseline. It could stratify the risk of disease relapse and was strongly associated with worse progression-free survival in a multivariate analysis (P = 0.021; hazard ratio [HR] 6.89, 95% CI 1.34-35.43). After therapy, HLC ratios improved, with 43 patients (48%) remaining abnormal. The post-therapeutic HLC ratio, if abnormal, also remained as an independent prognostic factor associated with worse progression-free survival (P = 0.019; HR 4.30, 95% CI 1.27-14.56). These results suggest the prognostic utility of HLC ratios in clinical management of POEMS patients. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

    Science.gov (United States)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

    Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

  13. RAPID COMMUNICATION: Improving prediction accuracy of GPS satellite clocks with periodic variation behaviour

    Science.gov (United States)

    Heo, Youn Jeong; Cho, Jeongho; Heo, Moon Beom

    2010-07-01

    The broadcast ephemeris and IGS ultra-rapid predicted (IGU-P) products are primarily available for use in real-time GPS applications. The IGU orbit precision has been remarkably improved since late 2007, but its clock products have not shown acceptably high-quality prediction performance. One reason for this fact is that satellite atomic clocks in space can be easily influenced by various factors such as temperature and environment and this leads to complicated aspects like periodic variations, which are not sufficiently described by conventional models. A more reliable prediction model is thus proposed in this paper in order to be utilized particularly in describing the periodic variation behaviour satisfactorily. The proposed prediction model for satellite clocks adds cyclic terms to overcome the periodic effects and adopts delay coordinate embedding, which offers the possibility of accessing linear or nonlinear coupling characteristics like satellite behaviour. The simulation results have shown that the proposed prediction model outperforms the IGU-P solutions at least on a daily basis.

  14. Improved characterization of EV preparations based on protein to lipid ratio and lipid properties.

    Directory of Open Access Journals (Sweden)

    Xabier Osteikoetxea

    Full Text Available In recent years the study of extracellular vesicles has gathered much scientific and clinical interest. As the field is expanding, it is becoming clear that better methods for characterization and quantification of extracellular vesicles as well as better standards to compare studies are warranted. The goal of the present work was to find improved parameters to characterize extracellular vesicle preparations. Here we introduce a simple 96 well plate-based total lipid assay for determination of lipid content and protein to lipid ratios of extracellular vesicle preparations from various myeloid and lymphoid cell lines as well as blood plasma. These preparations included apoptotic bodies, microvesicles/microparticles, and exosomes isolated by size-based fractionation. We also investigated lipid bilayer order of extracellular vesicle subpopulations using Di-4-ANEPPDHQ lipid probe, and lipid composition using affinity reagents to clustered cholesterol (monoclonal anti-cholesterol antibody and ganglioside GM1 (cholera toxin subunit B. We have consistently found different protein to lipid ratios characteristic for the investigated extracellular vesicle subpopulations which were substantially altered in the case of vesicular damage or protein contamination. Spectral ratiometric imaging and flow cytometric analysis also revealed marked differences between the various vesicle populations in their lipid order and their clustered membrane cholesterol and GM1 content. Our study introduces for the first time a simple and readily available lipid assay to complement the widely used protein assays in order to better characterize extracellular vesicle preparations. Besides differentiating extracellular vesicle subpopulations, the novel parameters introduced in this work (protein to lipid ratio, lipid bilayer order, and lipid composition, may prove useful for quality control of extracellular vesicle related basic and clinical studies.

  15. Understanding Laterally Varying Path Effects on P/S Ratios and their Effectiveness for Event Discrimination at Local Distances

    Science.gov (United States)

    Pyle, M. L.; Walter, W. R.

    2017-12-01

    Discrimination between underground explosions and naturally occurring earthquakes is an important endeavor for global security and test-ban treaty monitoring, and ratios of seismic P to S-wave amplitudes at regional distances have proven to be an effective discriminant. The use of the P/S ratio is rooted in the idea that explosive sources should theoretically only generate compressional energy. While, in practice, shear energy is observed from explosions, generally when corrections are made for magnitude and distance, P/S ratios from explosions are higher than those from surrounding earthquakes. At local distances (chemical explosions at the Nevada National Security Site (NNSS) designed to improve our understanding and modeling capabilities of shear waves generated by explosions. Phase I consisted of 5 explosions in granite and Phase II will move to a contrasting dry alluvium geology. We apply a high-resolution 2D attenuation model to events near the NNSS to examine what effect path plays in local P/S ratios, and how well an earthquake-derived model can account for shallower explosion paths. The model incorporates both intrinsic attenuation and scattering effects and extends to 16 Hz, allowing us to make lateral path corrections and consider high-frequency ratios. Preliminary work suggests that while 2D path corrections modestly improve earthquake amplitude predictions, explosion amplitudes are not well matched, and so P/S ratios do not necessarily improve. Further work is needed to better understand the uses and limitation of 2D path corrections for local P/S ratios.

  16. Financial Ratios and Perceived Household Financial Satisfaction

    Directory of Open Access Journals (Sweden)

    Scott Garrett

    2013-08-01

    Full Text Available This paper tests the relative strength of three objective measures of financial health (using the solvency, liquidity, and investment asset ratio in predicting a household’s subjective feeling of current financial satisfaction. Using a sample of 6,923 respondents in the 2008 Health and Retirement Study this paper presents evidence of two main findings: 1 the solvency ratio is most strongly associated with financial satisfaction levels based on a cross-sectional design and 2 changes in the investment asset ratio are most strongly associated with changes in financial satisfaction over time.

  17. Improved time series prediction with a new method for selection of model parameters

    International Nuclear Information System (INIS)

    Jade, A M; Jayaraman, V K; Kulkarni, B D

    2006-01-01

    A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

  18. Regional improvement of signal-to-noise and contrast-to-noise ratios in dual-screen CR chest imaging - a phantom study

    International Nuclear Information System (INIS)

    Liu Xinming; Shaw, Chris C.

    2001-01-01

    The improvement of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in dual-screen computed radiography (CR) has been investigated for various regions in images of an anthropomorphic chest phantom. With the dual-screen CR technique, two image plates are placed in a cassette and exposed together during imaging. The exposed plates are separately scanned to form a front image and a back image, which are then registered and superimposed to form a composite image with improved SNRs and CNRs. The improvement can be optimized by applying specifically selected weighting factors during superimposition. In this study, dual-screen CR images of an anthropomorphic chest phantom were acquired and formed with four different combinations of standard resolution (ST) and high-resolution (HR) screens: ST-ST, ST-HR, HR-ST, and HR-HR. SNRs and their improvements were measured and compared over twelve representative regions-of-interest (ROIs) in these images. A 19.1%-45.7% increase of the SNR was observed, depending on the ROI and screen combination used. The optimal weighting factors were found to vary by only 4.5%-12.4%. Largest improvement was found in the lung field for all screen combinations. Improvement of CNRs was investigated over two ROIs in the lung field using the rib bones as the contrast objects and a 29.2%-43.9% improvement of the CNR was observed. Among the four screen combinations, ST-ST resulted in the most SNR and CNR improvement, followed in order by HR-ST, HR-HR, and ST-HR. The HR-ST combination yielded the lowest spatial variation of the optimal weighting factors with improved SNRs and CNRs close to those of the ST-ST combination

  19. Improving the signal-to-noise ratio in ultrasound-modulated optical tomography by a lock-in amplifier

    Science.gov (United States)

    Zhu, Lili; Wu, Jingping; Lin, Guimin; Hu, Liangjun; Li, Hui

    2016-10-01

    With high spatial resolution of ultrasonic location and high sensitivity of optical detection, ultrasound-modulated optical tomography (UOT) is a promising noninvasive biological tissue imaging technology. In biological tissue, the ultrasound-modulated light signals are very weak and are overwhelmed by the strong unmodulated light signals. It is a difficulty and key to efficiently pick out the weak modulated light from strong unmodulated light in UOT. Under the effect of an ultrasonic field, the scattering light intensity presents a periodic variation as the ultrasonic frequency changes. So the modulated light signals would be escape from the high unmodulated light signals, when the modulated light signals and the ultrasonic signal are processed cross correlation operation by a lock-in amplifier and without a chopper. Experimental results indicated that the signal-to-noise ratio of UOT is significantly improved by a lock-in amplifier, and the higher the repetition frequency of pulsed ultrasonic wave, the better the signal-to-noise ratio of UOT.

  20. Does the aldosterone: renin ratio predict the efficacy of spironolactone over bendroflumethiazide in hypertension? A clinical trial protocol for RENALDO (RENin-ALDOsterone study

    Directory of Open Access Journals (Sweden)

    McInnes Gordon T

    2007-05-01

    Full Text Available Abstract Background High blood pressure is an important determinant of cardiovascular disease risk. Treated hypertensives do not attain a risk level equivalent to normotensives. This may be a consequence of suboptimal blood pressure control to which indiscriminate use of antihypertensive drugs may contribute. Indeed the recent ALLHAT1study suggests that thiazides should be given first to virtually all hypertensives. Whether this is correct or whether different antihypertensive therapies should be targeted towards different patients is a major unresolved issue, which we address in this study. The measurement of the ratio of aldosterone: renin is used to identify hypertensive subjects who may respond well to treatment with the aldosterone antagonist spironolactone. It is not known if subjects with a high ratio have aldosteronism or aldosterone-sensitive hypertension is debated but it is important to know whether spironolactone is superior to other diuretics such as bendroflumethiazide in this setting. Methods/design The study is a double-blind, randomised, crossover, controlled trial that will randomise 120 hypertensive subjects to 12 weeks treatment with spironolactone 50 mg once daily and 12 weeks treatment with bendroflumethiazide 2.5 mg once daily. The 2 treatment periods are separated by a 2-week washout period. Randomisation is stratified by aldosterone: renin ratio to include equal numbers of subjects with high and low aldosterone: renin ratios. Primary Objective – To test the hypothesis that the aldosterone: renin ratio predicts the antihypertensive response to spironolactone, specifically that the effect of spironolactone 50 mg is greater than that of bendroflumethiazide 2.5 mg in hypertensive subjects with high aldosterone: renin ratios. Secondary Objectives – To determine whether bendroflumethiazide induces adverse metabolic abnormalities, especially in subjects with high aldosterone: renin ratios and if baseline renin measurement

  1. Increased tumour ADC value during chemotherapy predicts improved survival in unresectable pancreatic cancer

    Energy Technology Data Exchange (ETDEWEB)

    Nishiofuku, Hideyuki; Tanaka, Toshihiro; Kichikawa, Kimihiko [Nara Medical University, Department of Radiology and IVR Center, Kashihara-city, Nara (Japan); Marugami, Nagaaki [Nara Medical University, Department of Endoscopy and Ultrasound, Kashihara-city, Nara (Japan); Sho, Masayuki; Akahori, Takahiro; Nakajima, Yoshiyuki [Nara Medical University, Department of Surgery, Kashihara-city, Nara (Japan)

    2016-06-15

    To investigate whether changes to the apparent diffusion coefficient (ADC) of primary tumour in the early period after starting chemotherapy can predict progression-free survival (PFS) or overall survival (OS) in patients with unresectable pancreatic adenocarcinoma. Subjects comprised 43 patients with histologically confirmed unresectable pancreatic cancer treated with first-line chemotherapy. Minimum ADC values in primary tumour were measured using the selected area ADC (sADC), which excluded cystic and necrotic areas and vessels, and the whole tumour ADC (wADC), which included whole tumour components. Relative changes in ADC were calculated from baseline to 4 weeks after initiation of chemotherapy. Relationships between ADC and both PFS and OS were modelled by Cox proportional hazards regression. Median PFS and OS were 6.1 and 11.0 months, respectively. In multivariate analysis, sADC change was the strongest predictor of PFS (hazard ratio (HR), 4.5; 95 % confidence interval (CI), 1.7-11.9; p = 0.002). Multivariate Cox regression analysis for OS revealed sADC change and CRP as independent predictive markers, with sADC change as the strongest predictive biomarker (HR, 6.7; 95 % CI, 2.7-16.6; p = 0.001). Relative changes in sADC could provide a useful imaging biomarker to predict PFS and OS with chemotherapy for unresectable pancreatic adenocarcinoma. (orig.)

  2. Predicting grade of cerebral gliomas using Myo-inositol/Creatine ratio

    Directory of Open Access Journals (Sweden)

    Lamiaa I.A. Metwally

    2014-03-01

    Conclusion: MRS has proven to be an important complementary tool saving the patient from unnecessary biopsy taking when it is conclusive thus altering the treatment planning. This study had demonstrated that MI level and MI/Cr ratio are important in presurgical grading of brain tumors.

  3. Qualitative Resting Coronary Pressure Wave Form Analysis to Predict Fractional Flow Reserve.

    Science.gov (United States)

    Matsumura, Mitsuaki; Maehara, Akiko; Johnson, Nils P; Fearon, William F; De Bruyne, Bernard; Oldroyd, Keith G; Pijls, Nico H J; Jenkins, Paul; Ali, Ziad A; Mintz, Gary S; Stone, Gregg W; Jeremias, Allen

    2018-03-27

    To evaluate the predictability of resting distal coronary pressure wave forms for fractional flow reserve (FFR). Resting coronary wave forms were qualitatively evaluated for the presence of (i) dicrotic notch; (ii) diastolic dipping; and (iii) ventricularization. In a development cohort (n=88) a scoring system was developed that was then applied to a validation cohort (n=428) using a multivariable linear regression model to predict FFR and receiver operating characteristics (ROC) to predict FFR ≤0.8. In the development cohort, all 3 qualitative parameters were independent predictors of FFR. However, in a multivariable linear regression model in the validation cohort, qualitative wave form analysis did not further improve the ability of resting distal coronary to aortic pressure ratio (Pd/Pa) (p=0.80) or instantaneous wave-free ratio (iFR) (p=0.26) to predict FFR. Using ROC, the area under the curve of resting Pd/Pa (0.86 versus 0.86, P=0.08) and iFR (0.86 versus 0.86, P=0.26) did not improve by adding qualitative analysis. Qualitative coronary wave form analysis showed moderate classification agreement in predicting FFR but did not add substantially to the resting pressure gradients Pd/Pa and iFR; however, when discrepancies between quantitative and qualitative analyses are observed, artifact or pressure drift should be considered.

  4. High Platelet-to-Lymphocyte Ratio Predicts Poor Prognosis and Clinicopathological Characteristics in Patients with Breast Cancer: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Miao Zhang

    2017-01-01

    Full Text Available Background. We aimed to evaluate the correlation of platelet-to-lymphocyte ratio (PLR with prognosis and clinicopathological characteristics of breast cancer. Methods. The PubMed and Embase databases were searched. Hazard ratio (HR with 95% confidence interval (CI was used to summarize disease-free survival (DFS and overall survival (OS. Odds ratio (OR was used to summarize tumor clinicopathological characteristics. Results. High PLR was associated with poor DFS and OS (DFS: HR = 1.47, 95% CI = 1.16–1.85, and Tau2 = 0.070; OS: HR = 1.88, 95% CI = 1.27–2.80, and Tau2 = 0.192. A Galbraith plot indicated that the studies by Allan et al. and Cihan et al. contributed the heterogeneity of DFS and OS, respectively. There were significant differences in the incidence of high PLR between stage II–IV and stage I groups (OR = 1.86, 95% CI = 1.20–2.90, and Tau2 < 0.001, between lymph node-positive and lymph node-negative groups (OR = 1.52, 95% CI = 1.22–1.91, and Tau2 =0.014, and between metastasis-positive and metastasis-negative groups (OR = 4.24, 95% CI = 2.73–6.59, and Tau2 < 0.001. Conclusions. Our results indicated that PLR was associated with poor prognosis of breast cancer and adequately predicted clinicopathological characteristics.

  5. Ratio of a strange quark mass ms to up or down quark mass mu,d predicted by a quark propagator in the framework of the chiral perturbation theory

    International Nuclear Information System (INIS)

    Peng Jinsong; Meng Chengju; Pan Jihuan; Yuan Tongquan; Zhou Lijuan; Ma Weixing

    2013-01-01

    Based on the fully dressed quark propagator and chiral perturbation theory, we study the ratio of the strange quark mass m s to up or down quark mass m u,d . The ratio is related to the determination of quark masses which are fundamental input parameters of QCD Lagrangian in the Standard Model of particle physics and can not be directly measured since the quark is confined within a hadron. An accurate determination of these QCD free parameters is extremely important for both phenomenological and theoretical applications. We begin with a brief introduction to the non-perturbation QCD theory, and then study the mass ratio in the framework of the chiral perturbation theory (χPT) with a parameterized fully dressed quark propagator which describes confining fully dressed quark propagation and is analytic everywhere in the finite complex p 2 -plane and has no Lehmann representation so there are no quark production thresholds in any theoretical calculations of observable data. Our prediction for the ratio m s /m u,d is consistent with other model predictions such as Lattice QCD, instanton model, QCD sum rules and the empirical values used widely in the literature. As a by-product of this study, our theoretical results, together with other predictions of physical quantities that used this quark propagator in our previous publications, clearly show that the parameterized form of the fully dressed quark propagator is an applicable and reliable approximation to the solution of the Dyson-Schwinger Equation of quark propagator in the QCD. (authors)

  6. Wald Sequential Probability Ratio Test for Analysis of Orbital Conjunction Data

    Science.gov (United States)

    Carpenter, J. Russell; Markley, F. Landis; Gold, Dara

    2013-01-01

    We propose a Wald Sequential Probability Ratio Test for analysis of commonly available predictions associated with spacecraft conjunctions. Such predictions generally consist of a relative state and relative state error covariance at the time of closest approach, under the assumption that prediction errors are Gaussian. We show that under these circumstances, the likelihood ratio of the Wald test reduces to an especially simple form, involving the current best estimate of collision probability, and a similar estimate of collision probability that is based on prior assumptions about the likelihood of collision.

  7. Improved prediction of reservoir behavior through integration of quantitative geological and petrophysical data

    Energy Technology Data Exchange (ETDEWEB)

    Auman, J. B.; Davies, D. K.; Vessell, R. K.

    1997-08-01

    Methodology that promises improved reservoir characterization and prediction of permeability, production and injection behavior during primary and enhanced recovery operations was demonstrated. The method is based on identifying intervals of unique pore geometry by a combination of image analysis techniques and traditional petrophysical measurements to calculate rock type and estimate permeability and saturation. Results from a complex carbonate and sandstone reservoir were presented as illustrative examples of the versatility and high level of accuracy of this method in predicting reservoir quality. 16 refs., 5 tabs., 14 figs.

  8. Predictive value of spot urine albumin-to-creatinine ratio for ...

    African Journals Online (AJOL)

    ABEOLUGBENGAS

    diagnosed hypertensive patients. 1. 2. 1. 3. 4. 1. 1 ... Keywords: Hypertension, microalbuminuria, albumin-to-creatinine ratio, left ventricular hypertrophy .... an average blood pressure of ≥140mmHg .... be due to variation in methods of detecting .... Unexpectedly high prevalence of target organ damage in newly diagnosed.

  9. Potential of right to left ventricular volume ratio measured on chest CT for the prediction of pulmonary hypertension: correlation with pulmonary arterial systolic pressure estimated by echocardiography

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Heon [Soon Chun Hyang University, Department of Radiology, Bucheon (Korea, Republic of); Kim, Seok Yeon [Seoul Medical Center, Department of Cardiology, Seoul (Korea, Republic of); Lee, Soo Jeong [Terarecon Korea, Seoul (Korea, Republic of); Kim, Jae Kyun [Chung-Ang University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Reddy, Ryan P.; Schoepf, U.J. [Medical University of South Carolina, Department of Radiology and Radiological Science and Division of Cardiology, Department of Medicine, Charleston, SC (United States)

    2012-09-15

    To investigate the correlation of right ventricular (RV) to left ventricular (LV) volume ratio measured by chest CT with pulmonary arterial systolic pressure (PASP) estimated by echocardiography. 104 patients (72.47 {+-} 13.64 years; 39 male) who had undergone chest CT and echocardiography were divided into two groups (hypertensive and normotensive) based upon an echocardiography-derived PASP of 25 mmHg. RV to LV volume ratios (RV{sub V}/LV{sub V}) were calculated. RV{sub V}/LV{sub V} was then correlated with PASP using regression analysis. The Area Under the Curve (AUC) for predicting pulmonary hypertension on chest CT was calculated. In the hypertensive group, the mean PASP was 46.29 {+-} 14.42 mmHg (29-98 mmHg) and there was strong correlation between the RV{sub V}/LV{sub V} and PASP (R = 0.82, p < 0.001). The intraobserver and interobserver correlation coefficients for RV{sub V}/LV{sub V} were 0.990 and 0.892. RV{sub V}/LV{sub V} was 1.01 {+-} 0.44 (0.51-2.77) in the hypertensive and 0.72 {+-} 0.14 (0.52-1.11) in the normotensive group (P <0.05). With 0.9 as the cutoff for RV{sub V}/LV{sub V}, sensitivity and specificity for predicting pulmonary hypertension over 40 mmHg were 79.5 % and 90 %, respectively. The AUC for predicting pulmonary hypertension was 0.87 RV/LV volume ratios on chest CT correlate well with PASP estimated by echocardiography and can be used to predict pulmonary hypertension over 40 mmHg with high sensitivity and specificity. (orig.)

  10. Balancing carbon/nitrogen ratio to improve nutrients removal and algal biomass production in piggery and brewery wastewaters.

    Science.gov (United States)

    Zheng, Hongli; Liu, Mingzhi; Lu, Qian; Wu, Xiaodan; Ma, Yiwei; Cheng, Yanling; Addy, Min; Liu, Yuhuan; Ruan, Roger

    2018-02-01

    To improve nutrients removal from wastewaters and enhance algal biomass production, piggery wastewater was mixed with brewery wastewaters. The results showed that it was a promising way to cultivate microalga in piggery and brewery wastewaters by balancing the carbon/nitrogen ratio. The optimal treatment condition for the mixed piggery-brewery wastewater using microalga was piggery wastewater mixed with brewery packaging wastewater by 1:5 at pH 7.0, resulting in carbon/nitrogen ratio of 7.9, with the biomass concentration of 2.85 g L -1 , and the removal of 100% ammonia, 96% of total nitrogen, 90% of total phosphorus, and 93% of chemical oxygen demand. The application of the established strategies can enhance nutrient removal efficiency of the wastewaters while reducing microalgal biomass production costs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Combined effects of cooled EGR and a higher geometric compression ratio on thermal efficiency improvement of a downsized boosted spark-ignition direct-injection engine

    International Nuclear Information System (INIS)

    Su, Jianye; Xu, Min; Li, Tie; Gao, Yi; Wang, Jiasheng

    2014-01-01

    Highlights: • Experiments for the effects of cooled EGR and two compression ratios (CR) on fuel efficiency were conducted. • The mechanism for the observed fuel efficiency behaviors by cooled EGR and high CR was clarified. • Cooled EGR offers more fuel efficiency improvement than elevating CR from 9.3 to 10.9. • Combining 18–25% cooled EGR with 10.9 CR lead to 2.1–3.5% brake thermal efficiency improvements. - Abstract: The downsized boosted spark-ignition direct-injection (SIDI) engine has proven to be one of the most promising concepts to improve vehicle fuel economy. However, the boosted engine is typically designed at a lower geometric compression ratio (CR) due to the increased knock tendency in comparison to naturally aspirated engines, limiting the potential of improving fuel economy. On the other hand, cooled exhaust gas recirculation (EGR) has drawn attention due to the potential to suppress knock and improve fuel economy. Combing the effects of boosting, increased CR and cooled EGR to further improve fuel economy within acceptable knock tolerance has been investigated using a 2.0 L downsized boosted SIDI engine over a wide range of engine operating conditions from 1000 rpm to 3000 rpm at low to high loads. To clarify the mechanism of this complicated effects, the first law of thermodynamics analysis was conducted with the inputs from GT-Power® engine simulation. Experiment results indicate that cooled EGR provides more brake thermal efficiency improvement than increasing geometric CR from 9.3 to 10.9. The benefit of brake thermal efficiency from the higher CR is limited to low load conditions. The attributes for improving brake thermal efficiency by cooled EGR include reduced heat transfer loss, reduced pumping work and increased ratio of specific heats for all the engine operating conditions, as well as higher degree of constant volume heat release only for the knock-limited high load conditions. The combined effects of 18–25% cooled EGR

  12. Investigation on Tensile Strength Ratio (TSR Specimen to Predict Moisture Sensitivity of Asphalt Pavements Mixture and Using Polymer to Reduce Moisture Damage

    Directory of Open Access Journals (Sweden)

    Mohammed Aziz Hameed Al-Shaybani

    2017-05-01

    Full Text Available Moisture damage of asphalt concrete is defined as losing the strength and Permanence caused by the active presence of moisture.The most common technique to reduce moisture damage is using modifiers with the asphalt binder or the aggregate.The goal of this study was to explore the effect of various modifiers of polymer on the moisture susceptibility mixture of asphaltic concrete pavement. Modifiers included in this research selected two kinds of polymers Crumb Rubber No 50 (CR No 50 and Methyl Methacrylates (MMA(which are available in the local markets in Iraq and have been used in three percentages for each type. These percentages are (5, 10 and 15% for (CR No 50 and (2.5, 5 and 7.5(% for (MMA.Each type of these polymers is blended with asphalt by wet process at constant blending times for a suitable range of temperatures. The experimental works showed that all polymers modified mixtures have indirect tensile strength higher than control asphalt mixtures, its about (2-15 %, dependent on different type of polymer and polymer concentration under predicted suitable blending time.Test results of indirect tensile strength indicated betterment in modifying the proprieties of mixture, the increased resistance mixture of asphalt concrete pavement versus moisture damage, and reduced the effect of water on asphalt concrete properties. The final result is the addition of (10% CR No 50 and (5% MMA to asphalt mixtures showed an improved mixture of asphalt concrete properties and produced strong mixtures for road construction.One model is predicted for tensile strength ratio [TSR]to estimate the effects of polymer modification on moisture susceptibility mixture of asphalt concrete.

  13. Waist-to-height ratio as index of cardiometabolic risk among the doctors

    Directory of Open Access Journals (Sweden)

    Miliva Mozaffor

    2017-12-01

    Full Text Available The aim of this study was to see the cardiometabolic risk among doctors using waist-to-height ratio index as tool. Cardiometabolic risk is an umbrella term that includes all the risk factors of diabetes and cardiovascular disease. The study was conducted among 195 doctors. According to waist-to-height ratio index 167 (85.6% doctors had cardiometabolic risk. Waist-to-height ratio index was found good (area under the curve >0.5, sensitivity 88.1%, specificity 23.2%, positive predictive value 53.9%, and negative predictive value 66.7% for their predictive value of cardiometabolic risk. Age grouping was done and found that no age group was free from cardiometabolic risk.

  14. Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

    Science.gov (United States)

    Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2016-08-07

    Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry.

    Science.gov (United States)

    Mozer, M C; Wolniewicz, R; Grimes, D B; Johnson, E; Kaushansky, H

    2000-01-01

    Competition in the wireless telecommunications industry is fierce. To maintain profitability, wireless carriers must control churn, which is the loss of subscribers who switch from one carrier to another.We explore techniques from statistical machine learning to predict churn and, based on these predictions, to determine what incentives should be offered to subscribers to improve retention and maximize profitability to the carrier. The techniques include logit regression, decision trees, neural networks, and boosting. Our experiments are based on a database of nearly 47,000 U.S. domestic subscribers and includes information about their usage, billing, credit, application, and complaint history. Our experiments show that under a wide variety of assumptions concerning the cost of intervention and the retention rate resulting from intervention, using predictive techniques to identify potential churners and offering incentives can yield significant savings to a carrier. We also show the importance of a data representation crafted by domain experts. Finally, we report on a real-world test of the techniques that validate our simulation experiments.

  16. Improving MJO Prediction and Simulation Using AGCM Coupled Ocean Model with Refined Vertical Resolution

    Science.gov (United States)

    Tu, Chia-Ying; Tseng, Wan-Ling; Kuo, Pei-Hsuan; Lan, Yung-Yao; Tsuang, Ben-Jei; Hsu, Huang-Hsiung

    2017-04-01

    Precipitation in Taiwan area is significantly influenced by MJO (Madden-Julian Oscillation) in the boreal winter. This study is therefore conducted by toggling the MJO prediction and simulation with a unique model structure. The one-dimensional TKE (Turbulence Kinetic Energy) type ocean model SIT (Snow, Ice, Thermocline) with refined vertical resolution near surface is able to resolve cool skin, as well as diurnal warm layer. SIT can simulate accurate SST and hence give precise air-sea interaction. By coupling SIT with ECHAM5 (MPI-Meteorology), CAM5 (NCAR) and HiRAM (GFDL), the MJO simulations in 20-yrs climate integrations conducted by three SIT-coupled AGCMs are significant improved comparing to those driven by prescribed SST. The horizontal resolutions in ECHAM5, CAM5 and HiRAM are 2-deg., 1-deg and 0.5-deg., respectively. This suggests that the improvement of MJO simulation by coupling SIT is AGCM-resolution independent. This study further utilizes HiRAM coupled SIT to evaluate its MJO forecast skill. HiRAM has been recognized as one of the best model for seasonal forecasts of hurricane/typhoon activity (Zhao et al., 2009; Chen & Lin, 2011; 2013), but was not as successful in MJO forecast. The preliminary result of the HiRAM-SIT experiment during DYNAMO period shows improved success in MJO forecast. These improvements of MJO prediction and simulation in both hindcast experiments and climate integrations are mainly from better-simulated SST diurnal cycle and diurnal amplitude, which is contributed by the refined vertical resolution near ocean surface in SIT. Keywords: MJO Predictability, DYNAMO

  17. FULLPROF as a new tool for flipping ratio analysis: further improvements

    International Nuclear Information System (INIS)

    Frontera, C.; Rodriguez-Carvajal, J.

    2004-01-01

    In the international workshop on polarized neutron for condensed matter investigation (Juelich, September 2002), we presented the implementations done in FULLPROF in order to introduce the ability of performing flipping ratio analysis. During this year we have modified the program in order to extend the initial features. We have tested these new implementations by re-analyzing flipping ratio data on Metrz-Nit (C 10 H 16 N 5 O 2 ) compound

  18. Better estimation of protein-DNA interaction parameters improve prediction of functional sites

    Directory of Open Access Journals (Sweden)

    O'Flanagan Ruadhan A

    2008-12-01

    Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

  19. Controlling effective aspect ratio and packing of clay with pH for improved gas barrier in nanobrick wall thin films.

    Science.gov (United States)

    Hagen, David A; Saucier, Lauren; Grunlan, Jaime C

    2014-12-24

    Polymer-clay thin films constructed via layer-by-layer (LbL) assembly, with a nanobrick wall structure (i.e., clay nanoplatelets as bricks surrounded by a polyelectrolyte mortar), are known to exhibit a high oxygen barrier. Further barrier improvement can be achieved by lowering the pH of the clay suspension in the polyethylenimine (PEI) and montmorillonite (MMT) system. In this case, the charge of the deposited PEI layer is increased in the clay suspension environment, which causes more clay to be deposited. At pH 4, MMT platelets deposit with near perfect ordering, observed with transmission electron microscopy, enabling a 5× improvement in the gas barrier for a 10 PEI/MMT bilayer thin film (85 nm) relative to the same film made with pH 10 MMT. This improved gas barrier approaches that achieved with much higher aspect ratio vermiculite clay. In essence, lower pH is generating a higher effective aspect ratio for MMT due to greater induced surface charge in the PEI layers, which causes heavier clay deposition. These flexible, transparent nanocoatings have a wide range of possible applications, from food and electronics packaging to pressurized bladders.

  20. Soil to plant transfer of radionuclides: predicting the fate of multiple radioisotopes in plants

    International Nuclear Information System (INIS)

    Willey, Neil J.

    2014-01-01

    Predicting soil-to-plant transfer of radionuclides is restricted by the range of species for which concentration ratios (CRs) have been measured. Here the radioecological utility of meta-analyses of phylogenetic effects on alkali earth metals will be explored for applications such as ‘gap-filling’ of CRs, the identification of sentinel biomonitor plants and the selection of taxa for phytoremediation of radionuclide contaminated soils. REML modelling of extensive CR/concentration datasets shows that the concentrations in plants of Ca, Mg and Sr are significantly influenced by phylogeny. Phylogenetic effects of these elements are shown here to be similar. Ratios of Ca/Mg and Ca/Sr are known to be quite stable in plants so, assuming that Sr/Ra ratios are stable, phylogenetic effects and estimated mean CRs are used to predict Ra CRs for groups of plants with few measured data. Overall, there are well quantified plant variables that could contribute significantly to improving predictions of the fate radioisotopes in the soil-plant system

  1. Late Financial Distress Process Stages and Financial Ratios

    DEFF Research Database (Denmark)

    Sormunen, Nina; Laitinen, Teija

    2012-01-01

    stage affects the classification ability of single financial ratios and financial distress prediction models in short-term financial distress prediction. The study shows that the auditor's GC task could be supported by paying attention to the financial distress process stage. The implications...... of these findings for auditors and every stakeholder of business firms are considered....

  2. Combining specificity determining and conserved residues improves functional site prediction

    Directory of Open Access Journals (Sweden)

    Gelfand Mikhail S

    2009-06-01

    Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

  3. Improvement and Simulation of THOR Formula with Yaw Angle

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2014-04-01

    Full Text Available The THOR formula is widely used in the investigation of vulnerability and effectiveness of weapon system, however, its application was limited by the small slenderness ratio and limited materials of target. In order to investigate the damage effect of KE-rod warhead, this paper, basing on the classic THOR formula, focused on improving the formula of residual velocity and residual mass. The improved THOR model could predict the residual velocity and residual mass of KE-rod penetration in the complex conditions, and the predictions were found to be consistent with the experimental numerical results in the literatures. As the experimental data is limited, for the better validation of the improved formula, the paper investigated further research and verification of the improvement THOR formula with numerical simulation. Since the experimental data are limited for hypervelocity impact, comparisons of results between M-THOR with experimental and numerical data were widely preceded. The error is less than 4.8% for the predicted residual velocity while 5.4% for predicted residual velocity. The effect of yaw angle in the modified THOR formula was also found to agree quite well with the reference.

  4. Wakes behind surface-mounted obstacles: Impact of aspect ratio, incident angle, and surface roughness

    Science.gov (United States)

    Tobin, Nicolas; Chamorro, Leonardo P.

    2018-03-01

    The so-called wake-moment coefficient C˜h and lateral wake deflection of three-dimensional windbreaks are explored in the near and far wake. Wind-tunnel experiments were performed to study the functional dependence of C˜h with windbreak aspect ratio, incidence angle, and the ratio of the windbreak height and surface roughness (h /z0 ). Supported with the data, we also propose basic models for the wake deflection of the windbreak in the near and far fields. The near-wake model is based on momentum conservation considering the drag on the windbreak, whereas the far-wake counterpart is based on existing models for wakes behind surface-mounted obstacles. Results show that C˜h does not change with windbreak aspect ratios of 10 or greater; however, it may be lower for an aspect ratio of 5. C˜h is found to change roughly with the cosine of the incidence angle, and to depend strongly on h /z0 . The data broadly support the proposed wake-deflection models, though better predictions could be made with improved knowledge of the windbreak drag coefficient.

  5. Regional Longitudinal Deformation Improves Prediction of Ventricular Tachyarrhythmias in Patients With Heart Failure With Reduced Ejection Fraction

    DEFF Research Database (Denmark)

    Biering-Sørensen, Tor; Knappe, Dorit; Pouleur, Anne-Catherine

    2017-01-01

    BACKGROUND: Left ventricular dysfunction is a known predictor of ventricular arrhythmias. We hypothesized that measures of regional longitudinal deformation by speckle-tracking echocardiography predict ventricular tachyarrhythmias and provide incremental prognostic information over clinical...... in the model, only a decreasing myocardial function in the inferior myocardial wall predicted VT/VF (hazard ratio, 1.05 [1.00-1.11]; P=0.039). Only strain obtained from the inferior myocardial wall provided incremental prognostic information for VT/VF over clinical and echocardiographic parameters (C statistic...... 0.71 versus 0.69; P=0.005). CONCLUSIONS: Assessment of regional longitudinal myocardial deformation in the inferior region provided incremental prognostic information over clinical and echocardiographic risk factors in predicting ventricular tachyarrhythmias. CLINICAL TRIAL REGISTRATION: URL: http...

  6. Improved methods of online monitoring and prediction in condensate and feed water system of nuclear power plant

    International Nuclear Information System (INIS)

    Wang, Hang; Peng, Min-jun; Wu, Peng; Cheng, Shou-yu

    2016-01-01

    Highlights: • Different methods for online monitoring and diagnosis are summarized. • Numerical simulation modeling of condensate and feed water system in nuclear power plant are done by FORTRAN programming. • Integrated online monitoring and prediction methods have been developed and tested. • Online monitoring module, fault diagnosis module and trends prediction module can be verified with each other. - Abstract: Faults or accidents may occur in a nuclear power plant (NPP), but it is hard for operators to recognize the situation and take effective measures quickly. So, online monitoring, diagnosis and prediction (OMDP) is used to provide enough information to operators and improve the safety of NPPs. In this paper, distributed conservation equation (DCE) and artificial immunity system (AIS) are proposed for online monitoring and diagnosis. On this basis, quantitative simulation models and interactive database are combined to predict the trends and severity of faults. The effectiveness of OMDP in improving the monitoring and prediction of condensate and feed water system (CFWS) was verified through simulation tests.

  7. Prediction and moderation of improvement in cognitive-behavioral and psychodynamic psychotherapy for panic disorder.

    Science.gov (United States)

    Chambless, Dianne L; Milrod, Barbara; Porter, Eliora; Gallop, Robert; McCarthy, Kevin S; Graf, Elizabeth; Rudden, Marie; Sharpless, Brian A; Barber, Jacques P

    2017-08-01

    To identify variables predicting psychotherapy outcome for panic disorder or indicating which of 2 very different forms of psychotherapy-panic-focused psychodynamic psychotherapy (PFPP) or cognitive-behavioral therapy (CBT)-would be more effective for particular patients. Data were from 161 adults participating in a randomized controlled trial (RCT) including these psychotherapies. Patients included 104 women; 118 patients were White, 33 were Black, and 10 were of other races; 24 were Latino(a). Predictors/moderators measured at baseline or by Session 2 of treatment were used to predict change on the Panic Disorder Severity Scale (PDSS). Higher expectancy for treatment gains (Credibility/Expectancy Questionnaire d = -1.05, CI 95% [-1.50, -0.60]), and later age of onset (d = -0.65, CI 95% [-0.98, -0.32]) were predictive of greater change. Both variables were also significant moderators: patients with low expectancy of improvement improved significantly less in PFPP than their counterparts in CBT, whereas this was not the case for patients with average or high levels of expectancy. When patients had an onset of panic disorder later in life (≥27.5 years old), they fared as well in PFPP as CBT. In contrast, at low and mean levels of onset age, CBT was the more effective treatment. Predictive variables suggest possibly fruitful foci for improvement of treatment outcome. In terms of moderation, CBT was the more consistently effective treatment, but moderators identified some patients who would do as well in PFPP as in CBT, thereby widening empirically supported options for treatment of this disorder. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.

    Science.gov (United States)

    van Dijk, Lisanne V; Brouwer, Charlotte L; van der Schaaf, Arjen; Burgerhof, Johannes G M; Beukinga, Roelof J; Langendijk, Johannes A; Sijtsema, Nanna M; Steenbakkers, Roel J H M

    2017-02-01

    Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER 12m ) and sticky saliva (STIC 12m ) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XER base ) or sticky saliva (STIC base ) scores. The purpose is to improve prediction of XER 12m and STIC 12m with patient-specific characteristics, based on CT image biomarkers (IBMs). Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping. The prediction of XER 12m could be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XER base . For STIC 12m , the IBM maximum CT intensity of the submandibular gland was selected in addition to STIC base and mean dose to submandibular glands. Prediction of XER 12m and STIC 12m was improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  9. Identifying Malignant Pleural Effusion by A Cancer Ratio (Serum LDH: Pleural Fluid ADA Ratio).

    Science.gov (United States)

    Verma, Akash; Abisheganaden, John; Light, R W

    2016-02-01

    We studied the diagnostic potential of serum lactate dehydrogenase (LDH) in malignant pleural effusion. Retrospective analysis of patients hospitalized with exudative pleural effusion in 2013. Serum LDH and serum LDH: pleural fluid ADA ratio was significantly higher in cancer patients presenting with exudative pleural effusion. In multivariate logistic regression analysis, pleural fluid ADA was negatively correlated 0.62 (0.45-0.85, p = 0.003) with malignancy, whereas serum LDH 1.02 (1.0-1.03, p = 0.004) and serum LDH: pleural fluid ADA ratio 0.94 (0.99-1.0, p = 0.04) was correlated positively with malignant pleural effusion. For serum LDH: pleural fluid ADA ratio, a cut-off level of >20 showed sensitivity, specificity of 0.98 (95 % CI 0.92-0.99) and 0.94 (95 % CI 0.83-0.98), respectively. The positive likelihood ratio was 32.6 (95 % CI 10.7-99.6), while the negative likelihood ratio at this cut-off was 0.03 (95 % CI 0.01-0.15). Higher serum LDH and serum LDH: pleural fluid ADA ratio in patients presenting with exudative pleural effusion can distinguish between malignant and non-malignant effusion on the first day of hospitalization. The cut-off level for serum LDH: pleural fluid ADA ratio of >20 is highly predictive of malignancy in patients with exudative pleural effusion (whether lymphocytic or neutrophilic) with high sensitivity and specificity.

  10. High ratio of triglycerides to hdl-cholesterol predicts extensive coronary disease

    Directory of Open Access Journals (Sweden)

    Protasio Lemos da Luz

    2008-01-01

    Full Text Available An abnormal ratio of triglycerides to HDL-cholesterol (TG/HDL-c indicates an atherogenic lipid profile and a risk for the development of coronary disease. OBJECTIVE: To investigate the association between lipid levels, specifically TG/HDL-c, and the extent of coronary disease. METHODS: High-risk patients (n = 374 submitted for coronary angiography had their lipid variables measured and coronary disease extent scored by the Friesinger index. RESULTS: The subjects consisted of 220 males and 154 females, age 57.2 ± 11.1 years, with total cholesterol of 210± 50.3 mg/dL, triglycerides of 173.8 ± 169.8 mg/dL, HDL-cholesterol (HDL-c of 40.1 ± 12.8 mg/dL, LDL-cholesterol (LDL-c of 137.3 ± 46.2 mg/dL, TG/HDL-c of 5.1 ± 5.3, and a Friesinger index of 6.6 ± 4.7. The relationship between the extent of coronary disease (dichotomized by a Friesenger index of 5 and lipid levels (normal vs. abnormal was statistically significant for the following: triglycerides, odds ratio of 2.02 (1.31-3.1; p = 0.0018; HDL-c, odds ratio of 2.21 (1.42-3.43; p = 0.0005; and TG/HDL-c, odds ratio of 2.01(1.30-3.09; p = 0.0018. However, the relationship was not significant between extent of coronary disease and total cholesterol [1.25 (0.82-1.91; p = 0.33] or LDL-c [1.47 (0.96-2.25; p = 0.0842]. The chi-square for linear trends for Friesinger > 4 and lipid quartiles was statistically significant for triglycerides (p = 0.0017, HDL-c (p = 0.0001, and TG/HDL-c (p = 0.0018, but not for total cholesterol (p = 0.393 or LDL-c (p = 0.0568. The multivariate analysis by logistic regression OR gave 1.3 ± 0.79 (p = .0001 for TG/HDL-c, 0.779 ± 0.074 (p = .0001 for HDL-c, and 1.234 ± 0.097 (p = 0.03 for LDL. Analysis of receiver operating characteristic curves showed that only TG/HDL-c and HDL-c were useful for detecting extensive coronary disease, with the former more strongly associated with disease. CONCLUSIONS: Although some lipid variables were associated with the extent of

  11. Improving Flood Predictions in Data-Scarce Basins

    Science.gov (United States)

    Vimal, Solomon; Zanardo, Stefano; Rafique, Farhat; Hilberts, Arno

    2017-04-01

    Flood modeling methodology at Risk Management Solutions Ltd. has evolved over several years with the development of continental scale flood risk models spanning most of Europe, the United States and Japan. Pluvial (rain fed) and fluvial (river fed) flood maps represent the basis for the assessment of regional flood risk. These maps are derived by solving the 1D energy balance equation for river routing and 2D shallow water equation (SWE) for overland flow. The models are run with high performance computing and GPU based solvers as the time taken for simulation is large in such continental scale modeling. These results are validated with data from authorities and business partners, and have been used in the insurance industry for many years. While this methodology has been proven extremely effective in regions where the quality and availability of data are high, its application is very challenging in other regions where data are scarce. This is generally the case for low and middle income countries, where simpler approaches are needed for flood risk modeling and assessment. In this study we explore new methods to make use of modeling results obtained in data-rich contexts to improve predictive ability in data-scarce contexts. As an example, based on our modeled flood maps in data-rich countries, we identify statistical relationships between flood characteristics and topographic and climatic indicators, and test their generalization across physical domains. Moreover, we apply the Height Above Nearest Drainage (HAND)approach to estimate "probable" saturated areas for different return period flood events as functions of basin characteristics. This work falls into the well-established research field of Predictions in Ungauged Basins.

  12. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  13. Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.

    Science.gov (United States)

    Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

    2015-06-12

    Docking scoring functions can be used to predict the strength of protein-ligand binding. It is widely believed that training a scoring function with low-quality data is detrimental for its predictive performance. Nevertheless, there is a surprising lack of systematic validation experiments in support of this hypothesis. In this study, we investigated to which extent training a scoring function with data containing low-quality structural and binding data is detrimental for predictive performance. We actually found that low-quality data is not only non-detrimental, but beneficial for the predictive performance of machine-learning scoring functions, though the improvement is less important than that coming from high-quality data. Furthermore, we observed that classical scoring functions are not able to effectively exploit data beyond an early threshold, regardless of its quality. This demonstrates that exploiting a larger data volume is more important for the performance of machine-learning scoring functions than restricting to a smaller set of higher data quality.

  14. Improved prediction for the mass of the W boson in the NMSSM

    International Nuclear Information System (INIS)

    Staal, O.; Zeune, L.

    2015-10-01

    Electroweak precision observables, being highly sensitive to loop contributions of new physics, provide a powerful tool to test the theory and to discriminate between different models of the underlying physics. In that context, the W boson mass, M W , plays a crucial role. The accuracy of the M W measurement has been significantly improved over the last years, and further improvement of the experimental accuracy is expected from future LHC measurements. In order to fully exploit the precise experimental determination, an accurate theoretical prediction for M W in the Standard Model (SM) and extensions of it is of central importance. We present the currently most accurate prediction for the W boson mass in the Next-to-Minimal Supersymmetric extension of the Standard Model (NMSSM), including the full one-loop result and all available higher-order corrections of SM and SUSY type. The evaluation of M W is performed in a flexible framework, which facilitates the extension to other models beyond the SM. We show numerical results for the W boson mass in the NMSSM, focussing on phenomenologically interesting scenarios, in which the Higgs signal can be interpreted as the lightest or second lightest CP-even Higgs boson of the NMSSM. We find that, for both Higgs signal interpretations, the NMSSM M W prediction is well compatible with the measurement. We study the SUSY contributions to M W in detail and investigate in particular the genuine NMSSM effects from the Higgs and neutralino sectors.

  15. The transverse Poisson's ratio of composites.

    Science.gov (United States)

    Foye, R. L.

    1972-01-01

    An expression is developed that makes possible the prediction of Poisson's ratio for unidirectional composites with reference to any pair of orthogonal axes that are normal to the direction of the reinforcing fibers. This prediction appears to be a reasonable one in that it follows the trends of the finite element analysis and the bounding estimates, and has the correct limiting value for zero fiber content. It can only be expected to apply to composites containing stiff, circular, isotropic fibers bonded to a soft matrix material.

  16. Use of net reclassification improvement (NRI method confirms the utility of combined genetic risk score to predict type 2 diabetes.

    Directory of Open Access Journals (Sweden)

    Claudia H T Tam

    Full Text Available BACKGROUND: Recent genome-wide association studies (GWAS identified more than 70 novel loci for type 2 diabetes (T2D, some of which have been widely replicated in Asian populations. In this study, we investigated their individual and combined effects on T2D in a Chinese population. METHODOLOGY: We selected 14 single nucleotide polymorphisms (SNPs in T2D genes relating to beta-cell function validated in Asian populations and genotyped them in 5882 Chinese T2D patients and 2569 healthy controls. A combined genetic score (CGS was calculated by summing up the number of risk alleles or weighted by the effect size for each SNP under an additive genetic model. We tested for associations by either logistic or linear regression analysis for T2D and quantitative traits, respectively. The contribution of the CGS for predicting T2D risk was evaluated by receiver operating characteristic (ROC analysis and net reclassification improvement (NRI. RESULTS: We observed consistent and significant associations of IGF2BP2, WFS1, CDKAL1, SLC30A8, CDKN2A/B, HHEX, TCF7L2 and KCNQ1 (8.5×10(-18ratios ranging from 1.07 to 2.09. The 8 significant SNPs exhibited joint effect on increasing T2D risk, fasting plasma glucose and use of insulin therapy as well as reducing HOMA-β, BMI, waist circumference and younger age of diagnosis of T2D. The addition of CGS marginally increased AUC (2% but significantly improved the predictive ability on T2D risk by 11.2% and 11.3% for unweighted and weighted CGS, respectively using the NRI approach (P<0.001. CONCLUSION: In a Chinese population, the use of a CGS of 8 SNPs modestly but significantly improved its discriminative ability to predict T2D above and beyond that attributed to clinical risk factors (sex, age and BMI.

  17. Predictions of nitrogen oxides production in diffusion turbulent flames; Predictions de la production des oxydes d`azote dans les flammes turbulentes de diffusion

    Energy Technology Data Exchange (ETDEWEB)

    Sanders, H.; Gokalp, I. [Centre National de la Recherche Scientifique (CNRS), 45 - Orleans-la-Source (France). Laboratoire de Combustion Systemes Reactifs

    1996-12-31

    The suitability of the turbulent combustion flamelets model in order to predict the index of NO{sub x} production in turbulent flames of hydrogen diffusion is analyzed. In the flamelet approach, the turbulent flame is equivalent to a group of laminar flames submitted to a mechanical stretching which generates a chemical disequilibrium. This effect can be described by the stretching or by the scalar dissipation ratio. A numerical modeling is performed in order to evaluate the advantages of both approaches and to compare the behaviour of the NO{sub x} emission index with the experiments of Chen and Driscoll. This study shows that predictions of NO{sub x} emission indexes have a correct behaviour with respect to the Damkoehler number only when the scalar dissipation ratio is used as a parameter to describe the chemical state outside equilibrium. Predictions of the flamelet models are improving when the Damkoehler number increases. On the other hand, the absolute NO{sub x} concentrations are overestimated and can be due to the effects of differential diffusion. (J.S.) 14 refs.

  18. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    International Nuclear Information System (INIS)

    Rattá, G.A.; Vega, J.; Murari, A.

    2012-01-01

    Highlights: ► A new signal selection methodology to improve disruption prediction is reported. ► The approach is based on Genetic Algorithms. ► An advanced predictor has been created with the new set of signals. ► The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called “Advanced Predictor Of Disruptions” (APODIS), developed for the “Joint European Torus” (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals’ parameters in order to maximize the performance of the predictor is reported. The approach is based on “Genetic Algorithms” (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  19. Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov

    2016-02-25

    Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

  20. Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

    International Nuclear Information System (INIS)

    Hao, Ming; Wang, Yanli; Bryant, Stephen H.

    2016-01-01

    Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

  1. Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

    Science.gov (United States)

    Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

    2018-02-19

    Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

  2. Classifying organic materials by oxygen-to-carbon elemental ratio to predict the activation regime of Cloud Condensation Nuclei (CCN

    Directory of Open Access Journals (Sweden)

    M. Kuwata

    2013-05-01

    Full Text Available The governing highly soluble, slightly soluble, or insoluble activation regime of organic compounds as cloud condensation nuclei (CCN was examined as a function of oxygen-to-carbon elemental ratio (O : C. New data were collected for adipic, pimelic, suberic, azelaic, and pinonic acids. Secondary organic materials (SOMs produced by α-pinene ozonolysis and isoprene photo-oxidation were also included in the analysis. The saturation concentrations C of the organic compounds in aqueous solutions served as the key parameter for delineating regimes of CCN activation, and the values of C were tightly correlated to the O : C ratios. The highly soluble, slightly soluble, and insoluble regimes of CCN activation were found to correspond to ranges of [O : C] > 0.6, 0.2 < [O : C] < 0.6, and [O : C] < 0.2, respectively. These classifications were evaluated against CCN activation data of isoprene-derived SOM (O : C = 0.69–0.72 and α-pinene-derived SOM (O : C = 0.38–0.48. Isoprene-derived SOM had highly soluble activation behavior, consistent with its high O : C ratio. For α-pinene-derived SOM, although CCN activation can be modeled as a highly soluble mechanism, this behavior was not predicted by the O : C ratio, for which a slightly soluble mechanism was anticipated. Complexity in chemical composition, resulting in continuous water uptake and the absence of a deliquescence transition that can thermodynamically limit CCN activation, might explain the difference in the behavior of α-pinene-derived SOM compared to that of pure organic compounds. The present results suggest that atmospheric particles dominated by hydrocarbon-like organic components do not activate (i.e., insoluble regime whereas those dominated by oxygenated organic components activate (i.e., highly soluble regime for typical atmospheric cloud life cycles.

  3. An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Nisansala Wijekoon

    2015-07-01

    Full Text Available The primary objective of this study is to develop an integrated model to predict corporate failure of listed companies in Sri Lanka. The logistic regression analysis was employed to a data set of 70 matched-pairs of failed and non-failed companies listed in the Colombo Stock Exchange (CSE in Sri Lanka over the period 2002 to 2010. A total of fifteen financial ratios and eight corporate governance variables were used as predictor variables of corporate failure. Analysis of the statistical testing results indicated that model consists with both corporate governance variables and financial ratios improved the prediction accuracy to reach 88.57 per cent one year prior to failure. Furthermore, predictive accuracy of this model in all three years prior to failure is above 80 per cent. Hence model is robust in obtaining accurate results for up to three years prior to failure. It was further found that two financial ratios, working capital to total assets and cash flow from operating activities to total assets, and two corporate governance variables, outside director ratio and company audit committee are having more explanatory power to predict corporate failure. Therefore, model developed in this study can assist investors, managers, shareholders, financial institutions, auditors and regulatory agents in Sri Lanka to forecast corporate failure of listed companies.

  4. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Directory of Open Access Journals (Sweden)

    Michael F Sloma

    2017-11-01

    Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  5. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Science.gov (United States)

    Sloma, Michael F; Mathews, David H

    2017-11-01

    Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  6. Improving the Accuracy of a Heliocentric Potential (HCP Prediction Model for the Aviation Radiation Dose

    Directory of Open Access Journals (Sweden)

    Junga Hwang

    2016-12-01

    Full Text Available The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs, flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA. However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015. In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1 real-time daily sunspot assessments, (2 predictions of the daily HCP by our prediction algorithm, and (3 calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

  7. Ultrasonographic elastography of thyroid nodules: Is adding strain ratio to colour mapping better?

    International Nuclear Information System (INIS)

    Chong, Y.; Shin, J.H.; Ko, E.S.; Han, B.-K.

    2013-01-01

    Aim: To determine the diagnostic performance of colour mapping and strain ratio for characterizing malignant thyroid nodules on ultrasonographic (US) elastography. Materials and methods: The study was approved by the institutional review board and written informed consent was obtained. One hundred and thirty-one patients with 142 thyroid nodules >0.5 cm were prospectively enrolled between July 2010 and January 2011. Seven radiologists performed US elastography (iU22 Vision 2010; Philips, Seattle, WA, USA) using colour mapping and strain ratio for thyroid nodules blinded to the cytopathological results. Diagnostic performances of colour mapping alone, strain ratio alone, colour mapping and strain ratio, and colour mapping or strain ratio were compared using receiver operating characteristic (ROC) curve analysis. Results: Of the 142 nodules, 69 (48.6%) were benign and 73 (51.4%) were malignant. Colour mapping of elastography showed a more frequent blue colour in malignant nodules than in benign nodules (65.8% versus 24.6%, p < 0.0001). A higher ratio than 1.21 as the best cut-off value was found in 65.8% of malignant nodules and 46.4% of benign nodules (p = 0.030). Area under the ROC curve (AUC) of colour mapping alone was significantly greater than that of colour mapping or strain ratio (AUC = 0.706 versus AUC = 0.63, p = 0.0195) and similar to that of colour mapping and strain ratio (AUC = 0.673, p = 0.1364). Conclusion: US elastography is helpful to predict malignant thyroid nodules. However, adding strain ratio to colour mapping does not improve performance compared to colour mapping alone

  8. Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    2017-03-01

    Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

  9. Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

    Directory of Open Access Journals (Sweden)

    Otto Savolainen

    Full Text Available The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D risk that would improve prediction of T2D over current risk markers.Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629. Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D.Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA, smoking, serum adiponectin alone, and in combination with metabolomics had the largest areas under the curve (AUC (0.794 (95% confidence interval [0.738-0.850] and 0.808 [0.749-0.867] respectively, with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]. Prediction based on non-blood based measures was 0.638 [0.565-0.711].Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

  10. Influence of La/W ratio on electrical conductivity of lanthanum tungstate with high La/W ratio

    International Nuclear Information System (INIS)

    Kojo, Gen; Shono, Yohei; Ushiyama, Hiroshi; Oshima, Yoshito; Otomo, Junichiro

    2017-01-01

    The proton-conducting properties of lanthanum tungstates (LWOs) with high La/W ratios were investigated using electrochemical measurements and quantum chemical calculations. Single phases of LWOs with high La/W ratios (6.3≤La/W≤6.7) were synthesized by high-temperature sintering at around 1700 °C. The electrical conductivity of LWO increased with increasing La/W ratio in the single-phase region. The LWO synthesized at the optimum sintering temperature and time, and with the optimum La/W ratio gave the maximum conductivity, i.e., 2.7×10 −3 S cm −1 with La/W=6.7 at 500 °C. Density functional theory calculations, using the nudged elastic band method, were performed to investigate the proton diffusion barrier. The results suggest that the proton diffusion paths around La sites have the lowest proton diffusion barrier. These findings improve our understanding of LWO synthesis and the proton-conducting mechanism and provide a strategy for improving proton conduction in LWOs. - Graphical abstract: The LWOs with high La/W ratios were synthesized for the first time. The optimum La/W ratio gave the maximum conductivity with La/W=6.7 at 500 °C. The proton diffusion paths were also considered with density functional theory calculations. - Highlights: • The proton-conducting properties of lanthanum tungstates (LWOs) were investigated. • Single phase LWOs with high La/W ratios (6.3≤La/W≤6.7) were synthesized successfully. • LWOs with the high La/W ratios showed high proton conductivity. • The DFT calculation suggested the lowest proton diffusion barrier in the path around La sites.

  11. Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

    2018-02-01

    Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

  12. Improved Dutch Roll Approximation for Hypersonic Vehicle

    Directory of Open Access Journals (Sweden)

    Liang-Liang Yin

    2014-06-01

    Full Text Available An improved dutch roll approximation for hypersonic vehicle is presented. From the new approximations, the dutch roll frequency is shown to be a function of the stability axis yaw stability and the dutch roll damping is mainly effected by the roll damping ratio. In additional, an important parameter called roll-to-yaw ratio is obtained to describe the dutch roll mode. Solution shows that large-roll-to-yaw ratio is the generate character of hypersonic vehicle, which results the large error for the practical approximation. Predictions from the literal approximations derived in this paper are compared with actual numerical values for s example hypersonic vehicle, results show the approximations work well and the error is below 10 %.

  13. On the Use of Backward Difference Formulae to Improve the Prediction of Direction in Market Related Data

    Directory of Open Access Journals (Sweden)

    E. Momoniat

    2013-01-01

    Full Text Available The use of a BDF method as a tool to correct the direction of predictions made using curve fitting techniques is investigated. Random data is generated in such a fashion that it has the same properties as the data we are modelling. The data is assumed to have “memory” such that certain information imbedded in the data will remain within a certain range of points. Data within this period where “memory” exists—say at time steps t1,t2,…,tn—is curve-fitted to produce a prediction at the next discrete time step, tn+1. In this manner a vector of predictions is generated and converted into a discrete ordinary differential representing the gradient of the data. The BDF method implemented with this lower order approximation is used as a means of improving upon the direction of the generated predictions. The use of the BDF method in this manner improves the prediction of the direction of the time series by approximately 30%.

  14. ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins

    Directory of Open Access Journals (Sweden)

    Raghava Gajendra PS

    2008-11-01

    Full Text Available Abstract Background The expansion of raw protein sequence databases in the post genomic era and availability of fresh annotated sequences for major localizations particularly motivated us to introduce a new improved version of our previously forged eukaryotic subcellular localizations prediction method namely "ESLpred". Since, subcellular localization of a protein offers essential clues about its functioning, hence, availability of localization predictor would definitely aid and expedite the protein deciphering studies. However, robustness of a predictor is highly dependent on the superiority of dataset and extracted protein attributes; hence, it becomes imperative to improve the performance of presently available method using latest dataset and crucial input features. Results Here, we describe augmentation in the prediction performance obtained for our most popular ESLpred method using new crucial features as an input to Support Vector Machine (SVM. In addition, recently available, highly non-redundant dataset encompassing three kingdoms specific protein sequence sets; 1198 fungi sequences, 2597 from animal and 491 plant sequences were also included in the present study. First, using the evolutionary information in the form of profile composition along with whole and N-terminal sequence composition as an input feature vector of 440 dimensions, overall accuracies of 72.7, 75.8 and 74.5% were achieved respectively after five-fold cross-validation. Further, enhancement in performance was observed when similarity search based results were coupled with whole and N-terminal sequence composition along with profile composition by yielding overall accuracies of 75.9, 80.8, 76.6% respectively; best accuracies reported till date on the same datasets. Conclusion These results provide confidence about the reliability and accurate prediction of SVM modules generated in the present study using sequence and profile compositions along with similarity search

  15. Breast calcifications. A standardized mammographic reporting and data system to improve positive predictive value

    International Nuclear Information System (INIS)

    Perugini, G.; Bonzanini, B.; Valentino, C.

    1999-01-01

    The purpose of this work is to investigate the usefulness of a standardized reporting and data system in improving the positive predictive value of mammography in breast calcifications. Using the Breast Imaging Reporting and Data System lexicon developed by the American College of Radiology, it is defined 5 descriptive categories of breast calcifications and classified diagnostic suspicion of malignancy on a 3-grade scale (low, intermediate and high). Two radiologists reviewed 117 mammographic studies selected from those of the patients submitted to surgical biopsy for mammographically detected calcifications from January 1993 to December 1997, and classified them according to the above criteria. The positive predictive value was calculated for all examinations and for the stratified groups. Defining a standardized system for assessing and describing breast calcifications helps improve the diagnostic accuracy of mammography in clinical practice [it

  16. Improving the Ar I and II branching ratio calibration method: Monte Carlo simulations of effects from photon scattering/reflecting in hollow cathodes

    Science.gov (United States)

    Lawler, J. E.; Den Hartog, E. A.

    2018-03-01

    The Ar I and II branching ratio calibration method is discussed with the goal of improving the technique. This method of establishing a relative radiometric calibration is important in ongoing research to improve atomic transition probabilities for quantitative spectroscopy in astrophysics and other fields. Specific suggestions are presented along with Monte Carlo simulations of wavelength dependent effects from scattering/reflecting of photons in a hollow cathode.

  17. A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

    Science.gov (United States)

    Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2013-09-01

    Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

  18. Prediction of Impending Type 1 Diabetes through Automated Dual-Label Measurement of Proinsulin:C-Peptide Ratio.

    Directory of Open Access Journals (Sweden)

    Annelien Van Dalem

    Full Text Available The hyperglycemic clamp test, the gold standard of beta cell function, predicts impending type 1 diabetes in islet autoantibody-positive individuals, but the latter may benefit from less invasive function tests such as the proinsulin:C-peptide ratio (PI:C. The present study aims to optimize precision of PI:C measurements by automating a dual-label trefoil-type time-resolved fluorescence immunoassay (TT-TRFIA, and to compare its diagnostic performance for predicting type 1 diabetes with that of clamp-derived C-peptide release.Between-day imprecision (n = 20 and split-sample analysis (n = 95 were used to compare TT-TRFIA (AutoDelfia, Perkin-Elmer with separate methods for proinsulin (in-house TRFIA and C-peptide (Elecsys, Roche. High-risk multiple autoantibody-positive first-degree relatives (n = 49; age 5-39 were tested for fasting PI:C, HOMA2-IR and hyperglycemic clamp and followed for 20-57 months (interquartile range.TT-TRFIA values for proinsulin, C-peptide and PI:C correlated significantly (r2 = 0.96-0.99; P<0.001 with results obtained with separate methods. TT-TRFIA achieved better between-day %CV for PI:C at three different levels (4.5-7.1 vs 6.7-9.5 for separate methods. In high-risk relatives fasting PI:C was significantly and inversely correlated (rs = -0.596; P<0.001 with first-phase C-peptide release during clamp (also with second phase release, only available for age 12-39 years; n = 31, but only after normalization for HOMA2-IR. In ROC- and Cox regression analysis, HOMA2-IR-corrected PI:C predicted 2-year progression to diabetes equally well as clamp-derived C-peptide release.The reproducibility of PI:C benefits from the automated simultaneous determination of both hormones. HOMA2-IR-corrected PI:C may serve as a minimally invasive alternative to the more tedious hyperglycemic clamp test.

  19. Improvement in R{sub off}/R{sub on} ratio and reset current via combining compliance current with multilayer structure in tantalum oxide-based RRAM

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaorong; Feng, Jie [Shanghai Jiao Tong University, Key Laboratory for Thin Film and Microfabrication of Ministry of Education, Department of Micro/Nano Electronics, Shanghai (China)

    2015-07-15

    Improvements in the R{sub off}/R{sub on} ratio and reset current are required prior to the practical application of RRAM. To achieve this improvement, tantalum oxide-based RRAM devices with multilayer structure (bi-layer and tri-layer) were fabricated and various compliance currents were adopted. The reset current of 40 μA was observed; the R{sub off}/R{sub on} ratio increased to more than 20 in the tri-layer structure device. Resistance changes in two types of devices under voltage pulses with different pulse width were also conducted. The tri-layer device exhibited lower reset voltage and higher R{sub off}/R{sub on} ratio than the bi-layer device under voltage pulses. X-ray photoelectron spectroscopy demonstrated the formation of Ta{sub 2}O{sub 5} via plasma oxidation, and there was an oxygen gradient in the multilayer devices. The results demonstrated that the tri-layer structure with oxygen gradient was an effective method for achieving better device performance. Additionally, it is implied that reasonable control of the proportion of TaO{sub 2} and Ta{sub 2}O{sub 5} and compliance current can improve device performance. (orig.)

  20. A Predictive-Control-Based Over-Modulation Method for Conventional Matrix Converters

    DEFF Research Database (Denmark)

    Zhang, Guanguan; Yang, Jian; Sun, Yao

    2018-01-01

    To increase the voltage transfer ratio of the matrix converter and improve the input/output current performance simultaneously, an over-modulation method based on predictive control is proposed in this paper, where the weighting factor is selected by an automatic adjusting mechanism, which is able...... to further enhance the system performance promptly. This method has advantages like the maximum voltage transfer ratio can reach 0.987 in the experiments; the total harmonic distortion of the input and output current are reduced, and the losses in the matrix converter are decreased. Moreover, the specific...

  1. Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

    Science.gov (United States)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

  2. Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

    Energy Technology Data Exchange (ETDEWEB)

    Tucker, Susan L., E-mail: sltucker@mdanderson.org [Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li Minghuan [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Xu Ting; Gomez, Daniel [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yuan Xianglin [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China); Yu Jinming [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Liu Zhensheng; Yin Ming; Guan Xiaoxiang; Wang Lie; Wei Qingyi [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Vinogradskiy, Yevgeniy [University of Colorado School of Medicine, Aurora, Colorado (United States); Martel, Mary [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)

    2013-01-01

    Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.

  3. The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

    Science.gov (United States)

    Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

    2014-12-30

    This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

  4. The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Chuncai Xiao

    2014-12-01

    Full Text Available This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM and improved particle swarm optimization (IPSO algorithm (SVM-IPSO. In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN, the basic particle swarm optimization (PSO method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

  5. The triglyceride/high-density lipoprotein cholesterol ratio fails to predict insulin resistance in African-American women: an analysis of Jackson Heart Study.

    Science.gov (United States)

    Sumner, Anne E; Harman, Jane L; Buxbaum, Sarah G; Miller, Bernard V; Tambay, Anita V; Wyatt, Sharon B; Taylor, Herman A; Rotimi, Charles N; Sarpong, Daniel F

    2010-12-01

    Compared to whites, insulin-resistant African Americans have worse outcomes. Screening programs that could identify insulin resistance early enough for intervention to affect outcome often rely on triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels. Racial differences in TG and HDL-C may compromise the efficacy of these programs in African Americans. A recommendation currently exists to use the TG/HDL-C ratio ≥2.0 to predict insulin resistance in African Americans. The validity of this recommendation needs examination. Therefore, our aim was to determine the ability of TG/HDL-C ratio to predict insulin resistance in African Americans. In 1,903 African Americans [895 men, 1,008 women, age 55 ± 12 years, mean ± standard deviation (SD), range 35-80 years, body mass index (BMI) 31.0 ± 6.4 kg/m(2), range 18.5-55 kg/m(2)] participating in the Jackson Heart Study, a population-based study of African Americans, Jackson, Mississippi tricounty region, insulin resistance was defined by the upper quartile (≥4.43) of homeostasis model assessment of insulin resistance (HOMA-IR). An area under the receiver operating characteristic curve (AUC-ROC) of >0.70 was required for prediction of insulin resistance by TG/HDL-C. The optimal test cutoff was determined by the Youden index. HOMA-IR was similar in men and women (3.40 ± 2.03 vs. 3.80 ± 2.46, P = 0.60). Women had lower TG (94 ± 49 vs. 109 ± 65 mg/dL P Heart Study can help determine the efficacy of screening programs in African-Americans.

  6. Improvement of the butanol production selectivity and butanol to acetone ratio (B:A) by addition of electron carriers in the batch culture of a new local isolate of Clostridium acetobutylicum YM1.

    Science.gov (United States)

    Nasser Al-Shorgani, Najeeb Kaid; Kalil, Mohd Sahaid; Wan Yusoff, Wan Mohtar; Shukor, Hafiza; Hamid, Aidil Abdul

    2015-12-01

    Improvement in the butanol production selectivity or enhanced butanol:acetone ratio (B:A) is desirable in acetone-butanol-ethanol (ABE) fermentation by Clostridium strains. In this study, artificial electron carriers were added to the fermentation medium of a new isolate of Clostridium acetobutylicum YM1 in order to improve the butanol yield and B:A ratio. The results revealed that medium supplementation with electron carriers changed the metabolism flux of electron and carbon in ABE fermentation by YM1. A decrease in acetone production, which subsequently improved the B:A ratio, was observed. Further improvement in the butanol production and B:A ratios were obtained when the fermentation medium was supplemented with butyric acid. The maximum butanol production (18.20 ± 1.38 g/L) was gained when a combination of methyl red and butyric acid was added. Although the addition of benzyl viologen (0.1 mM) and butyric acid resulted in high a B:A ratio of 16:1 (800% increment compared with the conventional 2:1 ratio), the addition of benzyl viologen to the culture after 4 h resulted in the production of 18.05 g/L butanol. Manipulating the metabolic flux to butanol through the addition of electron carriers could become an alternative strategy to achieve higher butanol productivity and improve the B:A ratio. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Science.gov (United States)

    Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

    2015-01-01

    The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  8. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    Energy Technology Data Exchange (ETDEWEB)

    Ratta, G.A., E-mail: garatta@gateme.unsj.edu.ar [GATEME, Facultad de Ingenieria, Universidad Nacional de San Juan, Avda. San Martin 1109 (O), 5400 San Juan (Argentina); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 40, 28040 Madrid (Spain); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Murari, A. [Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova (Italy); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer A new signal selection methodology to improve disruption prediction is reported. Black-Right-Pointing-Pointer The approach is based on Genetic Algorithms. Black-Right-Pointing-Pointer An advanced predictor has been created with the new set of signals. Black-Right-Pointing-Pointer The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called 'Advanced Predictor Of Disruptions' (APODIS), developed for the 'Joint European Torus' (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals' parameters in order to maximize the performance of the predictor is reported. The approach is based on 'Genetic Algorithms' (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  9. Prognostic value of pretreatment albumin–globulin ratio in predicting long-term mortality in gastric cancer patients who underwent D2 resection

    Directory of Open Access Journals (Sweden)

    Liu J

    2017-04-01

    Full Text Available Jianjun Liu,1,2,* Shangxiang Chen,1,2,* Qirong Geng,1,3 Xuechao Liu,1,2 Pengfei Kong,1,2 Youqing Zhan,1,2 Dazhi Xu1,2 1State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 2Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, 3Department of Hematology Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China *These authors contributed equally to this work Background: Several studies have highlighted the prognostic value of the albumin–globulin ratio (AGR in various kinds of cancers. Our study was designed to assess whether AGR is associated with the prognosis of gastric cancer patients. Patients and methods: A total of 507 gastric cancer patients between 2005 and 2012 were included. The AGR was defined as the ratio of serum albumin to nonalbumin and calculated by the equation: albumin/(total protein - albumin. Furthermore, AGR was divided into two groups (low and high using the X-tile software. Survival analysis stratified by AGR groups was performed. Results: The mean survival time for each group was 36.62 months (95% CI: 33.92–39.32 for the low AGR group and 48.95 months (95% CI: 41.93–55.96, P=0.003 for the high AGR group. Patients in the high group (AGR ≥1.93 had a significantly lower 5-year mortality in comparison with the low group (AGR <1.93 (52.4% vs 78.5%, P=0.003. The high AGR group showed obviously better overall survival than the low AGR group according to Kaplan–Meier curves (P=0.003. Multivariate analysis showed that AGR was an independent predictive factor of prognosis in gastric patients. Conclusion: Pretreatment AGR is a significant and independent predictive factor of prognosis. Keywords: gastric cancer, survival, inflammation, albumin–globulin ratio

  10. Improving Spectral Image Classification through Band-Ratio Optimization and Pixel Clustering

    Science.gov (United States)

    O'Neill, M.; Burt, C.; McKenna, I.; Kimblin, C.

    2017-12-01

    The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of DigitalGlobe's WorldView-3 (WV3) to detect and map UNE signatures. WV3 is the current state-of-the-art, commercial, multispectral imaging satellite; however, it has relatively limited spectral and spatial resolutions. These limitations impede image classifiers from detecting targets that are spatially small and lack distinct spectral features. In order to improve classification results, we developed custom algorithms to reduce false positive rates while increasing true positive rates via a band-ratio optimization and pixel clustering front-end. The clusters resulting from these algorithms were processed with standard spectral image classifiers such as Mixture-Tuned Matched Filter (MTMF) and Adaptive Coherence Estimator (ACE). WV3 and AVIRIS data of Cuprite, Nevada, were used as a validation data set. These data were processed with a standard classification approach using MTMF and ACE algorithms. They were also processed using the custom front-end prior to the standard approach. A comparison of the results shows that the custom front-end significantly increases the true positive rate and decreases the false positive rate.This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy. DOE/NV/25946-3283.

  11. Prediction of multi-wake problems using an improved Jensen wake model

    DEFF Research Database (Denmark)

    Tian, Linlin; Zhu, Wei Jun; Shen, Wen Zhong

    2017-01-01

    The improved analytical wake model named as 2D_k Jensen model (which was proposed to overcome some shortcomes in the classical Jensen wake model) is applied and validated in this work for wind turbine multi-wake predictions. Different from the original Jensen model, this newly developed 2D_k Jensen...... model uses a cosine shape instead of the top-hat shape for the velocity deficit in the wake, and the wake decay rate as a variable that is related to the ambient turbulence as well as the rotor generated turbulence. Coupled with four different multi-wake combination models, the 2D_k Jensen model...... is assessed through (1) simulating two wakes interaction under full wake and partial wake conditions and (2) predicting the power production in the Horns Rev wind farm for different wake sectors around two different wind directions. Through comparisons with field measurements, results from Large Eddy...

  12. Predicting the effect of spectral subtraction on the speech recognition threshold based on the signal-to-noise ratio in the envelope domain

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    rarely been evaluated perceptually in terms of speech intelligibility. This study analyzed the effects of the spectral subtraction strategy proposed by Berouti at al. [ICASSP 4 (1979), 208-211] on the speech recognition threshold (SRT) obtained with sentences presented in stationary speech-shaped noise....... The SRT was measured in five normal-hearing listeners in six conditions of spectral subtraction. The results showed an increase of the SRT after processing, i.e. a decreased speech intelligibility, in contrast to what is predicted by the Speech Transmission Index (STI). Here, another approach is proposed......, denoted the speech-based envelope power spectrum model (sEPSM) which predicts the intelligibility based on the signal-to-noise ratio in the envelope domain. In contrast to the STI, the sEPSM is sensitive to the increased amount of the noise envelope power as a consequence of the spectral subtraction...

  13. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

    Science.gov (United States)

    Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-03-01

    Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  14. Clinical Significance of Preoperative Neutrophil Lymphocyte Ratio versus Platelet Lymphocyte Ratio in Patients with Small Cell Carcinoma of the Esophagus

    Directory of Open Access Journals (Sweden)

    Ji-Feng Feng

    2013-01-01

    Full Text Available Recent studies have shown that the presence of systemic inflammation correlates with poor survival in various of cancers. The aim of this study was to determine the prognostic values of neutrophil lymphocyte ratio (NLR and platelet lymphocyte ratio (PLR in patients with small cell carcinoma of the esophagus (SCCE. Preoperative NLR and PLR were evaluated in 43 patients with SCCE from January 2001 to December 2010. The prognostic significance of both markers was then determined by both uni- and multivariate analytical methods. Receiver operating characteristic (ROC curves were also plotted to verify the accuracy of NLR and PLR for survival prediction. Patients with PLR ≥150 had significantly poorer (relapse-free survival RFS and (overall survival OS compared to patients with PLR <150. However, RFS or OS did not differ according to NLR categories (<3.5 and ≥3.5. The areas under the curve (AUC indicated that PLR was superior to NLR as a predictive factor. The results of the present study conclude that PLR is superior to NLR as a predictive factor in patients with SCCE.

  15. New Predictive Parameters of Bell"s Palsy: Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio

    Directory of Open Access Journals (Sweden)

    Doğan Atan

    2015-06-01

    Full Text Available Background: Bell’s palsy is the most frequent cause of unilateral facial paralysis. Inflammation is thought to play an important role in the pathogenesis of Bell’s palsy. Aims: Neutrophil to lymphocyte ratio (NLR and platelet to lymphocyte ratio (PLR are simple and inexpensive tests which are indicative of inflammation and can be calculated by all physicians. The aim of this study was to reveal correlations of Bell’s palsy and degree of paralysis with NLR and PLR. Study Design: Case-control study. Methods: The retrospective study was performed January 2010 and December 2013. Ninety-nine patients diagnosed as Bell’s palsy were included in the Bell’s palsy group and ninety-nine healthy individuals with the same demographic characteristics as the Bell’s palsy group were included in the control group. As a result of analyses, NLR and PLR were calculated. Results: The mean NLR was 4.37 in the Bell’s palsy group and 1.89 in the control group with a statistically significant difference (p<0.001. The mean PLR was 137.5 in the Bell’s palsy group and 113.75 in the control group with a statistically significant difference (p=0.008. No statistically significant relation was detected between the degree of facial paralysis and NLR and PLR. Conclusion: The NLR and the PLR were significantly higher in patients with Bell’s palsy. This is the first study to reveal a relation between Bell’s palsy and PLR. NLR and PLR can be used as auxiliary parameters in the diagnosis of Bell’s palsy.

  16. The Benefits of Financial Ratios' as the Indocators of Future Bankruptcy on the Economic Crisis

    Directory of Open Access Journals (Sweden)

    Setia Mulyawan

    2015-08-01

    Full Text Available It is proved that financial ratios can predict future bankruptcy even on high uncertainty conditions such as an economic crisis. The research indicates that the accuracy of prediction is more increasing in line with a coming bankruptcy.The result of the research shows that four years before a corporate becomes bankrupt there have been significant differences of financial ratios between bankrupt company and sustained one. The ratios of liquidity, profitability, activity, and return on investment of sustained company are higher; while the leverage ratio is lower.The dominant influencing financial ratios toward a bankruptcy are liquidity and leverage ratios. The research finds that from ten tested ratios, Current Asset to current liabilities and total liabilities to total asset are the dominant financial ratios

  17. Improved Outcome Prediction Using CT Angiography in Addition to Standard Ischemic Stroke Assessment: Results from the STOPStroke Study

    Science.gov (United States)

    González, R. Gilberto; Lev, Michael H.; Goldmacher, Gregory V.; Smith, Wade S.; Payabvash, Seyedmehdi; Harris, Gordon J.; Halpern, Elkan F.; Koroshetz, Walter J.; Camargo, Erica C. S.; Dillon, William P.; Furie, Karen L.

    2012-01-01

    Purpose To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). Methods In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as “major” by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was≤7; (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores>10. Results Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS≤10/BASIS− (p10/BASIS+ compared to patients who are NIHSS≤10/BASIS−; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. Conclusions BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment. PMID:22276182

  18. Prediction model of ammonium uranyl carbonate calcination by microwave heating using incremental improved Back-Propagation neural network

    Energy Technology Data Exchange (ETDEWEB)

    Li Yingwei [Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Peng Jinhui, E-mail: jhpeng@kmust.edu.c [Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Liu Bingguo [Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Li Wei [Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Huang Daifu [No. 272 Nuclear Industry Factory, China National Nuclear Corporation, Hengyang, Hunan Province 421002 (China); Zhang Libo [Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China); Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, Yunnan Province 650093 (China)

    2011-05-15

    Research highlights: The incremental improved Back-Propagation neural network prediction model using the Levenberg-Marquardt algorithm based on optimizing theory is put forward. The prediction model of the nonlinear system is built, which can effectively predict the experiment of microwave calcining of ammonium uranyl carbonate (AUC). AUC can accept the microwave energy and microwave heating can quickly decompose AUC. In the experiment of microwave calcining of AUC, the contents of U and U{sup 4+} increased with increasing of microwave power and irradiation time, and decreased with increasing of the material average depth. - Abstract: The incremental improved Back-Propagation (BP) neural network prediction model was put forward, which was very useful in overcoming the problems, such as long testing cycle, high testing quantity, difficulty of optimization for process parameters, many training data probably were offered by the way of increment batch and the limitation of the system memory could make the training data infeasible, which existed in the process of calcinations for ammonium uranyl carbonate (AUC) by microwave heating. The prediction model of the nonlinear system was built, which could effectively predict the experiment of microwave calcining of AUC. The predicted results indicated that the contents of U and U{sup 4+} were increased with increasing of microwave power and irradiation time, and decreased with increasing of the material average depth.

  19. Prediction model of ammonium uranyl carbonate calcination by microwave heating using incremental improved Back-Propagation neural network

    International Nuclear Information System (INIS)

    Li Yingwei; Peng Jinhui; Liu Bingguo; Li Wei; Huang Daifu; Zhang Libo

    2011-01-01

    Research highlights: → The incremental improved Back-Propagation neural network prediction model using the Levenberg-Marquardt algorithm based on optimizing theory is put forward. → The prediction model of the nonlinear system is built, which can effectively predict the experiment of microwave calcining of ammonium uranyl carbonate (AUC). → AUC can accept the microwave energy and microwave heating can quickly decompose AUC. → In the experiment of microwave calcining of AUC, the contents of U and U 4+ increased with increasing of microwave power and irradiation time, and decreased with increasing of the material average depth. - Abstract: The incremental improved Back-Propagation (BP) neural network prediction model was put forward, which was very useful in overcoming the problems, such as long testing cycle, high testing quantity, difficulty of optimization for process parameters, many training data probably were offered by the way of increment batch and the limitation of the system memory could make the training data infeasible, which existed in the process of calcinations for ammonium uranyl carbonate (AUC) by microwave heating. The prediction model of the nonlinear system was built, which could effectively predict the experiment of microwave calcining of AUC. The predicted results indicated that the contents of U and U 4+ were increased with increasing of microwave power and irradiation time, and decreased with increasing of the material average depth.

  20. Bankruptcy prediction for credit risk using neural networks: a survey and new results.

    Science.gov (United States)

    Atiya, A F

    2001-01-01

    The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

  1. Improved stochastic resonance algorithm for enhancement of signal-to-noise ratio of high-performance liquid chromatographic signal

    International Nuclear Information System (INIS)

    Xie Shaofei; Xiang Bingren; Deng Haishan; Xiang Suyun; Lu Jun

    2007-01-01

    Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses

  2. Clinical utility of spot urine protein-to-creatinine ratio modified by estimated daily creatinine excretion in children.

    Science.gov (United States)

    Yang, Eun Mi; Yoon, Bo Ae; Kim, Soo Wan; Kim, Chan Jong

    2017-06-01

    The spot urine protein-to-creatinine ratio (UPCR) is widely used to predict 24-h urine protein (24-h UP) excretion. In patients with low daily urine creatinine excretion (UCr), however, the UPCR may overestimate 24-h UP. The aim of this study was to predict 24-h UP using UPCR adjusted by estimated 24-h UCr in children. This study included 442 children whose 24-h UP and spot UPCR were measured concomitantly. Estimated 24-h UCr was calculated using three previously existing equations. We estimated the 24-h UP excretion from UPCR by multiplying the estimated UCr. The results were compared with the measured 24-h UP. There was a strong correlation between UPCR and 24-h UP (r = 0.801, P < 0.001), and the correlation improved after multiplying the UPCR by the measured UCr (r = 0.847, P < 0.001). Using the estimated UCr rather than the measured UCr, there was high accuracy and strong correlation between the estimated UPCR weighted by the Cockcroft-Gault equation and 24-h UP. Improvement was also observed in the subgroup (proteinuria vs. non-proteinuria) analysis, particularly in the proteinuria group. The spot UPCR multiplied by the estimated UCr improved the accuracy of prediction of the 24-h UP in children.

  3. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility

    DEFF Research Database (Denmark)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail Anne

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements....... A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech......, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where...

  4. Assessment of prediction skill in equatorial Pacific Ocean in high resolution model of CFS

    Science.gov (United States)

    Arora, Anika; Rao, Suryachandra A.; Pillai, Prasanth; Dhakate, Ashish; Salunke, Kiran; Srivastava, Ankur

    2018-01-01

    The effect of increasing atmospheric resolution on prediction skill of El Niño southern oscillation phenomenon in climate forecast system model is explored in this paper. Improvement in prediction skill for sea surface temperature (SST) and winds at all leads compared to low resolution model in the tropical Indo-Pacific basin is observed. High resolution model is able to capture extreme events reasonably well. As a result, the signal to noise ratio is improved in the high resolution model. However, spring predictability barrier (SPB) for summer months in Nino 3 and Nino 3.4 region is stronger in high resolution model, in spite of improvement in overall prediction skill and dynamics everywhere else. Anomaly correlation coefficient of SST in high resolution model with observations in Nino 3.4 region targeting boreal summer months when predicted at lead times of 3-8 months in advance decreased compared its lower resolution counterpart. It is noted that higher variance of winds predicted in spring season over central equatorial Pacific compared to observed variance of winds results in stronger than normal response on subsurface ocean, hence increases SPB for boreal summer months in high resolution model.

  5. The Old-Age Healthy Dependency Ratio in Europe.

    Science.gov (United States)

    Muszyńska, Magdalena M; Rau, Roland

    2012-09-01

    The aim of this study is to answer the question of whether improvements in the health of the elderly in European countries could compensate for population ageing on the supply side of the labour market. We propose a state-of-health-specific (additive) decomposition of the old-age dependency ratio into an old-age healthy dependency ratio and an old-age unhealthy dependency ratio in order to participate in a discussion of the significance of changes in population health to compensate for the ageing of the labour force. Applying the proposed indicators to the Eurostat's population projection for the years 2010-2050, and assuming there will be equal improvements in life expectancy and healthy life expectancy at birth, we discuss various scenarios concerning future of the European labour force. While improvements in population health are anticipated during the years 2010-2050, the growth in the number of elderly people in Europe may be expected to lead to a rise in both healthy and unhealthy dependency ratios. The healthy dependency ratio is, however, projected to make up the greater part of the old-age dependency ratio. In the European countries in 2006, the value of the old-age dependency ratio was 25. But in the year 2050, with a positive migration balance over the years 2010-2050, there would be 18 elderly people in poor health plus 34 in good health per 100 people in the current working age range of 15-64. In the scenarios developed in this study, we demonstrate that improvements in health and progress in preventing disability will not, by themselves, compensate for the ageing of the workforce. However, coupled with a positive migration balance, at the level and with the age structure assumed in the Eurostat's population projections, these developments could ease the effect of population ageing on the supply side of the European labour market.

  6. An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

    Science.gov (United States)

    Dash, Rajashree

    2017-11-01

    Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

  7. Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

    DEFF Research Database (Denmark)

    Pena, Michelle J; Jankowski, Joachim; Heinze, Georg

    2015-01-01

    OBJECTIVE: Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma...... proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes. METHODS: Patients with hypertension (n = 125) and type 2 diabetes (n = 82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort....... RESULTS: In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0...

  8. Pretreatment combination of platelet counts and neutrophil–lymphocyte ratio predicts survival of nasopharyngeal cancer patients receiving intensity-modulated radiotherapy

    Directory of Open Access Journals (Sweden)

    Lin YH

    2017-05-01

    Full Text Available Yu-Hsuan Lin,1 Kuo-Ping Chang,2 Yaoh-Shiang Lin,2,3 Ting-Shou Chang2–4 1Department of Otolaryngology, Head and Neck Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 2Department of Otolaryngology, Head and Neck Surgery, Kaohsiung Veterans General Hospital, Kaohsiung, 3Department of Otolaryngology, Head and Neck Surgery, National Defense Medical Center, Taipei, 4Institute of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan, Republic of China Background: Increased cancer-related inflammation has been associated with unfavorable clinical outcomes. The combination of platelet count and neutrophil–lymphocyte ratio (COP-NLR has related outcomes in several cancers, except for nasopharyngeal carcinoma (NPC. This study evaluated the prognostic value of COP-NLR in predicting outcome in NPC patients treated with intensity-modulated radiotherapy (IMRT.Materials and methods: We analyzed the data collected from 232 NPC patients. Pretreatment total platelet counts, neutrophil–lymphocyte ratio (NLR, and COP-NLR score were evaluated as potential predictors. Optimal cutoff values for NLR and platelets were determined using receiver operating curve. Patients with both elevated NLR (>3 and platelet counts (>300×109/L were assigned a COP-NLR score of 2; those with one elevated or no elevated value were assigned a COP-NLR a score of 1 or 0. Cox proportional hazards model was used to test the association of these factors and relevant 3-year survivals.Results: Patients (COP-NLR scores 1 and 2=85; score 0=147 were followed up for 55.19 months. Univariate analysis showed no association between pretreatment NLR >2.23 and platelet counts >290.5×109/L and worse outcomes. Multivariate analysis revealed that those with COP-NLR scores of 0 had better 3-year disease-specific survival (P=0.02, overall survival (P=0.024, locoregional relapse-free survival (P=0.004, and distant

  9. Isotope ratio in stellar atmospheres and nucleosynthesis

    International Nuclear Information System (INIS)

    Barbuy, B.L.S.

    1987-01-01

    The determination of isotopic ratios in stellar atmospheres is studied. The isotopic shift of atomic and molecular lines of different species of a certain element is examined. CH and MgH lines are observed in order to obtain the 12 C: 13 C and 24 Mg: 25 Mg: 26 Mg isotpic ratios. The formation of lines in stellar atmospheres is computed and the resulting synthetic spectra are employed to determine the isotopic abundances. The results obtained for the isotopic ratios are compared to predictions of nucleosynthesis theories. Finally, the concept of primary and secondary element is discussed, and these definitions are applied to the observed variations in the abundance of elements as a function of metallicity. (author) [pt

  10. Congestion Prediction Modeling for Quality of Service Improvement in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ga-Won Lee

    2014-04-01

    Full Text Available Information technology (IT is pushing ahead with drastic reforms of modern life for improvement of human welfare. Objects constitute “Information Networks” through smart, self-regulated information gathering that also recognizes and controls current information states in Wireless Sensor Networks (WSNs. Information observed from sensor networks in real-time is used to increase quality of life (QoL in various industries and daily life. One of the key challenges of the WSNs is how to achieve lossless data transmission. Although nowadays sensor nodes have enhanced capacities, it is hard to assure lossless and reliable end-to-end data transmission in WSNs due to the unstable wireless links and low hard ware resources to satisfy high quality of service (QoS requirements. We propose a node and path traffic prediction model to predict and minimize the congestion. This solution includes prediction of packet generation due to network congestion from both periodic and event data generation. Simulation using NS-2 and Matlab is used to demonstrate the effectiveness of the proposed solution.

  11. The four-loop six-gluon NMHV ratio function

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, Lance J. [SLAC National Accelerator Lab., Stanford, CA (United States); California Inst. of Technology (CalTech), Pasadena, CA (United States); von Hippel, Matt [Perimeter Inst. for Theoretical Physics, Waterloo, ON (Canada); McLeod, Andrew J. [SLAC National Accelerator Lab., Stanford, CA (United States)

    2016-01-11

    We use the hexagon function bootstrap to compute the ratio function which characterizes the next-to-maximally-helicity-violating (NMHV) six-point amplitude in planar N = 4 super-Yang-Mills theory at four loops. A powerful constraint comes from dual superconformal invariance, in the form of a Q- differential equation, which heavily constrains the first derivatives of the transcendental functions entering the ratio function. At four loops, it leaves only a 34-parameter space of functions. Constraints from the collinear limits, and from the multi-Regge limit at the leading-logarithmic (LL) and next-to-leading-logarithmic (NLL) order, suffice to fix these parameters and obtain a unique result. We test the result against multi- Regge predictions at NNLL and N3LL, and against predictions from the operator product expansion involving one and two flux-tube excitations; all cross-checks are satisfied. We also study the analytical and numerical behavior of the parity-even and parity-odd parts on various lines and surfaces traversing the three-dimensional space of cross ratios. As part of this program, we characterize all irreducible hexagon functions through weight eight in terms of their coproduct. Furthermore, we provide representations of the ratio function in particular kinematic regions in terms of multiple polylogarithms.

  12. The four-loop six-gluon NMHV ratio function

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, Lance J. [SLAC National Accelerator Laboratory, Stanford University,Stanford, CA 94309 (United States); Walter Burke Institute for Theoretical Physics, California Institute of Technology,Pasadena, CA 91125 (United States); Hippel, Matt von [Perimeter Institute for Theoretical Physics,Waterloo, Ontario N2L 2Y5 (Canada); McLeod, Andrew J. [SLAC National Accelerator Laboratory, Stanford University,Stanford, CA 94309 (United States)

    2016-01-11

    We use the hexagon function bootstrap to compute the ratio function which characterizes the next-to-maximally-helicity-violating (NMHV) six-point amplitude in planar N=4 super-Yang-Mills theory at four loops. A powerful constraint comes from dual superconformal invariance, in the form of a Q̄ differential equation, which heavily constrains the first derivatives of the transcendental functions entering the ratio function. At four loops, it leaves only a 34-parameter space of functions. Constraints from the collinear limits, and from the multi-Regge limit at the leading-logarithmic (LL) and next-to-leading-logarithmic (NLL) order, suffice to fix these parameters and obtain a unique result. We test the result against multi-Regge predictions at NNLL and N{sup 3}LL, and against predictions from the operator product expansion involving one and two flux-tube excitations; all cross-checks are satisfied. We study the analytical and numerical behavior of the parity-even and parity-odd parts on various lines and surfaces traversing the three-dimensional space of cross ratios. As part of this program, we characterize all irreducible hexagon functions through weight eight in terms of their coproduct. We also provide representations of the ratio function in particular kinematic regions in terms of multiple polylogarithms.

  13. Protein docking prediction using predicted protein-protein interface

    Directory of Open Access Journals (Sweden)

    Li Bin

    2012-01-01

    Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

  14. Protein docking prediction using predicted protein-protein interface.

    Science.gov (United States)

    Li, Bin; Kihara, Daisuke

    2012-01-10

    Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

  15. Prediction of Splint Therapy Efficacy Using Bone Scan in Patients with Unilateral Temporomandibular Disorder

    International Nuclear Information System (INIS)

    Lee, Sang Mi; Lee, Won Woo; Yun, Pil Young; Kim, Young Kyun; Kim, Sang Eun

    2009-01-01

    It is not known whether bone scan is useful for the prediction of the prognosis of patients with temporomandibular disorders (TMD). The aim of the present study was to identify useful prognostic markers on bone scan for the pre-therapeutic assessment of patients with unilateral TMD. Between January 2005 and July 2007, 55 patients (M:F=9:46; mean age, 34.7±14.1 y) with unilateral TMD that underwent a pre-therapeutic bone scan were enrolled. Uptake of Tc-99m HDP in each temporomandibular joint (TMJ) was quantitated using a 13X13 pixel-square region-of-interest over TMJ and parietal skull area as background. TMJ uptake ratios and asymmetric indices were calculated. TMD patients were classified as improved or not improved and the bone scan findings associated with each group were investigated. Forty-six patients were improved, whereas 9 patients were not improved. There was no significant difference between the two groups of patients regarding the TMJ uptake ratio of the involved joint, the TMJ uptake ratio of the non-involved joint, and the asymmetric index (p>0.05). However, in a subgroup analysis, the patients with an increased uptake of Tc-99m HDP at the disease-involved TMJ, by visual assessment, could be easily identified by the asymmetric index; the patients that improved had a higher asymmetric index than the patients that did not improve (1.32±0.35 vs. 1.08±0.04, p=0.023), The Tc-99m HDP bone scan may help predict the prognosis of patients with unilateral TMD after splint therapy when the TMD-involved joint reveals increased uptake by visual assessment

  16. Prediction of Splint Therapy Efficacy Using Bone Scan in Patients with Unilateral Temporomandibular Disorder

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sang Mi; Lee, Won Woo; Yun, Pil Young; Kim, Young Kyun; Kim, Sang Eun [Seoul National University Bundang Hospital, Seoul (Korea, Republic of)

    2009-04-15

    It is not known whether bone scan is useful for the prediction of the prognosis of patients with temporomandibular disorders (TMD). The aim of the present study was to identify useful prognostic markers on bone scan for the pre-therapeutic assessment of patients with unilateral TMD. Between January 2005 and July 2007, 55 patients (M:F=9:46; mean age, 34.7{+-}14.1 y) with unilateral TMD that underwent a pre-therapeutic bone scan were enrolled. Uptake of Tc-99m HDP in each temporomandibular joint (TMJ) was quantitated using a 13X13 pixel-square region-of-interest over TMJ and parietal skull area as background. TMJ uptake ratios and asymmetric indices were calculated. TMD patients were classified as improved or not improved and the bone scan findings associated with each group were investigated. Forty-six patients were improved, whereas 9 patients were not improved. There was no significant difference between the two groups of patients regarding the TMJ uptake ratio of the involved joint, the TMJ uptake ratio of the non-involved joint, and the asymmetric index (p>0.05). However, in a subgroup analysis, the patients with an increased uptake of Tc-99m HDP at the disease-involved TMJ, by visual assessment, could be easily identified by the asymmetric index; the patients that improved had a higher asymmetric index than the patients that did not improve (1.32{+-}0.35 vs. 1.08{+-}0.04, p=0.023), The Tc-99m HDP bone scan may help predict the prognosis of patients with unilateral TMD after splint therapy when the TMD-involved joint reveals increased uptake by visual assessment.

  17. Changes in the Oswestry Disability Index that predict improvement after lumbar fusion.

    Science.gov (United States)

    Djurasovic, Mladen; Glassman, Steven D; Dimar, John R; Crawford, Charles H; Bratcher, Kelly R; Carreon, Leah Y

    2012-11-01

    Clinical studies use both disease-specific and generic health outcomes measures. Disease-specific measures focus on health domains most relevant to the clinical population, while generic measures assess overall health-related quality of life. There is little information about which domains of the Oswestry Disability Index (ODI) are most important in determining improvement in overall health-related quality of life, as measured by the 36-Item Short Form Health Survey (SF-36), after lumbar spinal fusion. The objective of the study is to determine which clinical elements assessed by the ODI most influence improvement of overall health-related quality of life. A single tertiary spine center database was used to identify patients undergoing lumbar fusion for standard degenerative indications. Patients with complete preoperative and 2-year outcomes measures were included. Pearson correlation was used to assess the relationship between improvement in each item of the ODI with improvement in the SF-36 physical component summary (PCS) score, as well as achievement of the SF-36 PCS minimum clinically important difference (MCID). Multivariate regression modeling was used to examine which items of the ODI best predicted achievement for the SF-36 PCS MCID. The effect size and standardized response mean were calculated for each of the items of the ODI. A total of 1104 patients met inclusion criteria (674 female and 430 male patients). The mean age at surgery was 57 years. All items of the ODI showed significant correlations with the change in SF-36 PCS score and achievement of MCID for the SF-36 PCS, but only pain intensity, walking, and social life had r values > 0.4 reflecting moderate correlation. These 3 variables were also the dimensions that were independent predictors of the SF-36 PCS, and they were the only dimensions that had effect sizes and standardized response means that were moderate to large. Of the health dimensions measured by the ODI, pain intensity, walking

  18. Improving student success using predictive models and data visualisations

    Directory of Open Access Journals (Sweden)

    Hanan Ayad

    2012-08-01

    Full Text Available The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50–60%. At the college level in the US only 30% of students graduate from 2-year colleges in 3 years or less and approximately 50% graduate from 4-year colleges in 5 years or less. A basic challenge in delivering global education, therefore, is improving student success. By student success we mean improving retention, completion and graduation rates. In this paper we describe a Student Success System (S3 that provides a holistic, analytical view of student academic progress.1 The core of S3 is a flexible predictive modelling engine that uses machine intelligence and statistical techniques to identify at-risk students pre-emptively. S3 also provides a set of advanced data visualisations for reaching diagnostic insights and a case management tool for managing interventions. S3's open modular architecture will also allow integration and plug-ins with both open and proprietary software. Powered by learning analytics, S3 is intended as an end-to-end solution for identifying at-risk students, understanding why they are at risk, designing interventions to mitigate that risk and finally closing the feedback look by tracking the efficacy of the applied intervention.

  19. Improved interpretation of renal-vein-renin-ratio by simultaneous determination of renal 131I-hippuric-acid-clearance-ratio in patients with renovascular hypertension

    International Nuclear Information System (INIS)

    Helber, A.; Boenner, G.; Hummerich, W.; Wambach, G.; Meurer, K.A.; Dvorak, K.; Lent, V.; Zehle, A.; Kaufmann, W.; Koeln Univ.; Staedtisches Krankenhaus Koeln-Merheim; Staedtisches Krankenhaus Koeln-Merheim; Koeln Univ.

    1979-01-01

    In patients with unilateral vascular kidney disease and hypertension, ratio of renal-vein-renin was compared with 131 I-Hippuric-acid clearance and change in blood pressure during Saralasininfusion. The ratio of renal-vein-renin was positively correlated with the ratio in renal plasma flow between the kidneys in all patients studied. The ratio of renins therefore is a result of two factors: The difference in renin secretion and the difference in blood flow in the two kidneys. In patients with angiotensin independent hypertension renin-ratios up to 2.0 were found without relevance to elevated blood pressure. When the difference in renal blood flow between both kidneys was small, even a slight difference in renal vein renin indicated hypertension related to increased renin secretion. (orig./AJ) [de

  20. Optimizing feeding composition and carbon-nitrogen ratios for improved methane yield during anaerobic co-digestion of dairy, chicken manure and wheat straw.

    Science.gov (United States)

    Wang, Xiaojiao; Yang, Gaihe; Feng, Yongzhong; Ren, Guangxin; Han, Xinhui

    2012-09-01

    This study investigated the possibilities of improving methane yield from anaerobic digestion of multi-component substrates, using a mixture of dairy manure (DM), chicken manure (CM) and wheat straw (WS), based on optimized feeding composition and the C/N ratio. Co-digestion of DM, CM and WS performed better in methane potential than individual digestion. A larger synergetic effect in co-digestion of DM, CM and WS was found than in mixtures of single manures with WS. As the C/N ratio increased, methane potential initially increased and then declined. C/N ratios of 25:1 and 30:1 had better digestion performance with stable pH and low concentrations of total ammonium nitrogen and free NH(3). Maximum methane potential was achieved with DM/CM of 40.3:59.7 and a C/N ratio of 27.2:1 after optimization using response surface methodology. The results suggested that better performance of anaerobic co-digestion can be fulfilled by optimizing feeding composition and the C/N ratio. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Flight Loads Prediction of High Aspect Ratio Wing Aircraft Using Multibody Dynamics

    Directory of Open Access Journals (Sweden)

    Michele Castellani

    2016-01-01

    Full Text Available A framework based on multibody dynamics has been developed for the static and dynamic aeroelastic analyses of flexible high aspect ratio wing aircraft subject to structural geometric nonlinearities. Multibody dynamics allows kinematic nonlinearities and nonlinear relationships in the forces definition and is an efficient and promising methodology to model high aspect ratio wings, which are known to be prone to structural nonlinear effects because of the high deflections in flight. The multibody dynamics framework developed employs quasi-steady aerodynamics strip theory and discretizes the wing as a series of rigid bodies interconnected by beam elements, representative of the stiffness distribution, which can undergo arbitrarily large displacements and rotations. The method is applied to a flexible high aspect ratio wing commercial aircraft and both trim and gust response analyses are performed in order to calculate flight loads. These results are then compared to those obtained with the standard linear aeroelastic approach provided by the Finite Element Solver Nastran. Nonlinear effects come into play mainly because of the need of taking into account the large deflections of the wing for flight loads computation and of considering the aerodynamic forces as follower forces.

  2. EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

    Science.gov (United States)

    Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

    2018-04-24

    Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

  3. Temperature diagnostic line ratios of Fe XVII

    International Nuclear Information System (INIS)

    Raymond, J.C.; Smith, B.W.; Los Alamos National Lab., NM)

    1986-01-01

    Based on extensive calculations of the excitation rates of Fe XVII, four temperature-sensitive line ratios are investigated, paying special attention to the contribution of resonances to the excitation rates and to the contributions of dielectronic recombination satellites to the observed line intensities. The predictions are compared to FPCS observations of Puppis A and to Solar Maximum Mission (SMM) and SOLEX observations of the sun. Temperature-sensitive line ratios are also computed for emitting gas covering a broad temperature range. It is found that each ratio yields a differently weighted average for the temperature and that this accounts for some apparent discrepancies between the theoretical ratios and solar observations. The effects of this weighting on the Fe XVII temperature diagnostics and on the analogous Fe XXIV/Fe XXV satellite line temperature diagnostics are discussed. 27 references

  4. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Directory of Open Access Journals (Sweden)

    Ulrike Ober

    Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  5. Verification and Improvement of the Three-Dimensional Basin Velocity Structure Model in the Osaka Sedimentary Basin, Japan Using Interstation Green's Functions and H/V Spectral Ratios of Microtremors

    Science.gov (United States)

    Asano, K.; Iwata, T.; Sekiguchi, H.; Somei, K.; Nishimura, T.; Miyakoshi, K.; Aoi, S.; Kunugi, T.

    2012-12-01

    as low as 350 m/s in 0.2-0.5 Hz. The second observation is a set of short-time (30~60 min) single-station microtremor observations to obtain H/V spectral ratios at sites. We observed microtremor at 100 strong motion stations of Osaka prefecture government, JMA, K-NET, KiK-net, and other institutes. The peak period of H/V ranges from about 1 to 7 s, and it depends on the bedrock depth at the observation site as previously pointed by Miyakoshi et al. (1997). Though the basin velocity model explains the characteristics of observed H/V spectral ratios at most sites, we found discrepancies between observed and predicted H/V peak periods at north part of Osaka bay area and hill area in southeastern part of the basin. By combining the observed constraints from the group velocities, waveform characteristics of interstation Green's functions, and H/V spectral ratios, we will improve the S-wave velocity structure model inside the Osaka basin.

  6. P-wave characteristics on routine preoperative electrocardiogram improve prediction of new-onset postoperative atrial fibrillation in cardiac surgery.

    Science.gov (United States)

    Wong, Jim K; Lobato, Robert L; Pinesett, Andre; Maxwell, Bryan G; Mora-Mangano, Christina T; Perez, Marco V

    2014-12-01

    To test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model. Retrospective analysis. Single-center university hospital. Five hundred twenty-six patients, ≥ 18 years of age, who underwent coronary artery bypass grafting, aortic valve replacement, mitral valve replacement/repair, or a combination of valve surgery and coronary artery bypass grafting requiring cardiopulmonary bypass. Retrospective review of medical records. Baseline characteristics and cardiopulmonary bypass times were collected. Digitally-measured timing and voltages from preoperative electrocardiograms were extracted. Postoperative atrial fibrillation was defined as atrial fibrillation requiring therapeutic intervention. Two hundred eight (39.5%) patients developed postoperative atrial fibrillation. Clinical predictors were age, ejection fractionelectrocardiogram variables to the prediction model with only clinical predictors significantly improved the area under the receiver operating characteristic curve, from 0.71 to 0.78 (p<0.01). Overall net reclassification improvement was 0.059 (p = 0.09). Among those who developed postoperative atrial fibrillation, the net reclassification improvement was 0.063 (p = 0.03). Several p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Is combination of neutrophil to lymphocyte ratio and platelet lymphocyte ratio a useful predictor of postoperative survival in patients with esophageal squamous cell carcinoma?

    Directory of Open Access Journals (Sweden)

    Tanoglu A

    2014-03-01

    Full Text Available Alpaslan Tanoglu,1 Ergenekon Karagoz,2 Nurettin Yiyit,3 Ufuk Berber4 1Department of Gastroenterology, 2Department of Infectious Diseases and Clinical Microbiology, 3Department of Thoracic Surgery, 4Department of Pathology, GATA Haydarpasa Training Hospital, Uskudar, TurkeyWe read with interest the recent article entitled "Combination of neutrophil to lymphocyte ratio and platelet lymphocyte ratio is a useful predictor of postoperative survival in patients with esophageal squamous cell carcinoma" by Feng et al.1 In their study, authors aimed to investigate the usefulness of a novel inflammation-based prognostic system, using the combination of neutrophil lymphocyte ratio (NLR and platelet lymphocyte ratio (PLR, for predicting survival in patients with esophageal squamous cell carcinoma (ESCC. Finally, they concluded that combination of NLR and PLR is a useful predictor of postoperative survival in patients with ESCC and combination of these parameters is superior to NLR or PLR as a predictive factor in patients with ESCC. We would like to thank the authors for their contribution.View original paper by Feng and colleagues.

  8. Improving diagnosis, prognosis and prediction by using biomarkers in CRC patients (Review).

    Science.gov (United States)

    Nikolouzakis, Taxiarchis Konstantinos; Vassilopoulou, Loukia; Fragkiadaki, Persefoni; Mariolis Sapsakos, Theodoros; Papadakis, Georgios Z; Spandidos, Demetrios A; Tsatsakis, Aristides M; Tsiaoussis, John

    2018-06-01

    Colorectal cancer (CRC) is among the most common cancers. In fact, it is placed in the third place among the most diagnosed cancer in men, after lung and prostate cancer, and in the second one for the most diagnosed cancer in women, following breast cancer. Moreover, its high mortality rates classifies it among the leading causes of cancer‑related death worldwide. Thus, in order to help clinicians to optimize their practice, it is crucial to introduce more effective tools that will improve not only early diagnosis, but also prediction of the most likely progression of the disease and response to chemotherapy. In that way, they will be able to decrease both morbidity and mortality of their patients. In accordance with that, colon cancer research has described numerous biomarkers for diagnostic, prognostic and predictive purposes that either alone or as part of a panel would help improve patient's clinical management. This review aims to describe the most accepted biomarkers among those proposed for use in CRC divided based on the clinical specimen that is examined (tissue, faeces or blood) along with their restrictions. Lastly, new insight in CRC monitoring will be discussed presenting promising emerging biomarkers (telomerase activity, telomere length and micronuclei frequency).

  9. Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?

    Science.gov (United States)

    Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Monego, Martina; Norbiato, Daniele; Ferri, Miche; Solomatine, Dimitri P.

    2017-02-01

    Monitoring stations have been used for decades to properly measure hydrological variables and better predict floods. To this end, methods to incorporate these observations into mathematical water models have also been developed. Besides, in recent years, the continued technological advances, in combination with the growing inclusion of citizens in participatory processes related to water resources management, have encouraged the increase of citizen science projects around the globe. In turn, this has stimulated the spread of low-cost sensors to allow citizens to participate in the collection of hydrological data in a more distributed way than the classic static physical sensors do. However, two main disadvantages of such crowdsourced data are the irregular availability and variable accuracy from sensor to sensor, which makes them challenging to use in hydrological modelling. This study aims to demonstrate that streamflow data, derived from crowdsourced water level observations, can improve flood prediction if integrated in hydrological models. Two different hydrological models, applied to four case studies, are considered. Realistic (albeit synthetic) time series are used to represent crowdsourced data in all case studies. In this study, it is found that the data accuracies have much more influence on the model results than the irregular frequencies of data availability at which the streamflow data are assimilated. This study demonstrates that data collected by citizens, characterized by being asynchronous and inaccurate, can still complement traditional networks formed by few accurate, static sensors and improve the accuracy of flood forecasts.

  10. Improvement of Surface Temperature Prediction Using SVR with MOGREPS Data for Short and Medium range over South Korea

    Science.gov (United States)

    Lim, S. J.; Choi, R. K.; Ahn, K. D.; Ha, J. C.; Cho, C. H.

    2014-12-01

    As the Korea Meteorology Administration (KMA) has operated Met Office Global and Regional Ensemble Prediction System (MOGREPS) with introduction of Unified Model (UM), many attempts have been made to improve predictability in temperature forecast in last years. In this study, post-processing method of MOGREPS for surface temperature prediction is developed with machine learning over 52 locations in South Korea. Past 60-day lag time was used as a training phase of Support Vector Regression (SVR) method for surface temperature forecast model. The selected inputs for SVR are followings: date and surface temperatures from Numerical Weather prediction (NWP), such as GDAPS, individual 24 ensemble members, mean and median of ensemble members for every 3hours for 12 days.To verify the reliability of SVR-based ensemble prediction (SVR-EP), 93 days are used (from March 1 to May 31, 2014). The result yielded improvement of SVR-EP by RMSE value of 16 % throughout entire prediction period against conventional ensemble prediction (EP). In particular, short range predictability of SVR-EP resulted in 18.7% better RMSE for 1~3 day forecast. The mean temperature bias between SVR-EP and EP at all test locations showed around 0.36°C and 1.36°C, respectively. SVR-EP is currently extending for more vigorous sensitivity test, such as increasing training phase and optimizing machine learning model.

  11. Significance of the interleukin-1 receptor antagonist/interleukin-1 beta ratio as a prognostic factor in patients with pulmonary sarcoidosis.

    Science.gov (United States)

    Mikuniya, T; Nagai, S; Takeuchi, M; Mio, T; Hoshino, Y; Miki, H; Shigematsu, M; Hamada, K; Izumi, T

    2000-01-01

    Various factors such as serum angiotensin-converting enzyme (sACE) activity, bronchoalveolar lavage (BAL) fluid lymphocyte percent, CD4/CD8 ratio, and shadows on chest radiograph have been identified as indexes of disease activity in patients with sarcoidosis. However, it remains to be confirmed whether these factors can predict clinical outcomes. To examine whether the interleukin-1 receptor antagonist (IL-1ra)/IL-1 beta ratio can predict the clinical course, we prospectively followed the clinical courses of 30 patients with pulmonary sarcoidosis 4 years after measurement of immunoreactive amounts of IL-1ra or IL-1 beta in the culture supernatants obtained from BAL fluid macrophages. Immunoreactive amounts of IL-1ra or IL-1 beta were measured using ELISA. Changes in pulmonary function, sACE activity, and shadows on chest radiographs during observation periods were evaluated as markers of changes in disease activity. We found that the patients whose shadows on chest radiographs showed improvement had a higher molar IL-1ra/IL-1 beta ratio than the patients whose shadows persistently remained 4 years after BAL examination (p sACE activity at the time of the last observation to sACE activity at the time of BAL (sACE(LAST)/sACE(BAL), p sACE(LAST)/sACE(BAL) ratio was significantly lower in patients whose shadows on chest radiographs decreased than in those whose shadows remained unchanged (p < 0.005). The IL-1ra/IL-1 beta ratio in the BAL fluid macrophage culture supernatants in patients with pulmonary sarcoidosis could be a useful marker in predicting the persistence of granulomatous lesions (chronicity). Copyright 2000 S. Karger AG, Basel

  12. Combined Effect of Contraction Ratio and Chamber Pressure on the Performance of a Gaseous Hydrogen-Liquid-Oxygen Combustor for a Given Propellant Weight Flow and Oxidant-Fuel Ratio

    Science.gov (United States)

    Hersch, Martin

    1961-01-01

    The effect of contraction ratio and chamber pressure on the combustion performance of a gaseous-hydrogen-liquid-oxygen combustor was investigated analytically and experimentally. The experiment was conducted with a "two-dimensional" gaseous-hydrogen-liquid-oxygen engine of about 150-pound thrust. The contraction ratio was varied from 1.5 to 6 by changing the nozzle throat area. This variation resulted in a chamber pressure variation of about 25 to 120 pounds per square inch. The experimental results were corrected for heat transfer to the engine walls and momentum pressure losses. The experimental performance, as evaluated in terms of characteristic exhaust velocity, was 98 percent of theoretical at contraction ratios greater than 3 but decreased very rapidly at smaller contraction ratios. The heat-transfer rate increased with increasing contraction ratio and chamber pressure; it was about 1 Btu per square inch per second at a contraction ratio of 1.5 and increased to about 3 at a contraction ratio of 6. The combined effects of contraction-ratio and chamber-pressure changes on performance were investigated analytically with a mixing model and a vaporization model. The mixing model predicted very poor mixing at contraction ratios below 3 and almost perfect mixing at higher contraction ratios. The performance predicted by the vaporization model was very close to 100 percent for all contraction ratios. From these results, it was concluded that the performance was limited by poor mixing at low contraction ratios and chamber pressures.

  13. Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

    Directory of Open Access Journals (Sweden)

    Lees Jonathan G

    2008-01-01

    Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

  14. Predicting cardiometabolic disturbances from waist-to-height ratio: findings from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline.

    Science.gov (United States)

    Castanheira, Marcelo; Chor, Dóra; Braga, José Uéleres; Cardoso, Letícia de Oliveira; Griep, Rosane Härter; Molina, Maria Del Carmen Bisi; Fonseca, Maria de Jesus Mendes da

    2018-04-01

    To evaluate the performance of waist-to-height ratio (WHtR) in predicting cardiometabolic outcomes and compare cut-off points for Brazilian adults. Cross-sectional study. WHtR areas under the curve (AUC) were compared with those for BMI, waist circumference (WC) and waist-to-hip ratio (WHR). The outcomes of interest were hypertension, diabetes, hypertriacylglycerolaemia and presence of at least two components of metabolic syndrome (≥2 MetS). Cut-offs for WHtR were compared and validity measures were estimated for each point. Teaching and research institutions in six Brazilian state capitals, 2008-2010. Women (n 5026) and men (n 4238) aged 35-54 years who participated in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) at baseline. WHtR age-adjusted AUC ranged from 0·68 to 0·72 in men and 0·69 to 0·75 in women, with smaller AUC for hypertriacylglycerolaemia and the largest for ≥2 MetS. WHtR performed better than BMI for practically all outcomes; better than WHR for hypertension in both sexes; and displayed larger AUC than WC in predicting diabetes mellitus. It also offered better discriminatory power for ≥2 MetS in men; and was better than WC, but not WHR, in women. Optimal cut-off points of WHtR were 0·55 (women) and 0·54 (men), but they presented high false-negative rate compared with 0·50. We recommend using WHtR (which performed similarly to, or better than, other available indices of adiposity) as an anthropometric index with good discriminatory power for cardiometabolic outcomes in Brazilian adults, indicating the already referenced limit of WHtR≥0·50.

  15. Improving ELM-Based Service Quality Prediction by Concise Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yuhai Zhao

    2015-01-01

    Full Text Available Web services often run on highly dynamic and changing environments, which generate huge volumes of data. Thus, it is impractical to monitor the change of every QoS parameter for the timely trigger precaution due to high computational costs associated with the process. To address the problem, this paper proposes an active service quality prediction method based on extreme learning machine. First, we extract web service trace logs and QoS information from the service log and convert them into feature vectors. Second, by the proposed EC rules, we are enabled to trigger the precaution of QoS as soon as possible with high confidence. An efficient prefix tree based mining algorithm together with some effective pruning rules is developed to mine such rules. Finally, we study how to extract a set of diversified features as the representative of all mined results. The problem is proved to be NP-hard. A greedy algorithm is presented to approximate the optimal solution. Experimental results show that ELM trained by the selected feature subsets can efficiently improve the reliability and the earliness of service quality prediction.

  16. Improvements in Precise and Accurate Isotope Ratio Determination via LA-MC-ICP-MS by Application of an Alternative Data Reduction Protocol

    Science.gov (United States)

    Fietzke, J.; Liebetrau, V.; Guenther, D.; Frische, M.; Zumholz, K.; Hansteen, T. H.; Eisenhauer, A.

    2008-12-01

    An alternative approach for the evaluation of isotope ratio data using LA-MC-ICP-MS will be presented. In contrast to previously applied methods it is based on the simultaneous responses of all analyte isotopes of interest and the relevant interferences without performing a conventional background correction. Significant improvements in precision and accuracy can be achieved when applying this new method and will be discussed based on the results of two first methodical applications: a) radiogenic and stable Sr isotopes in carbonates b) stable chlorine isotopes of pyrohydrolytic extracts. In carbonates an external reproducibility of the 87Sr/86Sr ratios of about 19 ppm (RSD) was achieved, an improvement of about a factor of 5. For recent and sub-recent marine carbonates a mean radiogenic strontium isotope ratio 87Sr/86Sr of 0.709170±0.000007 (2SE) was determined, which agrees well with the value of 0.7091741±0.0000024 (2SE) reported for modern sea water [1,2]. Stable chlorine isotope ratios were determined ablating pyrohydrolytic extracts with a reproducibility of about 0.05‰ (RSD). For basaltic reference material JB1a and JB2 chlorine isotope ratios were determined relative to SMOC (standard mean ocean chlorinity) δ37ClJB-1a = (-0.99±0.06) ‰ and δ37ClJB-1a = (-0.60±0.03) ‰ (SD), respectively, in accordance with published data [3]. The described strategies for data reduction are considered to be generally applicable for all isotope ratio measurements using LA-MC-ICP-MS. [1] J.M. McArthur, D. Rio, F. Massari, D. Castradori, T.R. Bailey, M. Thirlwall, S. Houghton, Palaeogeo. Palaeoclim. Palaeoeco., 2006, 242 (126), doi: 10.1016/j.palaeo.2006.06.004 [2] J. Fietzke, V. Liebetrau, D. Guenther, K. Guers, K. Hametner, K. Zumholz, T.H. Hansteen and A. Eisenhauer, J. Anal. At. Spectrom., 2008, 23, 955-961, doi:10.1039/B717706B [3] J. Fietzke, M. Frische, T.H. Hansteen and A. Eisenhauer, J. Anal. At. Spectrom., 2008, 23, 769-772, doi:10.1039/B718597A

  17. Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

    Science.gov (United States)

    Katzner, Steffen; Treue, Stefan; Busse, Laura

    2012-09-04

    One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

  18. Can Serum Neutrophil-to-Lymphocyte Ratio Be a Predictive Biomarker to Help Differentiate Active Chronic Otitis Media From Inactive Chronic Otitis Media?

    Science.gov (United States)

    Tansuker, Hasan Deniz; Eroğlu, Sinan; Yenigün, Alper; Taşkin, Ümit; Oktay, Mehmet Faruk

    2017-05-01

    The authors' aim was to investigate whether serum neutrophil to lymphocyte ratio might be used as a predictive biomarker to help differentiate active from inactive chronic otitis media (COM). Two hundred fifty-nine patients having inactive COM received tympanoplasty without mastoidectomy and were identified as Group 1. On the other hand, 254 patients having active COM received tympanoplasty with mastoidectomy and were identified as Group 2. Routine hemogram tests were performed preoperatively for both the groups. By performing a chart review, white blood cell count, red blood cell count, hemoglobin, hematocrit, platelet, and mean platelet volume values were compared between the groups in an age-matched and sex-matched manner. A total of 513 COM patients with age range of 7 to 65 years were included in the study. Two hundred seventy-five patients (53.6%) were male, 238 were (46.4%) female. Preoperatively both serum neutrophil and lymphocyte counts were significantly higher in Group 2 (P = 0.015 and P = 0.004, respectively). However, the neutrophil-to-lymphocyte ratios between the groups were not significantly different (P = 0.511). No statistically significant differences were identified from preoperative neutrophil-to-lymphocyte ratios between patients having active COM and inactive COM. Level NA.

  19. Regulation of the Docosapentaenoic Acid/Docosahexaenoic Acid Ratio (DPA/DHA Ratio) in Schizochytrium limacinum B4D1.

    Science.gov (United States)

    Zhang, Ke; Li, Huidong; Chen, Wuxi; Zhao, Minli; Cui, Haiyang; Min, Qingsong; Wang, Haijun; Chen, Shulin; Li, Demao

    2017-05-01

    Docosapentaenoic acid/docosahexaenoic acid ratio (DPA/DHA ratio) in Schizochytrium was relatively stable. But ideally the ratio of DPA/DHA will vary according to the desired end use. This study reports several ways of modulating the DPA/DHA ratio. Incubation times changed the DPA/DHA ratio, and changes in this ratio were associated with the variations in the saturated fatty acid (SFAs) content. Propionic acid sharply increased the SFAs content in lipids, dramatically decreased the even-chain SFAs content, and reduced the DPA/DHA ratio. Pentanoic acid (C5:0) and heptanoic acid (C7:0) had similar effects as propionic acid, whereas butyric acid (C4:0), hexanoic acid (C6:0), and octanoic acid (C8:0) did not change the fatty acid profile and the DPA/DHA ratio. Transcription analyses show that β-oxidation might be responsible for this phenomenon. Iodoacetamide upregulated polyunsaturated fatty acid (PUFA) synthase genes, reduced the DHA content, and improved the DPA content, causing the DPA/DHA ratio to increase. These results present new insights into the regulation of the DPA/DHA ratio.

  20. Does early change predict long-term (6 months) improvements in subjects who receive manual therapy for low back pain?

    Science.gov (United States)

    Cook, Chad; Petersen, Shannon; Donaldson, Megan; Wilhelm, Mark; Learman, Ken

    2017-09-01

    Early change is commonly assessed for manual therapy interventions and has been used to determine treatment appropriateness. However, current studies have only explored the relationship of between or within-session changes and short-/medium-term outcomes. The goal of this study was to determine whether pain changes after two weeks of pragmatic manual therapy could predict those participants with chronic low back pain who demonstrate continued improvements at 6-month follow-up. This study was a retrospective observational design. Univariate logistic regression analyses were performed using a 33% and a 50% pain change to predict improvement. Those who experienced a ≥33% pain reduction by 2 weeks had 6.98 (95% CI = 1.29, 37.53) times higher odds of 50% improvement on the GRoC and 4.74 (95% CI = 1.31, 17.17) times higher odds of 50% improvement on the ODI (at 6 months). Subjects who reported a ≥50% pain reduction at 2 weeks had 5.98 (95% CI = 1.56, 22.88) times higher odds of a 50% improvement in the GRoC and 3.99 (95% CI = 1.23, 12.88) times higher odds of a 50% improvement in the ODI (at 6 months). Future studies may investigate whether a change in plan of care is beneficial for patients who are not showing early improvement predictive of a good long-term outcome.

  1. Environmental impacts of genetic improvement of growth rate and feed conversion ratio in fish farming under rearing density and nitrogen output limitations

    NARCIS (Netherlands)

    Besson, M.; Aubin, J.; Komen, H.; Poelman, M.; Quillet, E.; Vandeputte, M.; Arendonk, Van J.A.M.; Boer, De I.J.M.

    2016-01-01

    Today, fish farming faces an increasing demand in fish products, but also various environmental challenges. Genetic improvement in growth rate and feed conversion ratio is known to be an efficient way to increase production and increase efficiency in fish farming. The environmental consequences

  2. Second to fourth digit ratio: a predictor of adult lung function

    Directory of Open Access Journals (Sweden)

    I-Nae Park

    2014-02-01

    Full Text Available Sex and sex hormones play a major role in lung physiology. It has been proposed that the ratio of the second to fourth digits (digit ratio is correlated with fetal sex hormones. We therefore hypothesized that digit ratio might help predict lung function. We investigated the relationship between digit ratio and pulmonary function test (PFT fi ndings. A total of 245 South Korean patients (162 male, 83 female aged from 34 to 90 years who were hospitalized for urological surgery were prospectively enrolled. Before administering the PFTs, the lengths of the second and fourth digits of the right hand were measured by a single investigator using a digital Vernier caliper. In males (n = 162, univariate and multivariate analysis using linear regression models showed that digit ratio was a signifi cant predictive factor of forced vital capacity (FVC and forced expiratory volume in 1 second (FEV1 (FVC: r = 0.156, P = 0.047; FEV1: r = 0.160, P = 0.042. In male ever-smokers (n = 69, lung functions (FVC and FEV1 were correlated with smoking exposure rather than digit ratio. In female never-smokers (n = 83, lung functions (FEV1 and FEV1/FVC ratio were positively correlated with digit ratio on univariate analysis (FEV1: r = 0.242, P = 0.027; FEV1/FVC ratio: r = 0.245, P = 0.026. Patients with lower digit ratios tend to have decreased lung function. These results suggest that digit ratio is a predictor of airway function.

  3. A Model Suggestion to Predict Leverage Ratio for Construction Projects

    OpenAIRE

    Özlem Tüz; Şafak Ebesek

    2013-01-01

    Due to the nature, construction is an industry with high uncertainty and risk. Construction industry carries high leverage ratios. Firms with low equities work in big projects through progress payment system, but in this case, even a small negative in the planned cash flows constitute a major risk for the company.The use of leverage, with a small investment to achieve profit targets large-scale, high-profit, but also brings a high risk with it. Investors may lose all or the portion of th...

  4. Improving prediction of fall risk among nursing home residents using electronic medical records.

    Science.gov (United States)

    Marier, Allison; Olsho, Lauren E W; Rhodes, William; Spector, William D

    2016-03-01

    Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls. The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data. In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification. Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  5. Absence of airway secretion accumulation predicts tolerance of noninvasive ventilation in subjects with amyotrophic lateral sclerosis.

    Science.gov (United States)

    Vandenberghe, Nadia; Vallet, Anne-Evelyne; Petitjean, Thierry; Le Cam, Pierre; Peysson, Stéphane; Guérin, Claude; Dailler, Frédéric; Jay, Sylvie; Cadiergue, Vincent; Bouhour, Françoise; Court-Fortune, Isabelle; Camdessanche, Jean-Philippe; Antoine, Jean-Christophe; Philit, François; Beuret, Pascal; Bin-Dorel, Sylvie; Vial, Christophe; Broussolle, Emmanuel

    2013-09-01

    To assess factors that predict good tolerance of noninvasive ventilation (NIV), in order to improve survival and quality of life in subjects with amyotrophic lateral sclerosis. We conducted a prospective study in subjects with amyotrophic lateral sclerosis and requiring NIV. The primary end point was NIV tolerance at 1 month. Subjects, several of whom failed to complete the study, were classified as "tolerant" or "poorly tolerant," according to the number of hours of NIV use (more or less than 4 h per night, respectively). Eighty-one subjects, 73 of whom also attended the 1-month follow-up visit, participated over 34 months. NIV tolerance after the first day of utilization predicted tolerance at 1 month (77.6% and 75.3% of subjects, respectively). Multivariate analysis disclosed 3 factors predicting good NIV tolerance: absence of airway secretions accumulation prior to NIV onset (odds ratio 11.5); normal bulbar function at initiation of NIV (odds ratio 8.5); and older age (weakly significant, odds ratio 1.1). Our study reveals 3 factors that are predictive of good NIV tolerance, in particular the absence of airway secretion accumulation, which should prompt NIV initiation before its appearance.

  6. Arcjet nozzle area ratio effects

    Science.gov (United States)

    Curran, Francis M.; Sarmiento, Charles J.; Birkner, Bjorn W.; Kwasny, James

    1990-01-01

    An experimental investigation was conducted to determine the effect of nozzle area ratio on the operating characteristics and performance of a low power dc arcjet thruster. Conical thoriated tungsten nozzle inserts were tested in a modular laboratory arcjet thruster run on hydrogen/nitrogen mixtures simulating the decomposition products of hydrazine. The converging and diverging sides of the inserts had half angles of 30 and 20 degrees, respectively, similar to a flight type unit currently under development. The length of the diverging side was varied to change the area ratio. The nozzle inserts were run over a wide range of specific power. Current, voltage, mass flow rate, and thrust were monitored to provide accurate comparisons between tests. While small differences in performance were observed between the two nozzle inserts, it was determined that for each nozzle insert, arcjet performance improved with increasing nozzle area ratio to the highest area ratio tested and that the losses become very pronounced for area ratios below 50. These trends are somewhat different than those obtained in previous experimental and analytical studies of low Re number nozzles. It appears that arcjet performance can be enhanced via area ratio optimization.

  7. Arcjet Nozzle Area Ratio Effects

    Science.gov (United States)

    Curran, Francis M.; Sarmiento, Charles J.; Birkner, Bjorn W.; Kwasny, James

    1990-01-01

    An experimental investigation was conducted to determine the effect of nozzle area ratio on the operating characteristics and performance of a low power dc arcjet thruster. Conical thoriated tungsten nozzle inserts were tested in a modular laboratory arcjet thruster run on hydrogen/nitrogen mixtures simulating the decomposition products of hydrazine. The converging and diverging sides of the inserts had half angles of 30 and 20 degrees, respectively, similar to a flight type unit currently under development. The length of the diverging side was varied to change the area ratio. The nozzle inserts were run over a wide range of specific power. Current, voltage, mass flow rate, and thrust were monitored to provide accurate comparisons between tests. While small differences in performance were observed between the two nozzle inserts, it was determined that for each nozzle insert, arcjet performance improved with increasing nozzle area ratio to the highest area ratio tested and that the losses become very pronounced for area ratios below 50. These trends are somewhat different than those obtained in previous experimental and analytical studies of low Re number nozzles. It appears that arcjet performance can be enhanced via area ratio optimization.

  8. HIGH-GRADIENT, HIGH-TRANSFORMER-RATIO, DIELECTRIC WAKE FIELD ACCELERATOR

    Energy Technology Data Exchange (ETDEWEB)

    Hirshfield, Jay L

    2012-04-12

    The Phase I work reported here responds to DoE'ss stated need "...to develop improved accelerator designs that can provide very high gradient (>200 MV/m for electrons...) acceleration of intense bunches of particles." Omega-P's approach to this goal is through use of a ramped train of annular electron bunches to drive a coaxial dielectric wakefield accelerator (CDWA) structure. This approach is a direct extension of the CDWA concept from acceleration in wake fields caused by a single drive bunch, to the more efficient acceleration that we predict can be realized from a tailored (or ramped) train of several drive bunches. This is possible because of a much higher transformer ratio for the latter. The CDWA structure itself has a number of unique features, including: a high accelerating gradient G, potentially with G > 1 GeV/m; continuous energy coupling from drive to test bunches without transfer structures; inherent transverse focusing forces for particles in the accelerated bunch; highly stable motion of high charge annular drive bunches; acceptable alignment tolerances for a multi-section system. What is new in the present approach is that the coaxial dielectric structure is now to be energized by-not one-but by a short train of ramped annular-shaped drive bunches moving in the outer coaxial channel of the structure. We have shown that this allows acceleration of an electron bunch traveling along the axis in the inner channel with a markedly higher transformer ratio T than for a single drive bunch. As described in this report, the structure will be a GHz-scale prototype with cm-scale transverse dimensions that is expected to confirm principles that can be applied to the design of a future THz-scale high gradient (> 500 MV/m) accelerator with mm-scale transverse dimensions. We show here a new means to significantly increase the transformer ratio T of the device, and thereby to significantly improve its suitability as a flexible and effective component in

  9. Predicting Bankruptcy in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul RASHID

    2011-09-01

    Full Text Available This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

  10. Genomic selection: genome-wide prediction in plant improvement.

    Science.gov (United States)

    Desta, Zeratsion Abera; Ortiz, Rodomiro

    2014-09-01

    Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Prognostic value of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in acute pulmonary embolism: a systematic review and meta-analysis.

    Science.gov (United States)

    Wang, Qian; Ma, Junfen; Jiang, Zhiyun; Ming, Liang

    2018-02-01

    Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been reported to predict prognosis of acute pulmonary embolism (PE). However, the prognostic value of NLR and PLR remained inconsistent between studies. The aim of this meta-analysis was to assess the prognostic role of NLR and PLR in acute PE. We systematically searched Pubmed, Embase, Web of Science and CNKI for relative literature up to March 2017. The pooled statistics for all outcomes were expressed as odds ratio (OR) and 95% confidence intervals (95% CI). The statistical analyses were performed using Review Manager 5.3.5 analysis software and Stata software. Totally 7 eligible studies consisting of 2323 patients were enrolled in our meta-analysis. Elevated NLR was significantly associated with overall (short-term and long-term) mortality (OR 10.13, 95% CI 6.57-15.64, Panalysis revealed that NLR and PLR are promising biomarkers in predicting prognosis in acute PE patients. We suggest NLR and PLR be used routinely in the PE prognostic assessment.

  12. Sex ratio and Wolbachia infection in the ant Formica exsecta.

    Science.gov (United States)

    Keller, L; Liautard, C; Reuter, M; Brown, W D; Sundström, L; Chapuisat, M

    2001-08-01

    Sex allocation data in social Hymenoptera provide some of the best tests of kin selection, parent-offspring conflict and sex ratio theories. However, these studies critically depend on controlling for confounding ecological factors and on identifying all parties that potentially manipulate colony sex ratio. It has been suggested that maternally inherited parasites may influence sex allocation in social Hymenoptera. If the parasites can influence sex allocation, infected colonies are predicted to invest more resources in females than non-infected colonies, because the parasites are transmitted through females but not males. Prime candidates for such sex ratio manipulation are Wolbachia, because these cytoplasmically transmitted bacteria have been shown to affect the sex ratio of host arthropods by cytoplasmic incompatibility, parthenogenesis, male-killing and feminization. In this study, we tested whether Wolbachia infection is associated with colony sex ratio in two populations of the ant Formica exsecta that have been the subject of extensive sex ratio studies. In these populations colonies specialize in the production of one sex or the other. We found that almost all F. exsecta colonies in both populations are infected with Wolbachia. However, in neither population did we find a significant association in the predicted direction between the prevalence of Wolbachia and colony sex ratio. In particular, colonies with a higher proportion of infected workers did not produce more females. Hence, we conclude that Wolbachia does not seem to alter the sex ratio of its hosts as a means to increase transmission rate in these two populations of ants.

  13. The film boiling look-up table: an improvement in predicting post-chf temperatures

    International Nuclear Information System (INIS)

    Groeneveld, D.C.; Leung, L.K.H.; Vasic, A.Z.; Guo, Y.J.; El Nakla, M.; Cheng, S.C.

    2002-01-01

    During the past 50 years more than 60 film boiling prediction methods have been proposed (Groeneveld and Leung, 2000). These prediction methods generally are applicable over limited ranges of flow conditions and do not provide reasonable predictions when extrapolated well outside the range of their respective database. Leung et al. (1996, 1997) and Kirillov et al. (1996) have proposed the use of a film-boiling look-up table as an alternative to the many models, equations and correlations for the inverted annular film boiling (IAFB) and the dispersed flow film-boiling (DFFB) regime. The film-boiling look-up table is a logical follow-up to the development of the successful CHF look-up table (Groeneveld et al., 1996). It is basically a normalized data bank of heat-transfer coefficients for discrete values of pressure, mass flux, quality and heat flux or surface-temperature. The look-up table proposed by Leung et al. (1996, 1997), and referred to as PDO-LW-96, was based on 14,687 data and predicted the surface temperature with an average error of 1.2% and an rms error of 6.73%. The heat-transfer coefficient was predicted with an average error of -4.93% and an rms error of 16.87%. Leung et al. clearly showed that the look-up table approach, as a general predictive tool for film-boiling heat transfer, was superior to the correlation or model approach. Error statistics were not provided for the look-up table proposed by Kirillov et al. (1996). This paper reviews the look-up table approach and describes improvements to the derivation of the film-boiling look-up table. These improvements include: (i) a larger data base, (ii) a wider range of thermodynamic qualities, (iii) use of the wall temperature instead of the heat flux as an independent parameter, (iv) employment of fully-developed film-boiling data only for the derivation of the look-up table, (v) a finer subdivision and thus more table entries, (vi) smoother table, and (vii) use of the best of five prediction methods

  14. The adenoid-nasopharynx ratio. Its clinical value in children

    International Nuclear Information System (INIS)

    Zou Mingshun

    1997-01-01

    To evaluate the clinical usefulness of adenoid-nasopharynx ratio (A/N ratio) measured on nasopharyngeal lateral plain film, 106 clinical cases of secretory otitis media were selected to measure the A/N ratio before treatment. For patients with A/N ratio of 0.50-0.70, the symptoms improved distinctly after conservative treatment, but one half of patients with A/N ratio ≥ 0.71 required adenoidectomy. A/N ratio is a practical and convenient method for evaluation of the adenoid. A/N ratio ≥ 0.71 indicates pathological enlarged adenoid

  15. Application of Performance Ratios in Portfolio Optimization

    Directory of Open Access Journals (Sweden)

    Aleš Kresta

    2015-01-01

    Full Text Available The cornerstone of modern portfolio theory was established by pioneer work of Harry Markowitz. Based on his mean-variance framework, Sharpe formulated his well-known Sharpe ratio aiming to measure the performance of mutual funds. The contemporary development in computer’s computational power allowed to apply more complex performance ratios, which take into account also higher moments of return probability distribution. Although these ratios were proposed to help the investors to improve the results of portfolio optimization, we empirically demonstrated in our paper that this may not necessarily be true. On the historical dataset of DJIA components we empirically showed that both Sharpe ratio and MAD ratio outperformed Rachev ratio. However, for Rachev ratio we assumed only one level of parameters value. Different set-ups of parameters may provide different results and thus further analysis is certainly required.

  16. Transient Elastography vs. Aspartate Aminotransferase to Platelet Ratio Index in Hepatitis C: A Meta-Analysis.

    Science.gov (United States)

    Mattos, A Z; Mattos, A A

    Many different non-invasive methods have been studied with the purpose of staging liver fibrosis. The objective of this study was verifying if transient elastography is superior to aspartate aminotransferase to platelet ratio index for staging fibrosis in patients with chronic hepatitis C. A systematic review with meta-analysis of studies which evaluated both non-invasive tests and used biopsy as the reference standard was performed. A random-effects model was used, anticipating heterogeneity among studies. Diagnostic odds ratio was the main effect measure, and summary receiver operating characteristic curves were created. A sensitivity analysis was planned, in which the meta-analysis would be repeated excluding each study at a time. Eight studies were included in the meta-analysis. Regarding the prediction of significant fibrosis, transient elastography and aspartate aminotransferase to platelet ratio index had diagnostic odds ratios of 11.70 (95% confidence interval = 7.13-19.21) and 8.56 (95% confidence interval = 4.90-14.94) respectively. Concerning the prediction of cirrhosis, transient elastography and aspartate aminotransferase to platelet ratio index had diagnostic odds ratios of 66.49 (95% confidence interval = 23.71-186.48) and 7.47 (95% confidence interval = 4.88-11.43) respectively. In conclusion, there was no evidence of significant superiority of transient elastography over aspartate aminotransferase to platelet ratio index regarding the prediction of significant fibrosis, but the former proved to be better than the latter concerning prediction of cirrhosis.

  17. An Improved Algorithm for Predicting Free Recalls

    Science.gov (United States)

    Laming, Donald

    2008-01-01

    Laming [Laming, D. (2006). "Predicting free recalls." "Journal of Experimental Psychology: Learning, Memory, and Cognition," 32, 1146-1163] has shown that, in a free-recall experiment in which the participants rehearsed out loud, entire sequences of recalls could be predicted, to a useful degree of precision, from the prior sequences of stimuli…

  18. Indonesian Stock Prediction using Support Vector Machine (SVM

    Directory of Open Access Journals (Sweden)

    Santoso Murtiyanto

    2018-01-01

    Full Text Available This project is part of developing software to provide predictive information technology-based services artificial intelligence (Machine Intelligence or Machine Learning that will be utilized in the money market community. The prediction method used in this early stages uses the combination of Gaussian Mixture Model and Support Vector Machine with Python programming. The system predicts the price of Astra International (stock code: ASII.JK stock data. The data used was taken during 17 yr period of January 2000 until September 2017. Some data was used for training/modeling (80 % of data and the remainder (20 % was used for testing. An integrated model comprising Gaussian Mixture Model and Support Vector Machine system has been tested to predict stock market of ASII.JK for l d in advance. This model has been compared with the Market Cummulative Return. From the results, it is depicts that the Gaussian Mixture Model-Support Vector Machine based stock predicted model, offers significant improvement over the compared models resulting sharpe ratio of 3.22.

  19. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model.

    Science.gov (United States)

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2018-01-01

    The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC models were compared using: concordance index (CI), bias-corrected concordance index (BCCI), calibration plots, the Grønnesby and Borgan test, Bayesian Information Criterion (BIC), generalized R 2 , Integrated Discrimination Improvement (IDI), and continuous Net Reclassification Index (cNRI) for individual risk factors and the three risk groups. Three hundred and twenty-one patients were eligible for analyses. The modified-IMDC model with NLR value of 3.6 and PLR value of 157 was selected for comparison with the IMDC model. Both models were well calibrated. All other measures favoured the modified-IMDC model over the IMDC model (CI, 0.706 vs. 0.677; BCCI, 0.699 vs. 0.671; BIC, 2,176.2 vs. 2,190.7; generalized R 2 , 0.238 vs. 0.202; IDI, 0.044; cNRI, 0.279 for individual risk factors; and CI, 0.669 vs. 0.641; BCCI, 0.669 vs. 0.641; BIC, 2,183.2 vs. 2,198.1; generalized R 2 , 0.163 vs. 0.123; IDI, 0.045; cNRI, 0.165 for the three risk groups). Incorporation of NLR and PLR in place of neutrophil count and platelet count improved prognostic accuracy of the IMDC model. These findings require external validation before introducing into clinical practice.

  20. A novel cutoff for the waist-to-height ratio predicting metabolic syndrome in young American adults

    Directory of Open Access Journals (Sweden)

    Adam D. Bohr

    2016-04-01

    Full Text Available Abstract Background Recent studies have shown the enhanced diagnostic capability of the waist-to-height ratio (WHtR over BMI. However, while a structured cutoff hierarchy has been established for BMI, a rigorous analysis to define individuals as obese using the WHtR has not been performed on a sample of American adults. This study attempts to establish a cutoff for the WHtR using metabolic syndrome as the outcome. Methods The study sample consisted of individuals that were part of the National Longitudinal Study of Adolescent Health (Add Health. The final sample for analysis consisted of 7 935 participants (3 469 males, 4 466 females that were complete respondents for the variables of interest at Wave IV. The participants ranged from 24.55-33.60 years. Weighted and unweighted receiver operator characteristics (ROC analyses were performed predicting metabolic syndrome from the WHtR. Cutoffs were chosen using the Youden index. The derived cutoffs were validated by logistic regression analysis on the Add Health participants and an external sample of 1 236 participants from the National Health and Nutrition Examination Survey (NHANES. Results The ROC analysis resulted in a WHtR cutoff of 0.578 (Youden Index = 0.50 for the full sample of complete respondents, 0.578 (Youden Index = 0.55 for males only, and 0.580 (Youden Index = 0.50 for females only. The area under the curve was 0.798 (95 % CI (0.788, 0.809 for the full sample of complete respondents, 0.833 (95 % CI (0.818, 0.848 for males only, and 0.804 (95 % CI (0.791, 0.818 for females only. Participants in the validation sample with a WHtR greater than the derived cutoff were more likely (Odds Ratio = 9.8, 95 % CI (6.2, 15.3 to have metabolic syndrome than those that were not. Conclusion A WHtR cutoff of 0.580 is optimal for discriminating individuals with metabolic syndrome in two nationally representative samples of young adults. This cutoff is an improvement over a