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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. 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

  3. 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.

  4. 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.

  5. 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,...

  6. 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

  7. 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)

  8. 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)

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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. 

  14. 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 ...

  15. 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 ...

  16. SOLVENCY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. 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...

  19. 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.

  20. 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...

  1. 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

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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%

  13. 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.

  14. 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%

  15. 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...

  16. Urine albumin/creatinine ratio, high sensitivity C-reactive protein and N-terminal pro brain natriuretic peptide--three new cardiovascular risk markers--do they improve risk prediction and influence treatment?

    DEFF Research Database (Denmark)

    Olsen, Michael H; Sehestedt, Thomas; Lyngbaek, Stig

    2010-01-01

    -proBNP), related to hemodynamic cardiovascular risk factors, high sensitivity C-reactive protein (hsCRP), related to metabolic cardiovascular risk factors and urine albumin/creatinine ratio (UACR), related to hemodynamic as well as metabolic risk factors. In healthy subjects with a 10-year risk of cardiovascular...... death lower than 5% based on HeartScore and therefore not eligible for primary prevention, the actual 10-year risk of cardiovascular death exceeded 5% in a small subgroup of subjects with UACR higher than the 95-percentile of approximately 1.6 mg/mmol. Combined use of high UACR or high hsCRP identified...... a larger subgroup of 16% with high cardiovascular risk in which primary prevention may be advised despite low-moderate cardiovascular risk based on HeartScore. Furthermore, combined use of high UACR or high Nt-proBNP in subjects with known cardiovascular disease or diabetes identified a large subgroup...

  17. 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

  18. 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…

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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)

  7. 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

  8. 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.

  9. 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.

  10. 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 .

  11. 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; ...

  12. 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

  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 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.

  15. 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.

  16. 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.

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. 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.

  20. 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...

  1. 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...

  2. 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.

  3. 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.

  4. 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

  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. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.)

  13. 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.

  14. 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

  15. 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

  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. 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.

  18. 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…

  19. 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.

  20. 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

  1. 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.

  2. 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. 

  3. 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%.

  4. 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.

  5. 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.

  6. 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.

  7. [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.

  8. 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.

  9. 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

  10. 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.

  11. Obesity Index That Better Predict Metabolic Syndrome: Body Mass Index, Waist Circumference, Waist Hip Ratio, or Waist Height Ratio

    Directory of Open Access Journals (Sweden)

    Abdulbari Bener

    2013-01-01

    Full Text Available Aim. The aim was to compare body mass index (BMI, waist circumference (WC, waist hip ratio (WHR, and waist height ratio (WHtR to identify the best predictor of metabolic syndrome (MetS among Qatari adult population. Methods. A cross-sectional survey from April 2011 to December 2012. Data was collected from 1552 participants followed by blood sampling. MetS was defined according to Third Adult Treatment Panel (ATPIII and International Diabetes Federation (IDF. Receiver operating characteristics (ROC curve analysis was performed. Results. Among men, WC followed by WHR and WHtR yielded the highest area under the curve (AUC (0.78; 95% CI 0.74–0.82 and 0.75; 95% CI 0.71–0.79, resp.. Among women, WC followed by WHtR yielded the highest AUC (0.81; 95% CI 0.78–0.85 & 0.79; 95% CI 0.76–0.83, resp.. Among men, WC at a cut-off 99.5 cm resulted in the highest Youden index with sensitivity 81.6% and 63.9% specificity. Among women, WC at a cut-off 91 cm resulted in the highest Youden index with the corresponding sensitivity and specificity of 86.5% and 64.7%, respectively. BMI had the lowest sensitivity and specificity in both genders. Conclusion. WC at cut-off 99.5 cm in men and 91 cm in women was the best predictor of MetS in Qatar.

  12. Improvements in disruption prediction at ASDEX Upgrade

    Energy Technology Data Exchange (ETDEWEB)

    Aledda, R., E-mail: raffaele.aledda@diee.unica.it; Cannas, B., E-mail: cannas@diee.unica.it; Fanni, A., E-mail: fanni@diee.unica.it; Pau, A., E-mail: alessandro.pau@diee.unica.it; Sias, G., E-mail: giuliana.sias@diee.unica.it

    2015-10-15

    Highlights: • A disruption prediction system for AUG, based on a logistic model, is designed. • The length of the disruptive phase is set for each disruption in the training set. • The model is tested on dataset different from that used during the training phase. • The generalization capability and the aging of the model have been tested. • The predictor performance is compared with the locked mode detector. - Abstract: In large-scale tokamaks disruptions have the potential to create serious damage to the facility. Hence disruptions must be avoided, but, when a disruption is unavoidable, minimizing its severity is mandatory. A reliable detection of a disruptive event is required to trigger proper mitigation actions. To this purpose machine learning methods have been widely studied to design disruption prediction systems at ASDEX Upgrade. The training phase of the proposed approaches is based on the availability of disrupted and non-disrupted discharges. In literature disruptive configurations were assumed appearing into the last 45 ms of each disruption. Even if the achieved results in terms of correct predictions were good, it has to be highlighted that the choice of such a fixed temporal window might have limited the prediction performance. In fact, it generates confusing information in cases of disruptions with disruptive phase different from 45 ms. The assessment of a specific disruptive phase for each disruptive discharge represents a relevant issue in understanding the disruptive events. In this paper, the Mahalanobis distance is applied to define a specific disruptive phase for each disruption, and a logistic regressor has been trained as disruption predictor. The results show that enhancements on the achieved performance on disruption prediction are possible by defining a specific disruptive phase for each disruption.

  13. Improvements in disruption prediction at ASDEX Upgrade

    International Nuclear Information System (INIS)

    Aledda, R.; Cannas, B.; Fanni, A.; Pau, A.; Sias, G.

    2015-01-01

    Highlights: • A disruption prediction system for AUG, based on a logistic model, is designed. • The length of the disruptive phase is set for each disruption in the training set. • The model is tested on dataset different from that used during the training phase. • The generalization capability and the aging of the model have been tested. • The predictor performance is compared with the locked mode detector. - Abstract: In large-scale tokamaks disruptions have the potential to create serious damage to the facility. Hence disruptions must be avoided, but, when a disruption is unavoidable, minimizing its severity is mandatory. A reliable detection of a disruptive event is required to trigger proper mitigation actions. To this purpose machine learning methods have been widely studied to design disruption prediction systems at ASDEX Upgrade. The training phase of the proposed approaches is based on the availability of disrupted and non-disrupted discharges. In literature disruptive configurations were assumed appearing into the last 45 ms of each disruption. Even if the achieved results in terms of correct predictions were good, it has to be highlighted that the choice of such a fixed temporal window might have limited the prediction performance. In fact, it generates confusing information in cases of disruptions with disruptive phase different from 45 ms. The assessment of a specific disruptive phase for each disruptive discharge represents a relevant issue in understanding the disruptive events. In this paper, the Mahalanobis distance is applied to define a specific disruptive phase for each disruption, and a logistic regressor has been trained as disruption predictor. The results show that enhancements on the achieved performance on disruption prediction are possible by defining a specific disruptive phase for each disruption.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. Improved techniques for predicting spacecraft power

    International Nuclear Information System (INIS)

    Chmielewski, A.B.

    1987-01-01

    Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance

  20. Improving LMA predictions with non standard interactions

    CERN Document Server

    Das, C R

    2010-01-01

    It has been known for some time that the well established LMA solution to the observed solar neutrino deficit fails to predict a flat energy spectrum for SuperKamiokande as opposed to what the data indicates. It also leads to a Chlorine rate which appears to be too high as compared to the data. We investigate the possible solution to these inconsistencies with non standard neutrino interactions, assuming that they come as extra contributions to the $\

  1. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. 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.

  3. 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...

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. Improving plant availability by predicting reactor trips

    International Nuclear Information System (INIS)

    Frank, M.V.; Epstein, S.A.

    1986-01-01

    Management Ahnalysis Company (MAC) has developed and applied two complementary software packages called RiTSE and RAMSES. Together they provide an mini-computer workstation for maintenance and operations personnel to dramatically reduce inadvertent reactor trips. They are intended to be used by those responsible at the plant for authorizing work during operation (such as a clearance coordinator or shift foreman in U.S. plants). They discover and represent all components, processes, and their interactions that could case a trip. They predict if future activities at the plant would cause a reactor trip, provide a reactor trip warning system and aid in post-trip cause analysis. RAMSES is a general reliability engineering software package that uses concepts of artificial intelligence to provide unique capabilities on personal and mini-computers

  9. 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

  10. 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.

  11. 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%

  12. 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.

  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. 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

  15. 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.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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 (...

  7. 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...

  8. Validation of the ureteral diameter ratio for predicting early spontaneous resolution of primary vesicoureteral reflux.

    Science.gov (United States)

    Arlen, Angela M; Kirsch, Andrew J; Leong, Traci; Cooper, Christopher S

    2017-08-01

    Management of primary vesicoureteral reflux (VUR) remains controversial, and reflux grade currently constitutes an important prognostic factor. Previous reports have demonstrated that distal ureteral diameter ratio (UDR) may be more predictive of outcome than vesicoureteral reflux (VUR) grade. We performed an external validation study in young children, evaluating early spontaneous resolution rates relative to reflux grade and UDR. Voiding cystourethrograms (VCUGs) were reviewed. UDR was computed by measuring largest ureteral diameter within the pelvis and dividing by the distance between the L1 and L3 vertebral bodies (Figure). VUR grade and UDR were tested in univariate and multivariable analyses. Primary outcome was status of VUR at last clinical follow-up (i.e. resolution, persistence, or surgical intervention). Demographics, VUR timing, laterality, and imaging indication were also assessed. One-hundred and forty-seven children (98 girls, 49 boys) were diagnosed with primary VUR at a mean age of 5.5 ± 4.7 months. Sixty-seven (45.6%) resolved spontaneously, 55 (37.4%) had persistent disease, and 25 (17%) were surgically corrected. Patients who spontaneously resolved had significantly lower VUR grade, refluxed later during bladder filling, and had significantly lower UDR. In a multivariable model, grade of VUR (p = 0.001), age early spontaneous resolution than grade alone. Furthermore, unlike traditional VUR grading where children with grade 1-5 may outgrow reflux depending on other factors, there appears to be a consistent UDR cutoff whereby patients are unlikely to resolve. In the present study, no child with a UDR greater than 0.43 experienced early spontaneous resolution, and only three (4.5%) of those with spontaneous resolution had a UDR above 0.35. UDR correlates with reflux grade, and is predictive of early resolution in children with primary VUR. UDR is an objective measurement of VUR, and provides valuable prognostic information about spontaneous

  9. Predictive value of platelet-to-lymphocyte ratio in severe degenerative aortic valve stenosis

    Directory of Open Access Journals (Sweden)

    Efe Edem

    2016-01-01

    Full Text Available Background: Aortic valve stenosis (AVS is the most common cause of left ventricular outflow obstruction, and its prevalence among elderly patients causes a major public health burden. Recently, platelet-to-lymphocyte ratio (PLR has been recognized as a novel prognostic biomarker that offers information about both aggregation and inflammation pathways. Since PLR indicates inflammation, we hypothesized that PLR may be associated with the severity of AVS due to chronic inflammation pathways that cause stiffness and calcification of the aortic valve. Materials and Methods: We retrospectively enrolled 117 patients with severe degenerative AVS, who underwent aortic valve replacement and 117 control patients in our clinic. PLR was defined as the absolute platelet count divided by the absolute lymphocyte count. Severe AVS was defined as calcification and sclerosis of the valve with a mean pressure gradient of >40 mmHg. Results: PLR was 197.03 ± 49.61 in the AVS group and 144.9 ± 40.35 in the control group, which indicated a statistically significant difference (P < 0.001. A receiver operating characteristic (ROC curve analysis demonstrated that PLR values over 188 predicted the severity of aortic stenosis with a sensitivity of 87% and a specificity of 70% (95% confidence interval = 0.734–0.882; P < 0.001; area under ROC curve: 0.808. Conclusion: We suggest that the level of PLR elevation is related to the severity of degenerative AVS, and PLR should be used to monitor patients' inflammatory responses and the efficacy of treatment, which will lead us to more closely monitor this high-risk population to detect severe degenerative AVS at an early stage.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Reduced brain/serum glucose ratios predict cerebral metabolic distress and mortality after severe brain injury.

    Science.gov (United States)

    Kurtz, Pedro; Claassen, Jan; Schmidt, J Michael; Helbok, Raimund; Hanafy, Khalid A; Presciutti, Mary; Lantigua, Hector; Connolly, E Sander; Lee, Kiwon; Badjatia, Neeraj; Mayer, Stephan A

    2013-12-01

    The brain is dependent on glucose to meet its energy demands. We sought to evaluate the potential importance of impaired glucose transport by assessing the relationship between brain/serum glucose ratios, cerebral metabolic distress, and mortality after severe brain injury. We studied 46 consecutive comatose patients with subarachnoid or intracerebral hemorrhage, traumatic brain injury, or cardiac arrest who underwent cerebral microdialysis and intracranial pressure monitoring. Continuous insulin infusion was used to maintain target serum glucose levels of 80-120 mg/dL (4.4-6.7 mmol/L). General linear models of logistic function utilizing generalized estimating equations were used to relate predictors of cerebral metabolic distress (defined as a lactate/pyruvate ratio [LPR] ≥ 40) and mortality. A total of 5,187 neuromonitoring hours over 300 days were analyzed. Mean serum glucose was 133 mg/dL (7.4 mmol/L). The median brain/serum glucose ratio, calculated hourly, was substantially lower (0.12) than the expected normal ratio of 0.40 (brain 2.0 and serum 5.0 mmol/L). In addition to low cerebral perfusion pressure (P = 0.05) and baseline Glasgow Coma Scale score (P brain/serum glucose ratios below the median of 0.12 were independently associated with an increased risk of metabolic distress (adjusted OR = 1.4 [1.2-1.7], P brain/serum glucose ratios were also independently associated with in-hospital mortality (adjusted OR = 6.7 [1.2-38.9], P brain/serum glucose ratios, consistent with impaired glucose transport across the blood brain barrier, are associated with cerebral metabolic distress and increased mortality after severe brain injury.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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

  17. 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.

  18. Low plasma arginine:asymmetric dimethyl arginine ratios predict mortality after intracranial aneurysm rupture

    DEFF Research Database (Denmark)

    Staalsø, Jonatan Myrup; Bergström, Anita; Edsen, Troels

    2013-01-01

    Asymmetrical dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthases, predicts mortality in cardiovascular disease and has been linked to cerebral vasospasm after aneurysmal subarachnoid hemorrhage (SAH). In this prospective study, we assessed whether circulating ADMA, arginine...

  19. 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.

  20. The FL/AC ratio for prediction of shoulder dystocia in women with gestational diabetes.

    Science.gov (United States)

    Duryea, Elaine L; Casey, Brian M; McIntire, Donald D; Twickler, Diane M

    2017-10-01

    To determine if sonographic variables, including fetal femur length to abdominal circumference (FL/AC) ratio, are associated with shoulder dystocia in women with gestational diabetes. This was a retrospective cohort study of women with gestational diabetes who delivered singleton infants at Parkland Hospital from 1997 to 2015. Diagnosis and treatment of gestational diabetes were uniform including sonography at 32-36 weeks. Biometric calculations were evaluated for correlation with shoulder dystocia. During the study period, 6952 women with gestational diabetes underwent a sonogram at a mean gestation of 34.8 ± 1.8 weeks. Of 4183 vaginal deliveries, 66 experienced shoulder dystocia (16/1000). The FL/AC was associated with shoulder dystocia (p dystocia in women with gestational diabetes. Additionally, it is a simple ratio that is independent of the reference used and remains stable, unlike age-adjusted AC and HC/AC ratio.

  1. Systematic discrepancies in Monte Carlo predictions of k-ratios emitted from thin films on substrates

    International Nuclear Information System (INIS)

    Statham, P; Llovet, X; Duncumb, P

    2012-01-01

    We have assessed the reliability of different Monte Carlo simulation programmes using the two available Bastin-Heijligers databases of thin-film measurements by EPMA. The MC simulation programmes tested include Curgenven-Duncumb MSMC, NISTMonte, Casino and PENELOPE. Plots of the ratio of calculated to measured k-ratios ('k calc /k meas ') against various parameters reveal error trends that are not apparent in simple error histograms. The results indicate that the MC programmes perform quite differently on the same dataset. However, they appear to show a similar pronounced trend with a 'hockey stick' shape in the 'k calc /k meas versus k meas ' plots. The most sophisticated programme PENELOPE gives the closest correspondence with experiment but still shows a tendency to underestimate experimental k-ratios by 10 % for films that are thin compared to the electron range. We have investigated potential causes for this systematic behaviour and extended the study to data not collected by Bastin and Heijligers.

  2. 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.

  3. 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.

  4. Fast predictive control for air-fuel ratio of SI engines using a ...

    African Journals Online (AJOL)

    In this paper MPC based on an adaptive neural network model is attempted for air fuel ratio (AFR), in which the model is adapted on-line to cope with nonlinear dynamics and parameter uncertainties. A radial basis function (RBF) network is employed and the recursive least squares (RLS) algorithm is used for weight ...

  5. 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.

  6. 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.

  7. Prediction of working memory performance in schizophrenia by plasma ratio of clozapine to N-desmethylclozapine.

    Science.gov (United States)

    Rajji, Tarek K; Mulsant, Benoit H; Davies, Simon; Kalache, Sawsan M; Tsoutsoulas, Christopher; Pollock, Bruce G; Remington, Gary

    2015-06-01

    Clozapine's potent antagonism of muscarinic M1 receptors is thought to worsen working memory deficits associated with schizophrenia. In contrast, its major metabolite, N-desmethylclozapine (NDMC), is thought to enhance working memory via its M1 receptor agonist activity. The authors hypothesized that the ratio of serum clozapine and NDMC concentrations would be inversely associated with working memory performance in schizophrenia. Thirty patients with schizophrenia or schizoaffective disorder who were receiving clozapine monotherapy at bedtime completed the MATRICS Consensus Cognitive Battery (MCCB) on the day their blood was collected to assess concentrations of clozapine and NDMC as well as serum anticholinergic activity. The clozapine/NDMC ratio was significantly and negatively associated with working memory performance after controlling for age, gender, education, and symptom severity. No significant associations were found between individual clozapine and NDMC concentrations and working memory performance. Serum anticholinergic activity was significantly associated with clozapine concentration, but not with working memory performance or NDMC concentration. No significant associations were found between any pharmacological measure and performance on other MCCB cognitive domains. This hypothesis-driven study confirms that clozapine/NDMC ratio is a strong predictor of working memory performance in patients with schizophrenia. This finding suggests that manipulating the clozapine/NDMC ratio could enhance cognition in patients with schizophrenia treated with clozapine. It also supports the study of procholinergic agents, such as M1 receptor-positive allosteric modulators, to enhance cognition in schizophrenia.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Discounting and Digit Ratio: Low 2D:4D Predicts Patience for a Sample of Females

    Directory of Open Access Journals (Sweden)

    Diego Aycinena

    2018-01-01

    Full Text Available Inter-temporal trade-offs are ubiquitous in human decision making. We study the relationship between preferences over such trade-offs and the ratio of the second digit to that of the forth (2D:4D, a marker for pre-natal exposure to sex hormones. Specifically, we study whether 2D:4D affects discounting. Our sample consists of 419 female participants of a Guatemalan conditional cash transfer program who take part in an experiment. Their choices in the convex time budget (CTB experimental task allow us to make inferences regarding their patience (discounting, while controlling for present-biasedness and preference for smoothing consumption (utility curvature. We find that women with lower digit ratios tend to be more patient.

  13. Towards accurate performance prediction of a vertical axis wind turbine operating at different tip speed ratios

    NARCIS (Netherlands)

    Rezaeiha, A.; Kalkman, I.; Blocken, B.J.E.

    2017-01-01

    Accurate prediction of the performance of a vertical-axis wind turbine (VAWT) using CFD simulation requires the employment of a sufficiently fine azimuthal increment (dθ) combined with a mesh size at which essential flow characteristics can be accurately resolved. Furthermore, the domain size needs

  14. Advancing individual tree biomass prediction: assessment and alternatives to the component ratio method

    Science.gov (United States)

    Aaron Weiskittel; Jereme Frank; David Walker; Phil Radtke; David Macfarlane; James Westfall

    2015-01-01

    Prediction of forest biomass and carbon is becoming important issues in the United States. However, estimating forest biomass and carbon is difficult and relies on empirically-derived regression equations. Based on recent findings from a national gap analysis and comprehensive assessment of the USDA Forest Service Forest Inventory and Analysis (USFS-FIA) component...

  15. 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.

  16. Facial Width-to-Height Ratio Does Not Predict Self-Reported Behavioral Tendencies

    OpenAIRE

    Kosinski, Michal

    2017-01-01

    A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. This work reexamined the links between fWHR and behavioral tendencies in a large sample of 137,163 participants. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-fa...

  17. The equivalent pore aspect ratio as a tool for pore type prediction in carbonate reservoirs

    OpenAIRE

    FOURNIER , François; Pellerin , Matthieu; Villeneuve , Quentin; Teillet , Thomas; Hong , Fei; Poli , Emmanuelle; Borgomano , Jean; Léonide , Philippe; Hairabian , Alex

    2018-01-01

    International audience; The equivalent pore aspect ratios (EPAR) provide a tool to detect pore types by combining P-and S-wave velocities, porosity, bulk density and mineralogical composition of carbonate rocks. The integration of laboratory measurements, well log data and petrographic analysis of 468 carbonate samples from various depositional and diagenetic settings (Lower Cretaceous pre-salt non-marine carbonates from offshore Brazil, Lower Cretaceous shallow-water platform carbonates from...

  18. Bax/Bcl-2 expression ratio in prediction of response to breast cancer radiotherapy

    Directory of Open Access Journals (Sweden)

    Hosein Azimian

    2018-03-01

    Full Text Available Objective(s: Radiotherapy is one of the most effective modalities of cancer therapy, but clinical responses of individual patients varies considerably. To enhance treatment efficiency it is essential to implement an individual-based treatment. The aim of present study was to identify the mechanism of intrinsic apoptosis pathway on radiosensitivity and normal tissue complications caused by the radiotherapy. Materials and Methods: Peripheral blood mononuclear cells from ten breast cancer patients were exposed to 6MV X-rays to deliver 1 and 2 Gy. Expression levels of Bax, Bcl-2, and Bax/Bcl-2 ratio were examined by relative quantitative RT-PCR. All the patients received similar tangential irradiation of the whole breast and conventional fractionation. Skin dosimetry was done by GAFChromic EBT-3 film and clinical radiosensitivity was determined using the acute reactions to radiotherapy of the skin according to Radiation Therapy Oncology Group score. All statistical analyses were performed using GraphPad Prism, version 7.01. Results: In the in-vitro experiment, Bax and Bax/Bcl-2 ratios were significantly increased with 1 and 2 Gy doses (PP0.05 for all patients. Conclusion: Significant correlation between Bax/Bcl-2 ratio determined before radiation therapy and clinical response in the patients, can be used as a biomarker to identify radiosensitive individuals. However, further studies are required to validate radiation-induced apoptotic biomarkers.

  19. 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.

  20. 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

  1. Pelvic interstitial brachytherapy - improving the therapeutic ratio with magnetic resonance imaging and optimization

    International Nuclear Information System (INIS)

    Swift, Patrick S.; Hricak, Hedvig; Forstner, Rosemary; Powell, C. Bethan; Purser, Phil; Weaver, Keith; Phillips, Theodore L.

    1996-01-01

    Introduction Interstitial brachytherapy in the pelvic region is often hampered by the radiation oncologist's inability to precisely differentiate tumor versus normal tissue during the planning and implantation procedures, often resulting in either excessive or incomplete coverage of tumor volume. The marked improvement in pelvic imaging seen with magnetic resonance, in conjunction with isodose optimization programs for remote-afterloading units, has created an opportunity to significantly improve the therapeutic ratio. Methods From 1992-1995, 23 interstitial perineal templates were performed in 22 patients with pelvic malignancies, using the pulsed low-dose-rate Selectron with dose optimization. MR imaging was performed immediately prior to the implant, with a MUPIT placed against the perineum and a vaginal obturator in place. These images were used for tumor volume measurements, determination of the number, depth and angle of needles required for the implant, and identification of position of normal tissues (rectum, small bowel, bladder) relative to the tumor. After implantation of stainless steel needles, orthogonal radiographs were obtained for isodose calculation, and planning carried out with isodose optimization. Patients were followed closely on a routine schedule, until time of last visit or until death. Every effort possible was made to assess local disease status at time of death. Results Sixteen patients with primary disease (14 cervix, 1 vulva, 1 vagina) and 6 with recurrent (2 with prior radiation) were implanted, all but 3 with curative intent. Nine patients with advanced cervix or vulvar cancer received concomitant chemotherapy (5FU + platinum or mitomycin-C) with the external beam therapy. At a median follow-up of 18.1 months for all cases, only three patients have failed locally for an actuarial local control of 85% at 1.5 years. Nine patients are alive and free of disease, 8 are alive with distant disease only (mean follow-up of 19.1 months), 2

  2. Improved environmental and forensics measurements using multiple ion counters in isotope ratio mass spectrometry

    International Nuclear Information System (INIS)

    Goldberg, S.A.; Richter, S.; Schwieters, H.

    2002-01-01

    Full text: A new detector system designed for isotope ratio mass spectrometers provides improved precision on measurements of samples with very low amounts ( -11 grams) of analyte. An array of continuous dynode electron multipliers has been installed on a new ThermoFinnigan MAT Triton thermal ionization mass spectrometer acquired by the New Brunswick Laboratory. These ion counters are modifications of miniaturized, commercially-available continuous dynode electron multipliers. They can be readily installed to replace individual Faraday cups in a multi-detector mass spectrometer or bundled together and located along the detector plane with a set of Faraday cups. On the New Brunswick Laboratory mass spectrometer, nine Faraday cups, one conventional discrete dynode electron multiplier, and seven miniaturized ion counters were installed. Six of the small ion counters were bundled together and positioned on the high mass side of the Low 4 Faraday cup. One additional ion counter was positioned on the low mass side of the Low 4 Faraday cup. This arrangement allows for the simultaneous measurement of all uranium (including 233 U) or plutonium (including 244 Pu) isotopes, and allows for the measurement of larger 238 U intensities on the Faraday cup if needed. Unit mass spacing of U, Pu, or other actinides is readily achieved by the use of a mass dispersion zoom lens. The advantage of multiple ion counting is the simultaneous collection of isotopes. It overcomes many of the problems such as transient signal variation in sample emission and ionization. For a given sample, multiple ion counting generates a greater number of counts for each isotope relative to single detector ion counting and provides improved counting statistics by a factor of two or more. Initial tests indicate that the multiple ion counters exhibit high counting efficiency, a dark noise of less than 10 counts per minute and typically less than 1 count per minute, and show linear response characteristics over

  3. 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.

  4. 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.

  5. Prediction of Clay/Organic Carbon Ratio Using On-The-Go Proximal Spectroscopy

    DEFF Research Database (Denmark)

    Tabatabai, Salman; Knadel, Maria; Greve, Mogens Humlekrog

    using a commercial mobile sensor platform (Veris Technologies, USA). Principal components analysis was performed on spectra followed by fuzzy c-means clustering to select 15 representative sampling locations on each field. Clay and OC were determined for all samples using pipette and ignition methods......-index using laboratory visible near-infrared spectroscopy (Vis-NIRS) for a wide range of soils was recently published. In this study, we tested a direct prediction of n-index in the field using a proximal spectrometer. Spectral reflectance of eight agricultural fields was measured in the range of 350-2200 nm......, respectively and n-index was calculated (range: 1.16-8.45). Partial least squares (PLS) models were calibrated using pretreated vis-NIR spectra as predictors and n-index as the response. Ventian Blinds (VB) cross validation (CV) using 15 segments, one-field-out (OFO) CV and regression prediction using...

  6. Predicting the hurricane damage ratio of commercial buildings by claim payout from Hurricane Ike

    OpenAIRE

    J. M. Kim; P. K. Woods; Y. J. Park; T. H. Kim; J. S. Choi; K. Son

    2013-01-01

    The increasing occurrence of natural disaster events and related damages have led to a growing demand for models that predict financial loss. Although considerable research has studied the financial losses related to natural disaster events, and has found significant predictors, there has not yet been a comprehensive study that addresses the relationship among the vulnerabilities, natural disasters, and economic losses of the individual buildings. This study...

  7. Can the cerebroplacental ratio (CPR) predict intrapartum fetal compromise? : a prospective observational study

    OpenAIRE

    Page, Ann-Sophie; Page, Geert; Dehaene, Isabelle; Roets, Ellen; Roelens, Kristien

    2017-01-01

    Objective: To investigate the potential clinical use of serial fetal CPR measurements during the last month of pregnancy for the prediction of adverse perinatal outcome in unselected low-risk pregnancies. Methods: A multicenter prospective observational cohort study in 315 consecutively recruited low-risk pregnancies. All eligible pregnancies underwent serial sonographic evaluation of fetal weight and Doppler indices at two week intervals, from 36 weeks gestation until delivery. Data were ...

  8. 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....

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Biodegradation measurements confirm the predictive value of the O: C-ratio for biochar recalcitrance

    DEFF Research Database (Denmark)

    Bai, Mo; Wilske, Burkhard; Buegger, Franz

    2014-01-01

    Suitable predictors of degradability are sought to support the identification of biochars with large potential to increase C sequestration in soils. We determined the biodegradation of 9 chars from hydrothermal carbonization and pyrolysis in two agricultural soils. The 200- and 115-day degradation...... correlated strongly with the O:C- and slightly with the H:C-atomic ratio of 9 and 14 biochars, respectively. Highest temperature treatment and ash content did not show similar correlations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim....

  14. 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

  15. 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.

  16. Improvement of the tetrachloromercurate absorption technique for measuring low atmospheric SO2 mixing ratios

    Science.gov (United States)

    Jaeschke, W.; Beltz, N.; Haunold, W.; Krischke, U.

    1997-07-01

    During the Gas-Phase Sulfur Intercomparison Experiment (GASIE) in 1994 an analytical system for measuring sulfur dioxide mixing ratios at low parts per trillion (pptv) levels was employed. It is based on the absorption of SO2 on a tetrachloromercurate(II)-impregnated filter. The subsequent analysis uses a chemiluminescence reaction by treating the resulting disulfitomercurate(II) complex with an acidic cerium sulfate solution. An improved sampling device has been introduced that increases the maximum sampling volume from 200 L to 500 L. It is also possible to determine the blank value accurately for each sample. The absorption efficiency of the sampling system is 98.7±6.4% at a nominal flow rate of 10 L/min. The calculated (3σ) detection limit is 3±1 pptv SO2. The sample solution is stable for up to 30 days, which allows the samples to be safely stored or shipped before analysis. This permits the use of a sensitive, compact, and reliable sampling system in the field with subsequent analysis under optimal conditions in the laboratory. A continuous flow chemiluminescence (CFCL) analyzer for on-line measurements is also presented. The system is based on the same chemical principles as the described filter technique.

  17. The PE Ratio and the Predicted Earnings Growth – the Case of Poland

    Directory of Open Access Journals (Sweden)

    Kurach Radosław

    2015-06-01

    Full Text Available We examine the components of equity returns on the Polish capital market. To analyse the underlying complexity of returns we took into consideration the model designed by Leibowitz (1999. This model captures three factors: dividend yield, expected growth in earnings and expected change in price-to-earnings (PE ratio. We applied this model to analyse the average discount/premium not only to particular shares but to market averages as well. Firstly, we examined the variation of PE across the companies (as adapted from Penman (1996 to analyse the average rate of return and their striking distance of individual stocks from a ‘normal’ level. Then we checked the transitory earnings in the portfolios of high PE, whereby a fall in current earnings relative to sustainable level of earnings leads to a transitory high PE ratio. We expect that the effect of transience in current year earnings can be significant. Lastly, we analysed the individual companies in order to check what percentage of companies give a “correct” signal about future prospects.

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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...

  3. 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...

  4. 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....

  5. Facial Width-to-Height Ratio Does Not Predict Self-Reported Behavioral Tendencies.

    Science.gov (United States)

    Kosinski, Michal

    2017-11-01

    A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. This work reexamined the links between fWHR and behavioral tendencies in a large sample of 137,163 participants. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-factor model of personality, impulsiveness, sense of fairness, sensational interests, self-monitoring, impression management, and satisfaction with life. The findings revealed that fWHR is not substantially linked with any of these self-reported measures of behavioral tendencies, calling into question whether the links between fWHR and behavior generalize beyond the small samples and specific experimental settings that have been used in past fWHR research.

  6. Group Facial Width-to-Height Ratio Predicts Intergroup Negotiation Outcomes.

    Science.gov (United States)

    Yang, Yu; Tang, Chen; Qu, Xiaofei; Wang, Chao; Denson, Thomas F

    2018-01-01

    Past studies have found that the facial width-to-height ratio (FWHR) is associated with a range of traits and behaviors that are possibly important to dyadic negotiations. However, it is unknown whether the FWHR would have an impact on intergroup negotiations, which happen frequently and often have higher stakes in the real world. To examine this question, in the current study, we randomly assigned 1,337 Chinese business executives into 288 groups and they completed a multi-issue negotiation exercise against each other. Results showed that groups with larger maximum individual FWHRs achieved objectively better negotiation outcomes. We conclude that groups containing individuals with relatively large FWHRs can claim more value in negotiations between groups.

  7. Accurate prediction of the ammonia probes of a variable proton-to-electron mass ratio

    Science.gov (United States)

    Owens, A.; Yurchenko, S. N.; Thiel, W.; Špirko, V.

    2015-07-01

    A comprehensive study of the mass sensitivity of the vibration-rotation-inversion transitions of 14NH3, 15NH3, 14ND3 and 15ND3 is carried out variationally using the TROVE approach. Variational calculations are robust and accurate, offering a new way to compute sensitivity coefficients. Particular attention is paid to the Δk = ±3 transitions between the accidentally coinciding rotation-inversion energy levels of the ν2 = 0+, 0-, 1+ and 1- states, and the inversion transitions in the ν4 = 1 state affected by the `giant' l-type doubling effect. These transitions exhibit highly anomalous sensitivities, thus appearing as promising probes of a possible cosmological variation of the proton-to-electron mass ratio μ. Moreover, a simultaneous comparison of the calculated sensitivities reveals a sizeable isotopic dependence which could aid an exclusive ammonia detection.

  8. General correlation for prediction of critical heat flux ratio in water cooled channels

    Energy Technology Data Exchange (ETDEWEB)

    Pernica, R.; Cizek, J.

    1995-09-01

    The paper present the general empirical Critical Heat Flux Ration (CHFR) correlation which is valid for vertical water upflow through tubes, internally heated concentric annuli and rod bundles geometries with both wide and very tight square and triangular rods lattices. The proposed general PG correlation directly predicts the CHFR, it comprises axial and radial non-uniform heating, and is valid in a wider range of thermal hydraulic conditions than previously published critical heat flux correlations. The PG correlation has been developed using the critical heat flux Czech data bank which includes more than 9500 experimental data on tubes, 7600 data on rod bundles and 713 data on internally heated concentric annuli. Accuracy of the CHFR prediction, statistically assessed by the constant dryout conditions approach, is characterized by the mean value nearing 1.00 and the standard deviation less than 0.06. Moverover, a subchannel form of the PG correlations is statistically verified on Westinghouse and Combustion Engineering rod bundle data bases, i.e. more than 7000 experimental CHF points of Columbia University data bank were used.

  9. 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.

  10. 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

  11. 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

  12. Improvement in decay ratio calculation in LAPUR5 methodology for BWR instability

    International Nuclear Information System (INIS)

    Li Hsuannien; Yang Tzungshiue; Shih Chunkuan; Wang Jongrong; Lin Haotzu

    2009-01-01

    LAPUR5, based on frequency domain approach, is a computer code that analyzes the core stability and calculates decay ratios (DRs) of boiling water nuclear reactors. In current methodology, one set of parameters (three friction multipliers and one density reactivity coefficient multiplier) is chosen for LAPUR5 input files, LAPURX and LAPURW. The calculation stops and DR for this particular set of parameters is obtained when the convergence criteria (pressure, mass flow rate) are first met. However, there are other sets of parameters which could also meet the same convergence criteria without being identified. In order to cover these ranges of parameters, we developed an improved procedure to calculate DR in LAPUR5. First, we define the ranges and increments of those dominant input parameters in the input files for DR loop search. After LAPUR5 program execution, we can obtain all DRs for every set of parameters which satisfy the converge criteria in one single operation. The part for loop search procedure covers those steps in preparing LAPURX and LAPURW input files. As a demonstration, we looked into the reload design of Kuosheng Unit 2 Cycle 22. We found that the global DR has a maximum at exposure of 9070 MWd/t and the regional DR has a maximum at exposure of 5770 MWd/t. It should be noted that the regional DR turns out to be larger than the global ones for exposures less than 5770 MWd/t. Furthermore, we see that either global or regional DR by the loop search method is greater than the corresponding values from our previous approach. It is concluded that the loop search method can reduce human error and save human labor as compared with the previous version of LAPUR5 methodology. Now the maximum DR can be effectively obtained for a given plant operating conditions and a more precise stability boundary, with less uncertainty, can be plotted on plant power/flow map. (author)

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. Lymph node ratio predicts the benefit of post-operative radiotherapy in oral cavity cancer

    International Nuclear Information System (INIS)

    Urban, Damien; Gluck, Iris; Pfeffer, M. Raphael; Symon, Zvi; Lawrence, Yaacov R.

    2013-01-01

    Background: The standard treatment for non-metastatic oral cavity squamous cell carcinoma (OCSCC) is surgical resection followed by post-operative radiotherapy (PORT) with/without chemotherapy in high risk patients. Given the substantial toxicity of PORT we assessed lymph node ratio (LNR) as a predictor of PORT benefit. Design: By using the Surveillance, Epidemiology and End Results (SEER) database, we analyzed all node positive OCSCC patients diagnosed between 1988 and 2007 who underwent neck dissection. LNR was categorized into three groups: <6%, 6–12.5% and >12.5%. Results: In 3091 subjects identified, median survival was 32, 25 and 16 months for LNR Groups 1, 2 and 3, respectively. On multivariate analysis, survival was associated with age, race, grade, tumor size, nodal stage, extra-capsular extension, use of PORT and LNR. When stratified by LNR group, PORT was associated with a survival benefit only in Group 3 (LNR > 12.5%): 2 year survival 25% vs 37%. No benefit to PORT was seen when the LNR ⩽ 12.5%: 2 year survival 51% vs 54%. Conclusion: A low LNR is associated with extended survival in LN positive OCSCC. The survival benefit associated with PORT in this disease appears to be limited to those with a LNR > 12.5%. Validation is required prior to the clinical implementation of our findings

  19. Impact of the basal metabolic ratio in predicting early deaths after allogeneic stem cell transplantation.

    Science.gov (United States)

    Nishiwaki, Satoshi; Miyamura, Koichi; Seto, Aika; Watanabe, Keisuke; Yanagisawa, Mayumi; Imahashi, Nobuhiko; Shimba, Makoto; Yasuda, Takahiko; Kuwatsuka, Yachiyo; Oba, Taku; Terakura, Seitaro; Kodera, Yoshihisa

    2009-09-01

    Early deaths after allogeneic stem cell transplantation (allo-SCT) are of major concern. On the assumption that both decreased and increased basal metabolism might relate to early deaths, we analyzed the risk factors for overall survival to days 30 (OS30) and 60 (OS60). The Harris-Benedict equation was used to calculate basal metabolism. Comparing a patient's basal metabolism (PBM) calculated from pretransplant body weight with the standard basal metabolism (SBM) calculated from standard body weight (body mass index (BMI) = 22), we defined the basal metabolic ratio (BMR) as a parameter (BMR = PBM/SBM). We retrospectively analyzed 360 adult patients transplanted between 1997 and 2006 at a single center in Japan. A multivariate analysis of OS30 showed risk factors to be: BMR BMR; LBR) (P = 0.01), BMR > 1.05 (high BMR; HBR) (P = 0.005) and non-complete remission (non-CR) (P 5 0.001), whereas a multivariate analysis of OS60 showed those risk factors to be: LBR (P = 0.02), HBR (P = 0.04), non-CR (P = 0.002), and performance status BMR BMR; ABR) (96.8 and 90.3% for ABR, 87.1 and 76.2% for LBR, and 87.8 and 81.1% for HBR). In conclusion, BMR could prove to be a predictor of early death after allo-SCT.

  20. 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)

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. Neutrophil-lymphocyte ratio: a new predictive and prognostic factor in patients with Bell palsy.

    Science.gov (United States)

    Özler, Gül Soylu; Günak, Güldem

    2014-05-01

    The aim of this study was to investigate whether neutrophil-lymphocyte ratio (NLR) levels are elevated in patients with Bell palsy (BP). Moreover, we aimed to find out whether there is a correlation between NLR levels and the severity and prognosis of BP. The study group consisted of 25 subjects who presented with BP and 25 control subjects with no evidence of facial nerve pathology. The subjects underwent a general physical examination; an assessment of laboratory blood parameters; and a cranial magnetic resonance imaging, using gadolinium as a contrast medium. The mean (SD) NLR values were 2.16 (0.80) in the patients with BP and 1.36 (0.48) in the control group. The mean NLR values in the patients with BP were significantly higher than in the control group (P = 0.0001). There was a positive correlation between NLR values and grade of facial paralysis (r = 0.661, P = 0.0001). The mean (SD) NLR values in the grades III, IV, V, and VI BP groups were 1.40 (0.54), 1.78 (0.44), 3.00 (0.63), and 2.60 (0.54), respectively. The mean NLR values in the grade V BP group were significantly higher than in the other groups (P = 0.0001). In addition, there was a positive correlation between NLR values and prognosis of facial paralysis (r = 0.239, P = 0.251). There is no previous study that investigated the association between NLR and BP in the literature. Higher NLR values in patients with BP may be a predictor of worse prognosis.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Improved Cyclability of Liquid Electrolyte Lithium/Sulfur Batteries by Optimizing Electrolyte/Sulfur Ratio

    Directory of Open Access Journals (Sweden)

    Sheng S. Zhang

    2012-12-01

    Full Text Available A liquid electrolyte lithium/sulfur (Li/S cell is a liquid electrochemical system. In discharge, sulfur is first reduced to highly soluble Li2S8, which dissolves into the organic electrolyte and serves as the liquid cathode. In solution, lithium polysulfide (PS undergoes a series of complicated disproportionations, whose chemical equilibriums vary with the PS concentration and affect the cell’s performance. Since the PS concentration relates to a certain electrolyte/sulfur (E/S ratio, there is an optimized E/S ratio for the cyclability of each Li/S cell system. In this work, we study the optimized E/S ratio by measuring the cycling performance of Li/S cells, and propose an empirical method for determination of the optimized E/S ratio. By employing an electrolyte of 0.25 m LiSO3CF3-0.25 m LiNO3 dissolved in a 1:1 (wt:wt mixture of dimethyl ether (DME and 1,3-dioxolane (DOL in an optimized E/S ratio, we show that the Li/S cell with a cathode containing 72% sulfur and 2 mg cm−2 sulfur loading is able to retain a specific capacity of 780 mAh g−1 after 100 cycles at 0.5 mA cm−2 between 1.7 V and 2.8 V.

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. The High Aspect Ratio Design (HARD): A candidate ITER concept with improved technology phase performance

    International Nuclear Information System (INIS)

    Nevins, W.M.; Perkins, L.J.; Wesley, J.C.

    1992-10-01

    The High Aspect Ratio Design (HARD) International Thermonuclear Experimental Reactor (ITER) concept developed by the US ITER team is an alternate to the low-aspect-ratio ITER design developed by the ITER participants during the Conceptual Design Activity (CDA). The CDA design, referred to hereafter as ITER CDA, has an aspect ratio, A, of 2.79, a toroidal magnetic field, B T , of 4.85 T, and a plasma current, I p , of 22 MA for operation with an ignited plasma. In contrast, HARD employs higher aspect ratio, A = 4.0, higher toroidal field, B T = 7.11 T, and lower plasma current, I p = 14.8 MA for ignition operation. The cross sections of the two designs are compared in. The parameters and performance of HARD and ITER CDA for inductively driven ignition operation are compared in. The HARD parameters provide the same ignition performance (ignition margin evaluated against ITER-89P confinement scaling) as ITER CDA in a device with comparable size and cost. However, the reason for advancing HARD rather than ITER CDA as the ITER design concept is not inductively driven ignition performance but HARD's significantly enhanced potential to achieve the technology testing and steady-state operation goals of the ITER objectives with non-inductive current drive

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  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. 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.

  11. 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.

  12. Improving the signal-to-noise ratio in mass and ion kinetic energy spectrometers

    International Nuclear Information System (INIS)

    Brenton, A.G.; Beynon, J.H.; Morgan, R.P.

    1979-01-01

    The signal-to-noise ratio in mass and ion kinetic energy spectrometers is limited by noise generated from the presence of scattered ions and neutrals. Methods of eliminating this are illustrated with reference to the ZAB-2F instrument manufactured by VG-Micromass Ltd. It is estimated that after the modifications the instrument is capable, on a routine basis, of measuring peaks corresponding to the arrival of ions at a rate of the order of 1 ion s -1 . (Auth.)

  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. 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.

  15. 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

  16. 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.

  17. Climatic extremes improve predictions of spatial patterns of tree species

    Science.gov (United States)

    Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

    2009-01-01

    Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

  18. Improved apparatus for predictive diagnosis of rotator cuff disease

    Science.gov (United States)

    Pillai, Anup; Hall, Brittany N.; Thigpen, Charles A.; Kwartowitz, David M.

    2014-03-01

    Rotator cuff disease impacts over 50% of the population over 60, with reports of incidence being as high as 90% within this population, causing pain and possible loss of function. The rotator cuff is composed of muscles and tendons that work in tandem to support the shoulder. Heavy use of these muscles can lead to rotator cuff tear, with the most common causes is age-related degeneration or sport injuries, both being a function of overuse. Tears ranges in severity from partial thickness tear to total rupture. Diagnostic techniques are based on physical assessment, detailed patient history, and medical imaging; primarily X-ray, MRI and ultrasonography are the chosen modalities for assessment. The final treatment technique and imaging modality; however, is chosen by the clinician is at their discretion. Ultrasound has been shown to have good accuracy for identification and measurement of full-thickness and partial-thickness rotator cuff tears. In this study, we report on the progress and improvement of our method of transduction and analysis of in situ measurement of rotator cuff biomechanics. We have improved the ability of the clinician to apply a uniform force to the underlying musculotendentious tissues while simultaneously obtaining the ultrasound image. This measurement protocol combined with region of interest (ROI) based image processing will help in developing a predictive diagnostic model for treatment of rotator cuff disease and help the clinicians choose the best treatment technique.

  19. Are neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as effective as Fournier's gangrene severity index for predicting the number of debridements in Fourner's gangrene?

    Science.gov (United States)

    Kahramanca, Sahin; Kaya, Oskay; Özgehan, Gülay; Irem, Burak; Dural, Ibrahim; Küçükpınar, Tevfik; Kargıcı, Hülagü

    2014-03-01

    Fournier's gangrene (FG) is a rapidly progressive and necrotizing infection of the subcutaneous and fascial tissues with a high mortality rate. In the present study, we aimed to investigate prognostic factors and analyze the outcomes of 68 patients in a tertiary reference hospital. Patients admitted to the emergency department were investigated retrospectively between January 2006 and January 2013 and divided into two groups. The patients in Group I (G1) required one debridement, and Group II (G2) patients required more than one. Patient demographic and clinical characteristics were encoded. Fournier's Gangrene Severity Index (FGSI) scores, neutrophil-lymphocyte ratios (NLR), and platelet-lymphocyte ratios (PLR) were calculated. Prognostic factors were compared between the groups. There were no statistically significant differences between the groups in terms of mean age, female-male ratio, or duration of symptoms on admission; however, there were more infection sources, predisposal factors, and positive culture results in G2. Additionally, hospital stay, total cost, and mortality rate values were high in G2. We found statistically higher NLR and PLR ratios in G2, but there was no significant difference in FGSI scores between the groups. The FGSI scoring system was not found to be valuable in determining prognosis. However, NLR and PLR were valuable, and previous use of NLR and PLR for determining Fournier's gangrene prognosis could not be found in the English literature.

  20. A high ratio of apoptosis to proliferation correlates with improved survival after radiotherapy for cervical adenocarcinoma

    International Nuclear Information System (INIS)

    Sheridan, Mary T.; Cooper, Rachel A.; West, Catharine M.L.

    1999-01-01

    Purpose: A retrospective study was made of the role of apoptosis in determining radiotherapy outcome in 39 adenocarcinoma of the cervix. A comparison was also made of the detection of apoptosis by morphology and the TdT dUtp nick end-labeling (TUNEL) assay. Methods and Materials: The level of apoptosis was assessed in paraffin-embedded sections by cell morphology, the TUNEL assay, and a combination of the two. A total of 2,000 cells were counted per section, to obtain apoptotic (AI) and mitotic (MI) indices. Results: Patients with a high AI had a higher survival rate than those with a low AI, however, the difference was not significant. Using a ratio of apoptosis to proliferation indices, patients with an AI:MI > median had significantly better survival than those with AI:MI < median. This was true where the AI was quantified by morphology alone (p = 0.030) or in combination with the TUNEL assay (p = 0.008). Where the AI was quantified by a combination of morphology and TUNEL, the 5-year survival rates for women with AI:MI greater or less than the median were 81% and 25%, respectively. Conclusion: A high ratio of AI:MI in adenocarcinoma of the cervix indicates a good prognosis. A combination of the TUNEL assay and morphology provided the best discrimination between outcome groups

  1. 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.

  2. Secondary antibodies as tools to improve tumor to non tumor ratio at radioimmunolocalisation and radioimmunotherapy

    International Nuclear Information System (INIS)

    Ullen, A.; Riklund Aalstroem, K.; Hietala, S.O.; Nilsson, B.; Aerlestig, L.; Stigbrand, T.

    1996-01-01

    One way of selectively improving the efficiency of radioimmunolocalization and radioimmunotherapy is to eliminate redundant, circulating, non-targeting radiolabeled antibodies after saturation of the target sites. Secondary antibodies of different types have been proposed as clearing agents for such purposes. The conceptually different approaches of the 'secondary antibody' strategy including its advantages and limitations are discussed. This mini-review also presents a model describing the kinetics of the components (the antigen, the primary and secondary antibodies) and approaches required to improve the efficacy of both radioimmunolocalization and radioimmunotherapy. (orig.)

  3. 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.

  4. A likelihood ratio-based method to predict exact pedigrees for complex families from next-generation sequencing data.

    Science.gov (United States)

    Heinrich, Verena; Kamphans, Tom; Mundlos, Stefan; Robinson, Peter N; Krawitz, Peter M

    2017-01-01

    Next generation sequencing technology considerably changed the way we screen for pathogenic mutations in rare Mendelian disorders. However, the identification of the disease-causing mutation amongst thousands of variants of partly unknown relevance is still challenging and efficient techniques that reduce the genomic search space play a decisive role. Often segregation- or linkage analysis are used to prioritize candidates, however, these approaches require correct information about the degree of relationship among the sequenced samples. For quality assurance an automated control of pedigree structures and sample assignment is therefore highly desirable in order to detect label mix-ups that might otherwise corrupt downstream analysis. We developed an algorithm based on likelihood ratios that discriminates between different classes of relationship for an arbitrary number of genotyped samples. By identifying the most likely class we are able to reconstruct entire pedigrees iteratively, even for highly consanguineous families. We tested our approach on exome data of different sequencing studies and achieved high precision for all pedigree predictions. By analyzing the precision for varying degrees of relatedness or inbreeding we could show that a prediction is robust down to magnitudes of a few hundred loci. A java standalone application that computes the relationships between multiple samples as well as a Rscript that visualizes the pedigree information is available for download as well as a web service at www.gene-talk.de CONTACT: heinrich@molgen.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  5. 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.

  6. Improving building performance using smart building concept: Benefit cost ratio comparison

    Science.gov (United States)

    Berawi, Mohammed Ali; Miraj, Perdana; Sayuti, Mustika Sari; Berawi, Abdur Rohim Boy

    2017-11-01

    Smart building concept is an implementation of technology developed in the construction industry throughout the world. However, the implementation of this concept is still below expectations due to various obstacles such as higher initial cost than a conventional concept and existing regulation siding with the lowest cost in the tender process. This research aims to develop intelligent building concept using value engineering approach to obtain added value regarding quality, efficiency, and innovation. The research combined quantitative and qualitative approach using questionnaire survey and value engineering method to achieve the research objectives. The research output will show additional functions regarding technology innovation that may increase the value of a building. This study shows that smart building concept requires higher initial cost, but produces lower operational and maintenance costs. Furthermore, it also confirms that benefit-cost ratio on the smart building was much higher than a conventional building, that is 1.99 to 0.88.

  7. Improvements in heavy water analysis using a ratio recording infrared spectrophotometer (Preprint No. CA-12)

    Energy Technology Data Exchange (ETDEWEB)

    Sutawane, U B; Alphonse, K P; Rathi, B N [Bhabha Atomic Research Centre, Bombay (India). Heavy Water Div.

    1989-04-01

    With a view to optimise existing analytical procedures for routine analyses of heavy water, studies were carried out using a ratio recording instrument with and without a reference beam attenuator in infrared spectrophotometric method. Absorbance difference as well as absorbance values with different path length cells were used for measurements. Due to various practical considerations, a method based on measurement of absorbance values rather than absorbance difference was found to be convenient for all routine work. However, scanning is essential since there is slight shifting of peak position. Measurements at fixed wave lengths should generally be avoided. Use of standards for calibration of instrument is essential and frequent check of calibration is recommended. Optimum conditions for analysis of heavy water in different ranges on the instrument used in this study are tabulated. (author). 6 refs., 1 tab.

  8. Improvements in heavy water analysis using a ratio recording infrared spectrophotometer (Preprint No. CA-12)

    International Nuclear Information System (INIS)

    Sutawane, U.B.; Alphonse, K.P.; Rathi, B.N.

    1989-04-01

    With a view to optimise existing analytical procedures for routine analyses of heavy water, studies were carried out using a ratio recording instrument with and without a reference beam attenuator in infrared spectrophotometric method. Absorbance difference as well as absorbance values with different path length cells were used for measurements. Due to various practical considerations, a method based on measurement of absorbance values rather than absorbance difference was found to be convenient for all routine work. However, scanning is essential since there is slight shifting of peak position. Measurements at fixed wave lengths should generally be avoided. Use of standards for calibration of instrument is essential and frequent check of calibration is recommended. Optimum conditions for analysis of heavy water in different ranges on the instrument used in this study are tabulated. (author). 6 refs., 1 tab

  9. Improving Therapeutic Ratio in Head and Neck Cancer with Adjuvant and Cisplatin-Based Treatments

    Directory of Open Access Journals (Sweden)

    Loredana G. Marcu

    2013-01-01

    Full Text Available Advanced head and neck cancers are difficult to manage despite the large treatment arsenal currently available. The multidisciplinary effort to increase disease-free survival and diminish normal tissue toxicity was rewarded with better locoregional control and sometimes fewer side effects. Nevertheless, locoregional recurrence is still one of the main reasons for treatment failure. Today, the standard of care in head and neck cancer management is represented by altered fractionation radiotherapy combined with platinum-based chemotherapy. Targeted therapies as well as chronotherapy were trialled with more or less success. The aim of the current work is to review the available techniques, which could contribute towards a higher therapeutic ratio in the treatment of advanced head and neck cancer patients.

  10. 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

  11. Improving predictive capabilities of environmental change with GLOBE data

    Science.gov (United States)

    Robin, Jessica Hill

    This dissertation addresses two applications of Normalized Difference Vegetation Index (NDVI) essential for predicting environmental changes. The first study focuses on whether NDVI can improve model simulations of evapotranspiration for temperate Northern (>35°) regions. The second study focuses on whether NDVI can detect phenological changes in start of season (SOS) for high Northern (>60°) environments. The overall objectives of this research were to (1) develop a methodology for utilizing GLOBE data in NDVI research; and (2) provide a critical analysis of NDVI as a long-term monitoring tool for environmental change. GLOBE is an international partnership network of K-12 students, teachers, and scientists working together to study and understand the global environment. The first study utilized data collected by one GLOBE school in Greenville, Pennsylvania and the second utilized phenology observations made by GLOBE students in Alaska. Results from the first study showed NDVI could predict transpiration periods for environments like Greenville, Pennsylvania. In phenological terms, these environments have three distinct periods (QI, QII, and QIII). QI reflects onset of the growing season (mid March--mid May) when vegetation is greening up (NDVI 0.60). Results from the second study showed that a climate threshold of 153 +/- 22 growing degree days was a better predictor of SOS for Fairbanks than a NDVI threshold applied to temporal AVHRR and MODIS datasets. Accumulated growing degree days captured the interannual variability of SOS better than the NDVI threshold and most closely resembled actual SOS observations made by GLOBE students. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska. Both studies did show that GLOBE data provides an important source of input and validation information for NDVI research.

  12. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

    Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

    2009-09-01

    An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

  13. 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.

  14. 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.

  15. Polarization modeling and predictions for DKIST part 3: focal ratio and thermal dependencies of spectral polarization fringes and optic retardance

    Science.gov (United States)

    Harrington, David M.; Sueoka, Stacey R.

    2018-01-01

    Data products from high spectral resolution astronomical polarimeters are often limited by fringes. Fringes can skew derived magnetic field properties from spectropolarimetric data. Fringe removal algorithms can also corrupt the data if the fringes and object signals are too similar. For some narrow-band imaging polarimeters, fringes change the calibration retarder properties and dominate the calibration errors. Systems-level engineering tools for polarimetric instrumentation require accurate predictions of fringe amplitudes, periods for transmission, diattenuation, and retardance. The relevant instabilities caused by environmental, thermal, and optical properties can be modeled and mitigation tools developed. We create spectral polarization fringe amplitude and temporal instability predictions by applying the Berreman calculus and simple interferometric calculations to optics in beams of varying F/ number. We then apply the formalism to superachromatic six-crystal retarders in converging beams under beam thermal loading in outdoor environmental conditions for two of the world's largest observatories: the 10-m Keck telescope and the Daniel K. Inouye Solar Telescope (DKIST). DKIST will produce a 300-W optical beam, which has imposed stringent requirements on the large diameter six-crystal retarders, dichroic beamsplitters, and internal optics. DKIST retarders are used in a converging beam with F/ ratios between 8 and 62. The fringe spectral periods, amplitudes, and thermal models of retarder behavior assisted DKIST optical designs and calibration plans with future application to many astronomical spectropolarimeters. The Low Resolution Imaging Spectrograph with polarimetry instrument at Keck also uses six-crystal retarders in a converging F / 13 beam in a Cassegrain focus exposed to summit environmental conditions providing observational verification of our predictions.

  16. Preoperative Monocyte-to-Lymphocyte Ratio in Peripheral Blood Predicts Stages, Metastasis, and Histological Grades in Patients with Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Jiangdong Xiang

    2017-02-01

    Full Text Available PURPOSE: The monocyte-to-lymphocyte ratio (MLR has been shown to be associated with the prognosis of various solid tumors. This study sought to evaluate the important value of the MLR in ovarian cancer patients. METHODS: A total of 133 ovarian cancer patients and 43 normal controls were retrospectively reviewed. The patients' demographics were analyzed along with clinical and pathologic data. The counts of peripheral neutrophils, lymphocytes, monocytes, and platelets were collected and used to calculate the MLR, neutrophil-to-lymphocyte ratio (NLR. and platelet-to-lymphocyte ratio (PLR. The optimal cutoff value of the MLR was determined by using receiver operating characteristic curve analysis. We compared the MLR, NLR, and PLR between ovarian cancer and normal control patients and among patients with different stages and different grades, as well as between patients with lymph node metastasis and non–lymph node metastasis. We then investigated the value of the MLR in predicting the stage, grade, and lymph node positivity by using logistic regression. The impact of the MLR on overall survival (OS was calculated by Kaplan-Meier method and compared by log-rank test. RESULTS: Statistically significant differences in the MLR were observed between ovarian cancer patients and normal controls. However, no difference was found for the NLR and PLR. Highly significant differences in the MLR were found among patients with different stages (stage I-II and stage III-IV, grades (G1 and >G1, and lymph node metastasis status. The MLR was a significant and independent risk factor for lymph node metastasis, as determined by logistic regression. The optimal cutoff value of the MLR was 0.23. We also classified the data according to tumor markers (CA125, CA199, HE4, AFP, and CEA and conventional coagulation parameters (International Normalized Ratio [INR] and fibrinogen. Highly significant differences in CA125, CA199, HE4, INR, fibrinogen levels, and lactate

  17. Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI

    Science.gov (United States)

    Liu, Rong

    2017-01-01

    Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with a power projective base method. Then we were applied a decision-making model, the sequential probability ratio testing (SPRT), for single-trial classification of motor imagery movement events. The unique strength of this proposed classification method lies in its accumulative process, which increases the discriminative power as more and more evidence is observed over time. The properties of the method were illustrated on thirteen subjects' recordings from three datasets. Results showed that our proposed power projective method outperformed two benchmark methods for every subject. Moreover, with sequential classifier, the accuracies across subjects were significantly higher than that with nonsequential ones. The average maximum accuracy of the SPRT method was 84.1%, as compared with 82.3% accuracy for the sequential Bayesian (SB) method. The proposed SPRT method provides an explicit relationship between stopping time, thresholds, and error, which is important for balancing the time-accuracy trade-off. These results suggest SPRT would be useful in speeding up decision-making while trading off errors in BCI. PMID:29348781

  18. Improving Clinical Prediction of Bipolar Spectrum Disorders in Youth

    Directory of Open Access Journals (Sweden)

    Thomas W. Frazier

    2014-03-01

    Full Text Available This report evaluates whether classification tree algorithms (CTA may improve the identification of individuals at risk for bipolar spectrum disorders (BPSD. Analyses used the Longitudinal Assessment of Manic Symptoms (LAMS cohort (629 youth, 148 with BPSD and 481 without BPSD. Parent ratings of mania symptoms, stressful life events, parenting stress, and parental history of mania were included as risk factors. Comparable overall accuracy was observed for CTA (75.4% relative to logistic regression (77.6%. However, CTA showed increased sensitivity (0.28 vs. 0.18 at the expense of slightly decreased specificity and positive predictive power. The advantage of CTA algorithms for clinical decision making is demonstrated by the combinations of predictors most useful for altering the probability of BPSD. The 24% sample probability of BPSD was substantially decreased in youth with low screening and baseline parent ratings of mania, negative parental history of mania, and low levels of stressful life events (2%. High screening plus high baseline parent-rated mania nearly doubled the BPSD probability (46%. Future work will benefit from examining additional, powerful predictors, such as alternative data sources (e.g., clinician ratings, neurocognitive test data; these may increase the clinical utility of CTA models further.

  19. Improving default risk prediction using Bayesian model uncertainty techniques.

    Science.gov (United States)

    Kazemi, Reza; Mosleh, Ali

    2012-11-01

    Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis. © 2012 Society for Risk Analysis.

  20. 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

  1. 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

  2. Variable Pitch Approach for Performance Improving of Straight-Bladed VAWT at Rated Tip Speed Ratio

    Directory of Open Access Journals (Sweden)

    Zhenzhou Zhao

    2018-06-01

    Full Text Available This paper presents a new variable pitch (VP approach to increase the peak power coefficient of the straight-bladed vertical-axis wind turbine (VAWT, by widening the azimuthal angle band of the blade with the highest aerodynamic torque, instead of increasing the highest torque. The new VP-approach provides a curve of pitch angle designed for the blade operating at the rated tip speed ratio (TSR corresponding to the peak power coefficient of the fixed pitch (FP-VAWT. The effects of the new approach are exploited by using the double multiple stream tubes (DMST model and Prandtl’s mathematics to evaluate the blade tip loss. The research describes the effects from six aspects, including the lift, drag, angle of attack (AoA, resultant velocity, torque, and power output, through a comparison between VP-VAWTs and FP-VAWTs working at four TSRs: 4, 4.5, 5, and 5.5. Compared with the FP-blade, the VP-blade has a wider azimuthal zone with the maximum AoA, lift, drag, and torque in the upwind half-cycle, and yields the two new larger maximum values in the downwind half-cycle. The power distribution in the swept area of the turbine changes from an arched shape of the FP-VAWT into the rectangular shape of the VP-VAWT. The new VP-approach markedly widens the highest-performance zone of the blade in a revolution, and ultimately achieves an 18.9% growth of the peak power coefficient of the VAWT at the optimum TSR. Besides achieving this growth, the new pitching method will enhance the performance at TSRs that are higher than current optimal values, and an increase of torque is also generated.

  3. Predicting local recurrence following breast-conserving treatment: parenchymal signal enhancement ratio (SER) around the tumor on preoperative MRI

    International Nuclear Information System (INIS)

    Kim, Mi Young; Cho, Nariya; Koo, Hye Ryoung; Yun, Bo La; Bae, Min Sun; Moon, Woo Kyung; Chie, Eui Kyu

    2013-01-01

    Background: The level of background parenchymal enhancement around tumor is known to be associated with breast cancer risk. However, there is no study investigating predictive power of parenchymal signal enhancement ratio (SER) around tumor for ipsilateral breast tumor recurrence (IBTR). Purpose: To investigate whether the breast parenchymal SER around the tumor on preoperative dynamic contrast-enhanced magnetic resonance imaging (MRI) is associated with subsequent IBTR in breast cancer patients who had undergone breast-conserving treatment. Material and Methods: Nineteen consecutive women (mean age, 44 years; range, 34-63 years) with breast cancer who developed IBTR following breast-conserving treatment and 114 control women matched for age, as well as T and N stages were included. We compared the clinicopathologic features of the two groups including nuclear grade, histologic grade, hormonal receptor status, human epidermal growth factor receptor-2 (HER-2) status, lymphovascular invasion, negative margin width, use of adjuvant therapy, and parenchymal SER around the tumor on preoperative DCE-MRI. The SER was measured on a slice showing the largest dimension of the tumor. Multivariate conditional logistic regression analysis was used to identify independent factors associated with IBTR. Results: In univariate analysis, ER negativity (odds ratio [OR] = 4.7; P = 0.040), PR negativity (OR = 4.0; P = 0.013), HER-2 positivity (OR = 3.6; P = 0.026), and a parenchymal SER greater than 0.53 (OR = 23.3; P = 0.011) were associated with IBTR. In multivariate analysis, ER negativity (OR = 3.8; P = 0.015) and a parenchymal SER greater than 0.53 (OR = 13.2; P = 0.040) on preoperative MRI were independent factors associated with IBTR. Conclusion: In addition to ER negativity, a higher parenchymal SER on preoperative MRI was an independent factor associated with subsequent IBTR in patients with breast cancer who had undergone breast-conserving treatment

  4. Lipid ratios and appropriate cut off values for prediction of diabetes: a cohort of Iranian men and women

    Directory of Open Access Journals (Sweden)

    Hadaegh Farzad

    2010-08-01

    Full Text Available Abstract Background Dyslipidemia is a risk factor for incident type 2 diabetes; however, no study has specifically assessed the lipid ratios (i.e. total cholesterol (TC/high density lipoprotein cholesterol (HDL-C and triglyceride (TG/HDL-C as predictors of diabetes. We aimed to compare the independent association between the different lipid measures with incident diabetes over a median follow up of 6.4 years in Iranian men and women. Method The study population consisted of 5201 non diabetic (men = 2173, women = 3028 subjects, aged ≥20 years. The risk factor adjusted odds ratios (ORs for diabetes were calculated for every 1 standard deviation (SD change in TC, log-transformed TG, HDL-C, non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using multivariate logistic regression analysis. Receiver operator characteristic (ROC curve analysis was used to define the points of the maximum sum of sensitivity and specificity (MAXss of each lipid measure as a predictor of diabetes. Result We found 366 (146 men and 220 women new diabetes cases during follow-up. The risk-factor-adjusted ORs for a 1 SD increase in TG, TC/HDL-C and TG/HDL-C were 1.23, 1.27 and 1.25 in men; the corresponding risks in females were 1.36, 1.14, 1.39 respectively (all p Conclusion TC/HDL-C and TG/HDL-C showed similar performance for diabetes prediction in men population however; among women TG/HDL-C highlighted higher risk than did TC/HDL-C, although there was no difference in discriminatory power. Importantly, HDL-C had a protective effect for incident diabetes only among women.

  5. Neutrophil-to-lymphocyte ratio predicting suicide risk in euthymic patients with bipolar disorder: Moderatory effect of family history.

    Science.gov (United States)

    Ivković, Maja; Pantović-Stefanović, Maja; Dunjić-Kostić, Bojana; Jurišić, Vladimir; Lačković, Maja; Totić-Poznanović, Sanja; Jovanović, Aleksandar A; Damjanović, Aleksandar

    2016-04-01

    Neutrophil-to-lymphocyte ratio (NLR) has been independently related to bipolar disorder (BD) and factors associated with suicidal risk. The aim of our study was to explore the relationship between NLR and suicide risk in euthymic BD patients. We also sought to propose a model of interaction between NLR and stress-diathesis factors, leading to suicidal risk in BD. The study group consisted of 83 patients diagnosed with BD (36 suicide attempters; 47 suicide non-attempters), compared to the healthy control group (n=73) and matched according to age, gender, and body mass index (BMI). NLR was measured according to the complete blood count. Mood symptoms have been assessed by Young Mania Rating Scale and Montgomery-Asberg Depression Rating Scale. Early trauma and acute stress were evaluated by Early Trauma Inventory Self Report-Short Form and List of Threatening Experiences Questionnaire, respectively. Suicide risk has been assessed by Suicide Behaviors Questionnaire-Revised (SBQ-R). Significant correlation was found between NLR and SBQ-R score. The main effects of suicide attempts on NLR, after covarying for confounders, were observed, indicating increased NLR in BD suicide attempters compared to healthy controls. We found significant moderatory effects of family history on NLR relationship to suicidal risk, with NLR being significant positive predictor of suicidal risk only in the patients with positive family history of suicide attempts. The results suggest an enhancing effect of positive family history of suicide attempts on predictive effect of NLR on suicide risk. Our data support the idea that immune markers can predict suicide attempt risk in BD, but only in the subpopulation of BD patients with family history of suicide attempts. This could lead to prevention in suicide behavior in the patient population at particular risk of suicide. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. 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.

  7. 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.

  8. A predictive maintenance approach for improved nuclear plant availability

    International Nuclear Information System (INIS)

    Verma, R.M.P.; Pandya, M.B.; Kini, M.P.

    1979-01-01

    Predictive maintenance programme as against preventive maintenance programme aims at diagnosing, inspecting, monitoring, and objective condition-checking of equipment. It helps in forecasting failures, and scheduling the optimal frequencies for overhauls, replacements, lubrication etc. It also helps in establishing work load, manpower, resource planning and inventory control. Various stages of predictive maintenance programme for a nuclear power plant are outlined. A partial list of instruments for predictive maintenance is given. (M.G.B.)

  9. 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.

  10. Neutrophil-to-lymphocyte ratio as a novel-potential marker for predicting prognosis of Bell palsy.

    Science.gov (United States)

    Bucak, Abdulkadir; Ulu, Sahin; Oruc, Serdar; Yucedag, Fatih; Tekin, Mustafa Said; Karakaya, Fatıma; Aycicek, Abdullah

    2014-07-01

    Bell palsy can be defined as an idiopathic, acute, facial nerve palsy. Although the pathogenesis of Bell palsy is not fully understood, inflammation seems to play important role. Neutrophil-to-lymphocyte (NLR) ratio was defined as a novel potential marker to determine inflammation and it is routinely measured in peripheral blood. Our goal was to investigate the relationship between Bell palsy and inflammation by using NLR. Retrospective study. The 54 patients who were followed up for Bell palsy for a period of 1 to 3 years, along with 45 age- and sex-matched controls, were included in the study. An automated blood cell counter was used for NLR measurements. All patients were treated with prednisone, 1 mg/kg per day with a progressive dose reduction. Patients were classified according to the House-Brackmann grading system at posttreatment period. Those with House-Brackmann grade I and grade II were regarded as satisfactory recovery; and those with House-Brackmann grade III to grade VI were regarded as nonsatisfactory recovery. The mean NLR and neutrophil values in patients with Bell palsy were significantly higher than in the control group (P=0.001 and PBell palsy and its prognosis. Our result suggest that while evaluating Bell palsy patients, NLR might be taken into account as a novel potential marker to predict the patients' prognosis. 3b. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

  11. A lymph node ratio of 10% is predictive of survival in stage III colon cancer: a French regional study.

    Science.gov (United States)

    Sabbagh, Charles; Mauvais, François; Cosse, Cyril; Rebibo, Lionel; Joly, Jean-Paul; Dromer, Didier; Aubert, Christine; Carton, Sophie; Dron, Bernard; Dadamessi, Innocenti; Maes, Bernard; Perrier, Guillaume; Manaouil, David; Fontaine, Jean-François; Gozy, Michel; Panis, Xavier; Foncelle, Pierre Henri; de Fresnoy, Hugues; Leroux, Fabien; Vaneslander, Pierre; Ghighi, Caroline; Regimbeau, Jean-Marc

    2014-01-01

    Lymph node ratio (LNR) (positive lymph nodes/sampled lymph nodes) is predictive of survival in colon cancer. The aim of the present study was to validate the LNR as a prognostic factor and to determine the optimum LNR cutoff for distinguishing between "good prognosis" and "poor prognosis" colon cancer patients. From January 2003 to December 2007, patients with TNM stage III colon cancer operated on with at least of 3 years of follow-up and not lost to follow-up were included in this retrospective study. The two primary endpoints were 3-year overall survival (OS) and disease-free survival (DFS) as a function of the LNR groups and the cutoff. One hundred seventy-eight patients were included. There was no correlation between the LNR group and 3-year OS (P=0.06) and a significant correlation between the LNR group and 3-year DFS (P=0.03). The optimal LNR cutoff of 10% was significantly correlated with 3-year OS (P=0.02) and DFS (P=0.02). The LNR was not an accurate prognostic factor when fewer than 12 lymph nodes were sampled. Clarification and simplification of the LNR classification are prerequisites for use of this system in randomized control trials. An LNR of 10% appears to be the optimal cutoff.

  12. Performance of in-hospital mortality prediction models for acute hospitalization: Hospital Standardized Mortality Ratio in Japan

    Directory of Open Access Journals (Sweden)

    Motomura Noboru

    2008-11-01

    Full Text Available Abstract Objective In-hospital mortality is an important performance measure for quality improvement, although it requires proper risk adjustment. We set out to develop in-hospital mortality prediction models for acute hospitalization using a nation-wide electronic administrative record system in Japan. Methods Administrative records of 224,207 patients (patients discharged from 82 hospitals in Japan between July 1, 2002 and October 31, 2002 were randomly split into preliminary (179,156 records and test (45,051 records groups. Study variables included Major Diagnostic Category, age, gender, ambulance use, admission status, length of hospital stay, comorbidity, and in-hospital mortality. ICD-10 codes were converted to calculate comorbidity scores based on Quan's methodology. Multivariate logistic regression analysis was then performed using in-hospital mortality as a dependent variable. C-indexes were calculated across risk groups in order to evaluate model performances. Results In-hospital mortality rates were 2.68% and 2.76% for the preliminary and test datasets, respectively. C-index values were 0.869 for the model that excluded length of stay and 0.841 for the model that included length of stay. Conclusion Risk models developed in this study included a set of variables easily accessible from administrative data, and still successfully exhibited a high degree of prediction accuracy. These models can be used to estimate in-hospital mortality rates of various diagnoses and procedures.

  13. 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.

  14. Using road topology to improve cyclist path prediction

    NARCIS (Netherlands)

    Pool, E.A.I.; Kooij, J.F.P.; Gavrila, D.; Ioannou, Petros; Zhang, Wei-Bin; Lu, Meng

    2017-01-01

    We learn motion models for cyclist path prediction on real-world tracks obtained from a moving vehicle, and propose to exploit the local road topology to obtain better predictive distributions. The tracks are extracted from the Tsinghua-Daimler Cyclist Benchmark for cyclist detection, and corrected

  15. 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.

  16. 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.

  17. 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.

  18. When selection ratios are high: predicting the expatriation willingness of prospective domestic entry-level job applicants

    NARCIS (Netherlands)

    Mol, S.T.; Born, M.P.; Willemsen, M.E.; van der Molen, H.T.; Derous, E.

    2009-01-01

    High expatriate selection ratios thwart the ability of multinational organizations to select expatriates. Reducing the selection ratio may be accomplished by selecting those applicants for entry level domestic positions who have expatriate aspirations. Regression analyses conducted on data from a

  19. Dynamic Filtering Improves Attentional State Prediction with fNIRS

    Science.gov (United States)

    Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

    2016-01-01

    Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

  20. 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

  1. 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.

  2. 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

  3. 137Cs Inter-Plant Concentration Ratios Provide a Predictive Tool for Coral Atolls with Distinct Benefits Over Transfer Factors

    Energy Technology Data Exchange (ETDEWEB)

    Robison, W L; Hamilton, T F; Bogen, K; Corado, C L; Kehl, S R

    2007-07-17

    Inter-plant concentration ratios (IPCR), [Bq g{sup -1} {sup 137}Cs in coral atoll tree food-crops/Bq g{sup -1} {sup 137}Cs in leaves of native plant species whose roots share a common soil volume], can replace transfer factors (TF) to predict {sup 137}Cs concentration in tree food-crops in a contaminated area with an aged source term. The IPCR strategy has significant benefits relative to TF strategy for such purposes in the atoll ecosystem. IPCR strategy applied to specific assessments takes advantage of the fact tree roots naturally integrate 137Cs over large volumes of soil. Root absorption of {sup 137}Cs replaces large-scale, expensive soil sampling schemes to reduce variability in {sup 137}Cs concentration due to inhomogeneous radionuclide distribution. IPCR [drinking-coconut meat (DCM)/Scaevola (SCA) and Tournefortia (TOU) leaves (native trees growing on all atoll islands)] are log normally distributed (LND) with geometric standard deviation (GSD) = 1.85. TF for DCM from Enewetak, Eneu, Rongelap and Bikini Atolls are LND with GSD's of 3.5, 3.0, 2.7, and 2.1, respectively. TF GSD for Rongelap copra coconut meat is 2.5. IPCR of Pandanus fruit to SCA and TOU leaves are LND with GSD = 1.7 while TF GSD is 2.1. Because IPCR variability is much lower than TF variability, relative sampling error of an IPCR field sample mean is up 6- to 10-fold lower than that of a TF sample mean if sample sizes are small (10 to 20). Other IPCR advantages are that plant leaf samples are collected and processed in far less time with much less effort and cost than soil samples.

  4. 137Cs inter-plant concentration ratios provide a predictive tool for coral atolls with distinct benefits over transfer factors

    International Nuclear Information System (INIS)

    Robison, William L.; Hamilton, Terry F.; Bogen, Kenneth T.; Conrado, Cynthia L.; Kehl, Steven R.

    2008-01-01

    Inter-plant concentration ratios (IPCR) [Bq g -1137 Cs in coral atoll tree food crops/Bq g -1137 Cs in leaves of native plant species whose roots share a common soil volume] can replace transfer factors (TF) to predict 137 Cs concentration in tree food crops in a contaminated area with an aged source term. The IPCR strategy has significant benefits relative to TF strategy for such purposes in the atoll ecosystem. IPCR strategy applied to specific assessments takes advantage of the fact that tree roots naturally integrate 137 Cs over large volumes of soil. Root absorption of 137 Cs replaces large-scale, expensive soil sampling schemes to reduce variability in 137 Cs concentration due to inhomogeneous radionuclide distribution. IPCR [drinking-coconut meat (DCM)/Scaevola (SCA) and Tournefortia (TOU) leaves (native trees growing on all atoll islands)] are log-normally distributed (LND) with geometric standard deviation (GSD) = 1.85. TF for DCM from Enewetak, Eneu, Rongelap and Bikini Atolls are LND with GSDs of 3.5, 3.0, 2.7, and 2.1, respectively. TF GSD for Rongelap copra coconut meat is 2.5. IPCR of Pandanus fruit to SCA and TOU leaves are LND with GSD = 1.7 while TF GSD is 2.1. Because IPCR variability is much lower than TF variability, relative sampling error of an IPCR field sample mean is up 6- to 10-fold lower than that of a TF sample mean if sample sizes are small (10-20). Other IPCR advantages are that plant leaf samples are collected and processed in far less time with much less effort and cost than soil samples

  5. High urinary albumin/creatinine ratio at admission predicts poor functional outcome in patients with acute ischaemic stroke.

    Science.gov (United States)

    Watanabe, Yoko; Suda, Satoshi; Kanamaru, Takuya; Katsumata, Toshiya; Okubo, Seiji; Kaneko, Tomohiro; Mii, Akiko; Sakai, Yukinao; Katayama, Yasuo; Kimura, Kazumi; Tsuruoka, Shuichi

    2017-03-01

    Albuminuria and a low estimated glomerular filtration rate (eGFR) are widely recognized indices of kidney dysfunction and have been linked to cardiovascular events, including stroke. We evaluated albuminuria, measured using the urinary albumin/creatinine ratio (UACR), and the eGFR in the acute phase of ischaemic stroke, and investigated the clinical characteristics of ischaemic stroke patients with and those without kidney dysfunction. The study included 422 consecutive patients admitted between June 2010 and May 2012. General blood and urine examinations were performed at admission. Kidney dysfunction was defined as a low eGFR (high albuminuria (≥30 mg/g creatinine), or both. Neurological severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) at admission and the modified Rankin scale (mRS) at discharge. A poor outcome was defined as a mRS score of 3-5 or death. The impacts of the eGFR and UACR on outcomes at discharge were evaluated using multiple logistic regression analysis. Kidney dysfunction was diagnosed in 278 of the 422 patients (65.9%). The eGFR was significantly lower and UACR was significantly higher in patients with a poor outcome than in those with a good outcome. In multivariate analyses performed after adjusting for confounding factors, UACR >31.2 mg/g creatinine (OR, 2.58; 95% CI, 1.52-4.43; P = 0.0005) was independently associated with a poor outcome, while a low eGFR was not associated. A high UACR at admission may predict a poor outcome at discharge in patients with acute ischaemic stroke. © 2016 Asian Pacific Society of Nephrology.

  6. 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

  7. Interpreting Disruption Prediction Models to Improve Plasma Control

    Science.gov (United States)

    Parsons, Matthew

    2017-10-01

    In order for the tokamak to be a feasible design for a fusion reactor, it is necessary to minimize damage to the machine caused by plasma disruptions. Accurately predicting disruptions is a critical capability for triggering any mitigative actions, and a modest amount of attention has been given to efforts that employ machine learning techniques to make these predictions. By monitoring diagnostic signals during a discharge, such predictive models look for signs that the plasma is about to disrupt. Typically these predictive models are interpreted simply to give a `yes' or `no' response as to whether a disruption is approaching. However, it is possible to extract further information from these models to indicate which input signals are more strongly correlated with the plasma approaching a disruption. If highly accurate predictive models can be developed, this information could be used in plasma control schemes to make better decisions about disruption avoidance. This work was supported by a Grant from the 2016-2017 Fulbright U.S. Student Program, administered by the Franco-American Fulbright Commission in France.

  8. Improving acute kidney injury diagnostics using predictive analytics.

    Science.gov (United States)

    Basu, Rajit K; Gist, Katja; Wheeler, Derek S

    2015-12-01

    Acute kidney injury (AKI) is a multifactorial syndrome affecting an alarming proportion of hospitalized patients. Although early recognition may expedite management, the ability to identify patients at-risk and those suffering real-time injury is inconsistent. The review will summarize the recent reports describing advancements in the area of AKI epidemiology, specifically focusing on risk scoring and predictive analytics. In the critical care population, the primary underlying factors limiting prediction models include an inability to properly account for patient heterogeneity and underperforming metrics used to assess kidney function. Severity of illness scores demonstrate limited AKI predictive performance. Recent evidence suggests traditional methods for detecting AKI may be leveraged and ultimately replaced by newer, more sophisticated analytical tools capable of prediction and identification: risk stratification, novel AKI biomarkers, and clinical information systems. Additionally, the utility of novel biomarkers may be optimized through targeting using patient context, and may provide more granular information about the injury phenotype. Finally, manipulation of the electronic health record allows for real-time recognition of injury. Integrating a high-functioning clinical information system with risk stratification methodology and novel biomarker yields a predictive analytic model for AKI diagnostics.

  9. 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.

  10. Improved fuzzy PID controller design using predictive functional control structure.

    Science.gov (United States)

    Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

    2017-11-01

    In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Verification and improvement of a predictive model for radionuclide migration

    International Nuclear Information System (INIS)

    Miller, C.W.; Benson, L.V.; Carnahan, C.L.

    1982-01-01

    Prediction of the rates of migration of contaminant chemical species in groundwater flowing through toxic waste repositories is essential to the assessment of a repository's capability of meeting standards for release rates. A large number of chemical transport models, of varying degrees of complexity, have been devised for the purpose of providing this predictive capability. In general, the transport of dissolved chemical species through a water-saturated porous medium is influenced by convection, diffusion/dispersion, sorption, formation of complexes in the aqueous phase, and chemical precipitation. The reliability of predictions made with the models which omit certain of these processes is difficult to assess. A numerical model, CHEMTRN, has been developed to determine which chemical processes govern radionuclide migration. CHEMTRN builds on a model called MCCTM developed previously by Lichtner and Benson

  12. 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.

  13. Improving Marital Prediction: A Model and a Pilot Study.

    Science.gov (United States)

    Dean, Dwight G.; Lucas, Wayne L.

    A model for the prediction of marital adjustment is proposed which presents selected social background factors (e.g., education) and interactive factors (e.g., Bienvenu's Communication scale, Hurvitz' Role Inventory, Dean's Emotional Maturity and Commitment scales, Rosenberg's Self-Esteem scale) in order to account for as much of the variance in…

  14. How Predictive Analytics and Choice Architecture Can Improve Student Success

    Science.gov (United States)

    Denley, Tristan

    2014-01-01

    This article explores the challenges that students face in navigating the curricular structure of post-secondary degree programs, and how predictive analytics and choice architecture can play a role. It examines Degree Compass, a course recommendation system that successfully pairs current students with the courses that best fit their talents and…

  15. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    user

    2010-10-04

    Oct 4, 2010 ... Available online at http://www.academicjournals.org/AJEST ... robust technique for predicting optimal image resolution for the mapping of savannah ecosystems was developed. .... whether to purchase multi-spectral imagery acquired by GeoEye-2 ..... Analysis of the spectral behaviour of the pasture class in.

  16. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    Past studies to predict optimal image resolution required for generating spatial information for savannah ecosystems have yielded different outcomes, hence providing a knowledge gap that was investigated in the present study. The postulation, for the present study, was that by graphically solving two simultaneous ...

  17. Combining disparate data sources for improved poverty prediction and mapping.

    Science.gov (United States)

    Pokhriyal, Neeti; Jacques, Damien Christophe

    2017-11-14

    More than 330 million people are still living in extreme poverty in Africa. Timely, accurate, and spatially fine-grained baseline data are essential to determining policy in favor of reducing poverty. The potential of "Big Data" to estimate socioeconomic factors in Africa has been proven. However, most current studies are limited to using a single data source. We propose a computational framework to accurately predict the Global Multidimensional Poverty Index (MPI) at a finest spatial granularity and coverage of 552 communes in Senegal using environmental data (related to food security, economic activity, and accessibility to facilities) and call data records (capturing individualistic, spatial, and temporal aspects of people). Our framework is based on Gaussian Process regression, a Bayesian learning technique, providing uncertainty associated with predictions. We perform model selection using elastic net regularization to prevent overfitting. Our results empirically prove the superior accuracy when using disparate data (Pearson correlation of 0.91). Our approach is used to accurately predict important dimensions of poverty: health, education, and standard of living (Pearson correlation of 0.84-0.86). All predictions are validated using deprivations calculated from census. Our approach can be used to generate poverty maps frequently, and its diagnostic nature is, likely, to assist policy makers in designing better interventions for poverty eradication. Copyright © 2017 the Author(s). Published by PNAS.

  18. Trajectory Analysis and Prediction for Improved Pedestrian Safety

    DEFF Research Database (Denmark)

    Møgelmose, Andreas; Trivedi, Mohan M.; Moeslund, Thomas B.

    2015-01-01

    This paper presents a monocular and purely vision based pedestrian trajectory tracking and prediction framework with integrated map-based hazard inference. In Advanced Driver Assistance systems research, a lot of effort has been put into pedestrian detection over the last decade, and several pede...

  19. 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...

  20. Selection procedures in sports: Improving predictions of athletes’ future performance

    NARCIS (Netherlands)

    den Hartigh, Jan Rudolf; Niessen, Anna; Frencken, Wouter; Meijer, Rob R.

    The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the

  1. Improved part-of-speech prediction in suffix analysis.

    Directory of Open Access Journals (Sweden)

    Mario Fruzangohar

    Full Text Available MOTIVATION: Predicting the part of speech (POS tag of an unknown word in a sentence is a significant challenge. This is particularly difficult in biomedicine, where POS tags serve as an input to training sophisticated literature summarization techniques, such as those based on Hidden Markov Models (HMM. Different approaches have been taken to deal with the POS tagger challenge, but with one exception--the TnT POS tagger--previous publications on POS tagging have omitted details of the suffix analysis used for handling unknown words. The suffix of an English word is a strong predictor of a POS tag for that word. As a pre-requisite for an accurate HMM POS tagger for biomedical publications, we present an efficient suffix prediction method for integration into a POS tagger. RESULTS: We have implemented a fully functional HMM POS tagger using experimentally optimised suffix based prediction. Our simple suffix analysis method, significantly outperformed the probability interpolation based TnT method. We have also shown how important suffix analysis can be for probability estimation of a known word (in the training corpus with an unseen POS tag; a common scenario with a small training corpus. We then integrated this simple method in our POS tagger and determined an optimised parameter set for both methods, which can help developers to optimise their current algorithm, based on our results. We also introduce the concept of counting methods in maximum likelihood estimation for the first time and show how counting methods can affect the prediction result. Finally, we describe how machine-learning techniques were applied to identify words, for which prediction of POS tags were always incorrect and propose a method to handle words of this type. AVAILABILITY AND IMPLEMENTATION: Java source code, binaries and setup instructions are freely available at http://genomes.sapac.edu.au/text_mining/pos_tagger.zip.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. 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...

  4. Improving protein function prediction methods with integrated literature data

    Directory of Open Access Journals (Sweden)

    Gabow Aaron P

    2008-04-01

    Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

  5. 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

  6. Preoperative C-Reactive Protein/Albumin Ratio Predicts Prognosis of Patients after Curative Resection for Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Xuechao Liu

    2015-08-01

    Full Text Available BACKGROUND: An elevated preoperative C-reactive protein/albumin (CRP/Alb ratio has been reported to be associated with a poor prognosis for hepatocellular carcinoma. The aim of the present study was to investigate the prognostic value of the preoperative CRP/Alb ratio and compare it with other systemic inflammatory response markers in patients with gastric cancer (GC. METHODS: A retrospective study was performed in 455 patients with GC undergoing curative resection. We investigated the correlations between the preoperative CRP/Alb ratio and overall survival (OS. Kaplan-Meier and Cox regression models were used to assess independent prognostic factors. The area under the curve was used to compare the prognostic value of different markers. RESULTS: On multivariate analysis, the CRP/Alb ratio were independently associated with OS in patients with GC (hazard ratio: 1.626; 95% confidence interval: 1.191-2.219; P = .002, along with age (P = .003, preoperative body weight loss (P = .001, tumor location (P = .008, metastatic lymph node ratio (P < .001, and seventh tumor-nodes-metastasis stage (American Joint Committee on Cancer (P = .007. However, several other systemic inflammation–based prognostic scores (neutrophil lymphocyte ratio, platelet lymphocyte ratio and systemic immune-inflammation index, Glasgow Prognostic Score, modified Glasgow prognostic score, and high-sensitivity modified Glasgow prognostic score were not. In addition, the CRP/Alb ratio had a higher area under the curve value (0.625 compared with several other systemic inflammation–based prognostic scores (P < .001. CONCLUSION: The preoperative CRP/Alb ratio, a system inflammation-based prognostic score, is a superior predictor of OS in patients undergoing curative resection for GC and may help to identify the high-risk patients for treatment decisions.

  7. Improved predictions of nuclear data: A continued challenge in astrophysics

    International Nuclear Information System (INIS)

    Goriely, S.

    2001-01-01

    Although important effort has been devoted in the last decades to measure reaction cross sections and decay half-lives of interest in astrophysics, most of the nuclear astrophysics applications still require the use of theoretical predictions to estimate experimentally unknown rates. The nuclear ingredients to the reaction or weak interaction models should preferentially be estimated from microscopic or semi-microscopic global predictions based on sound and reliable nuclear models which, in turn, can compete with more phenomenological highly-parametrized models in the reproduction of experimental data. The latest developments made in deriving the nuclear inputs of relevance in astrophysics applications are reviewed. It mainly concerns nuclear structure properties (atomic masses, deformations, radii, etc...), nuclear level densities, nucleon and α-optical potentials, γ-ray and Gamow-Teller strength functions

  8. Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech

    OpenAIRE

    劉, 麗清

    2015-01-01

    Linear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis due to its ability to model speech production process approximately. Hence LP analysis has been widely used for speech enhancement, low-bit-rate speech coding in cellular telephony, speech recognition, characteristic parameter extraction (vocal tract resonances frequencies, fundamental frequency called pitch) and so on. However, the performance of the co...

  9. Improving Transit Predictions of Known Exoplanets with TERMS

    Directory of Open Access Journals (Sweden)

    Mahadevan S.

    2011-02-01

    Full Text Available Transiting planet discoveries have largely been restricted to the short-period or low-periastron distance regimes due to the bias inherent in the geometric transit probability. Through the refinement of planetary orbital parameters, and hence reducing the size of transit windows, long-period planets become feasible targets for photometric follow-up. Here we describe the TERMS project that is monitoring these host stars at predicted transit times.

  10. Validation of cytoplasmic-to-nuclear ratio of survivin as an indicator of improved prognosis in breast cancer

    International Nuclear Information System (INIS)

    Rexhepaj, Elton; Jirstrom, Karin; O'Connor, Darran P; O'Brien, Sallyann L; Landberg, Goran; Duffy, Michael J; Brennan, Donal J; Gallagher, William M

    2010-01-01

    Conflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients. Survin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression. Following optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018). Using the same threshold as our previous study, we have validated survivin CNR as a marker of good prognosis in

  11. Validation of cytoplasmic-to-nuclear ratio of survivin as an indicator of improved prognosis in breast cancer

    LENUS (Irish Health Repository)

    Rexhepaj, Elton

    2010-11-23

    Abstract Background Conflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients. Methods Survin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression. Results Following optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018). Conclusion Using the same threshold as our previous study, we have

  12. 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

  13. Effect of the electric field during annealing of organic light emitting diodes for improving its on/off ratio.

    Science.gov (United States)

    Sharma, Rahul K; Katiyar, Monica; Rao, I V Kameshwar; Unni, K N Narayanan; Deepak

    2016-01-28

    If an organic light emitting diode is to be used as part of a matrix addressed array, it should exhibit low reverse leakage current. In this paper we present a method to improve the on/off ratio of such a diode by simultaneous application of heat and electric field post device fabrication. A green OLED with excellent current efficiency was seen to be suffering from a poor on/off ratio of 10(2). After examining several combinations of annealing along with the application of a reverse bias voltage, the on/off ratio of the same device could be increased by three orders of magnitude, specifically when the device was annealed at 80 °C under reverse bias (-15 V) followed by slow cooling also under the same bias. Simultaneously, the forward characteristics of the device were relatively unaffected. The reverse leakage in the OLED is mainly due to the injection of minority carriers in the hole transport layer (HTL) and the electron transport layer (ETL), in this case, of holes in tris-(8-hydroxyquinoline)aluminum(Alq3) and electrons in 4,4',4''-tris(N-3-methylphenyl-N-phenylamino)triphenylamine (m-MTDATA). Hence, to investigate these layers adjacent to the electrodes, we fabricated their single layer devices. The possibility of bulk traps present adjacent to electrodes providing states for injection was ruled out after estimating the trap density both before and after the reverse biased annealing. The temperature independent current in reverse bias ruled out the possibility of thermionic injection. The origin of the reverse bias current is attributed to the availability of interfacial hole levels in Alq3 at the cathode work function level in the as-fabricated device; the suppression of the same being attributed to the fact that these levels in Alq3 are partly removed after annealing under an electric field.

  14. 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

  15. 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.

  16. Improving 3D structure prediction from chemical shift data

    Energy Technology Data Exchange (ETDEWEB)

    Schot, Gijs van der [Utrecht University, Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry (Netherlands); Zhang, Zaiyong [Technische Universitaet Muenchen, Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie (Germany); Vernon, Robert [University of Washington, Department of Biochemistry (United States); Shen, Yang [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Vranken, Wim F. [VIB, Department of Structural Biology (Belgium); Baker, David [University of Washington, Department of Biochemistry (United States); Bonvin, Alexandre M. J. J., E-mail: a.m.j.j.bonvin@uu.nl [Utrecht University, Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry (Netherlands); Lange, Oliver F., E-mail: oliver.lange@tum.de [Technische Universitaet Muenchen, Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie (Germany)

    2013-09-15

    We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 A RMSD from the reference)

  17. 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.

  18. 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.

  19. Diabetic Retinopathy Screening Ratio Is Improved When Using a Digital, Nonmydriatic Fundus Camera Onsite in a Diabetes Outpatient Clinic

    Directory of Open Access Journals (Sweden)

    Pia Roser

    2016-01-01

    Full Text Available Objective. To evaluate the effect of onsite screening with a nonmydriatic, digital fundus camera for diabetic retinopathy (DR at a diabetes outpatient clinic. Research Design and Methods. This cross-sectional study included 502 patients, 112 with type 1 and 390 with type 2 diabetes. Patients attended screenings for microvascular complications, including diabetic nephropathy (DN, diabetic polyneuropathy (DP, and DR. Single-field retinal imaging with a digital, nonmydriatic fundus camera was used to assess DR. Prevalence and incidence of microvascular complications were analyzed and the ratio of newly diagnosed to preexisting complications for all entities was calculated in order to differentiate natural progress from missed DRs. Results. For both types of diabetes, prevalence of DR was 25.0% (n=126 and incidence 6.4% (n=32 (T1DM versus T2DM: prevalence: 35.7% versus 22.1%, incidence 5.4% versus 6.7%. 25.4% of all DRs were newly diagnosed. Furthermore, the ratio of newly diagnosed to preexisting DR was higher than those for DN (p=0.12 and DP (p=0.03 representing at least 13 patients with missed DR. Conclusions. The results indicate that implementing nonmydriatic, digital fundus imaging in a diabetes outpatient clinic can contribute to improved early diagnosis of diabetic retinopathy.

  20. Three dimensional conformal radiation therapy may improve the therapeutic ratio of radiation therapy after pneumonectomy for lung cancer

    Energy Technology Data Exchange (ETDEWEB)

    Trouette, R; Causse, N; Elkhadri, M; Caudry, M; Maire, J P; Houlard, J P; Racaldini, L; Demeaux, H

    1995-12-01

    Three dimensional conformal radiation therapy would allow to decrease the normal tissue dose while maintaining the same target dose as standard treatment. To evaluate the feasibility of normal tissue dose reduction for ten patients with pneumonectomy for lung cancer, we determined the dose distribution to the normal tissue with 3-dimensional conformal radiation therapy (3-DCRT) and conventional treatment planning (CTP). Dose-volume histograms for target and normal tissue (lung, heart) were used for comparison of the different treatment planning. The mean percentages of lung and heart volumes which received 40 Gy with 3-DCRT were respectively 63% and 37% of the mean percentage of lung and volumes which received the same dose with CTP. These preliminary results suggest that conformal therapy may improve the therapeutic ratio by reducing risk to normal tissue.

  1. Improving Prediction of Large-scale Regime Transitions

    Science.gov (United States)

    Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

    2017-12-01

    Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these

  2. 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.

  3. Statistical methods for improving verification of claims of origin for Italian wines based on stable isotope ratios

    International Nuclear Information System (INIS)

    Dordevic, N.; Wehrens, R.; Postma, G.J.; Buydens, L.M.C.; Camin, F.

    2012-01-01

    Highlights: ► The assessment of claims of origin is of enormous economic importance for DOC and DOCG wines. ► The official method is based on univariate statistical tests of H, C and O isotopic ratios. ► We consider 5220 Italian wine samples collected in the period 2000–2010. ► Multivariate statistical analysis leads to much better specificity and easier detection of false claims of origin. ► In the case of multi-modal data, mixture modelling provides additional improvements. - Abstract: Wine derives its economic value to a large extent from geographical origin, which has a significant impact on the quality of the wine. According to the food legislation, wines can be without geographical origin (table wine) and wines with origin. Wines with origin must have characteristics which are essential due to its region of production and must be produced, processed and prepared, exclusively within that region. The development of fast and reliable analytical methods for the assessment of claims of origin is very important. The current official method is based on the measurement of stable isotope ratios of water and alcohol in wine, which are influenced by climatic factors. The results in this paper are based on 5220 Italian wine samples collected in the period 2000–2010. We evaluate the univariate approach underlying the official method to assess claims of origin and propose several new methods to get better geographical discrimination between samples. It is shown that multivariate methods are superior to univariate approaches in that they show increased sensitivity and specificity. In cases where data are non-normally distributed, an approach based on mixture modelling provides additional improvements.

  4. Statistical methods for improving verification of claims of origin for Italian wines based on stable isotope ratios

    Energy Technology Data Exchange (ETDEWEB)

    Dordevic, N.; Wehrens, R. [IASMA Research and Innovation Centre, Fondazione Edmund Mach, via Mach 1, 38010 San Michele all' Adige (Italy); Postma, G.J.; Buydens, L.M.C. [Radboud University Nijmegen, Institute for Molecules and Materials, Analytical Chemistry, P.O. Box 9010, 6500 GL Nijmegen (Netherlands); Camin, F., E-mail: federica.camin@fmach.it [IASMA Research and Innovation Centre, Fondazione Edmund Mach, via Mach 1, 38010 San Michele all' Adige (Italy)

    2012-12-13

    Highlights: Black-Right-Pointing-Pointer The assessment of claims of origin is of enormous economic importance for DOC and DOCG wines. Black-Right-Pointing-Pointer The official method is based on univariate statistical tests of H, C and O isotopic ratios. Black-Right-Pointing-Pointer We consider 5220 Italian wine samples collected in the period 2000-2010. Black-Right-Pointing-Pointer Multivariate statistical analysis leads to much better specificity and easier detection of false claims of origin. Black-Right-Pointing-Pointer In the case of multi-modal data, mixture modelling provides additional improvements. - Abstract: Wine derives its economic value to a large extent from geographical origin, which has a significant impact on the quality of the wine. According to the food legislation, wines can be without geographical origin (table wine) and wines with origin. Wines with origin must have characteristics which are essential due to its region of production and must be produced, processed and prepared, exclusively within that region. The development of fast and reliable analytical methods for the assessment of claims of origin is very important. The current official method is based on the measurement of stable isotope ratios of water and alcohol in wine, which are influenced by climatic factors. The results in this paper are based on 5220 Italian wine samples collected in the period 2000-2010. We evaluate the univariate approach underlying the official method to assess claims of origin and propose several new methods to get better geographical discrimination between samples. It is shown that multivariate methods are superior to univariate approaches in that they show increased sensitivity and specificity. In cases where data are non-normally distributed, an approach based on mixture modelling provides additional improvements.

  5. 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

  6. Improving Student Success Using Predictive Models and Data Visualisations

    Science.gov (United States)

    Essa, Alfred; Ayad, Hanan

    2012-01-01

    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…

  7. Improving the TRIGA facility maintenance by predictive maintenance techniques

    International Nuclear Information System (INIS)

    Preda, M.; Sabau, C.; Barbalata, E.

    1997-01-01

    This work deals with the specific operation of equipment in radioactive environment or in conditions allowing radioactive contamination. The requirements of remote operation ensuring the operators' protection are presented. Also, the requirements of international standards issued by IAEA-Vienna are reviewed. The organizational withdraws of the maintenance activities, based on the standards and maintenance and repair directives still in force, are shown. It is emphasized the fact that this type of maintenance was adequate to a given level of technical development, characteristic for pre-computerized industry, but, at present, it is obsolete and uneconomic both in utilization and maintenance. Such a system constitutes already a burden hindering the efforts of maximizing the availability, maintenance, prolongation the service life of equipment and utilities, finally, of increasing the efficiency of complex installations. Moreover, the predictive maintenance techniques are strongly requested by the character of radioactive installations precluding the direct access in given zones (a potential risk of irradiation or radioactive contamination) of installations during operation. The results obtained by applying the predictive maintenance techniques in the operation of the double circuit irradiation loop, used in the TRIGA reactors, are presented

  8. 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...

  9. 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.

  10. Conversion of Blue Water into Green Water for Improving Utilization Ratio of Water Resources in Degraded Karst Areas

    Directory of Open Access Journals (Sweden)

    Ke Chen

    2016-12-01

    Full Text Available Vegetation deterioration and soil loss are the main causes of more precipitation leakages and surface water shortages in degraded karst areas. In order to improve the utilization of water resources in such regions, water storage engineering has been considered; however, site selection and cost associated with the special karstic geological structure have made this difficult. According to the principle of the Soil Plant Atmosphere Continuum, increasing both vegetation cover and soil thickness would change water cycle process, resulting in a transformation from leaked blue water (liquid form into green water (gas or saturated water form for terrestrial plant ecosystems, thereby improving the utilization of water resources. Using the Soil Vegetation Atmosphere Transfer model and the geographical distributed approach, this study simulated the conversion from leaked blue water (leakage into green water in the environs of Guiyang, a typical degraded karst area. The primary results were as follows: (1 Green water in the area accounted for <50% of precipitation, well below the world average of 65%; (2 Vegetation growth played an important role in converting leakage into green water; however, once it increased to 56%, its contribution to reducing leakage decreased sharply; (3 Increasing soil thickness by 20 cm converted the leakage considerably. The order of leakage reduction under different precipitation scenarios was dry year > normal year > rainy year. Thus, increased soil thickness was shown effective in improving the utilization ratio of water resources and in raising the amount of plant ecological water use; (4 The transformation of blue water into green water, which avoids constructions of hydraulic engineering, could provide an alternative solution for the improvement of the utilization of water resources in degraded karst area. Although there are inevitable uncertainties in simulation process, it has important significance for overcoming similar

  11. 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.

  12. 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.

  13. Improving, characterizing and predicting the lifetime of organic photovoltaics

    DEFF Research Database (Denmark)

    Gevorgyan, Suren A.; Heckler, Ilona Maria; Bundgaard, Eva

    2017-01-01

    This review summarizes the recent progress in the stability and lifetime of organic photovoltaics (OPVs). In particular, recently proposed solutions to failure mechanisms in different layers of the device stack are discussed comprising both structural and chemical modifications. Upscaling...... characterization reported recently. Lifetime testing and determination is another challenge in the field of organic solar cells and the final sections of this review discuss the testing protocols as well as the generic marker for device lifetime and the methodology for comparing all the lifetime landmarks in one...... common diagram. These tools were used to determine the baselines for OPV lifetime tested under different ageing conditions. Finally, the current status of lifetime for organic solar cells is presented and predictions are made for progress in the near future....

  14. Predicting occurrence of juvenile shark habitat to improve conservation planning.

    Science.gov (United States)

    Oh, Beverly Z L; Sequeira, Ana M M; Meekan, Mark G; Ruppert, Jonathan L W; Meeuwig, Jessica J

    2017-06-01

    Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark-monitoring data on large scales (100s-1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km 2 of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species-level models had higher accuracy (ĸ ≥ 0.69) and deviance explained (≥48%) than our order-level model (ĸ = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species-specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species-focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non-extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across

  15. 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.

  16. Relationship between the Peroxidation of Leukocytes Index Ratio and the Improvement of Postprandial Metabolic Stress by a Functional Food.

    Science.gov (United States)

    Peluso, Ilaria; Manafikhi, Husseen; Reggi, Raffaella; Longhitano, Yaroslava; Zanza, Christian; Palmery, Maura

    2016-01-01

    For the first time, we investigated the relationship between postprandial dysmetabolism and the Peroxidation of Leukocytes Index Ratio (PLIR), a test that measures the resistance of leukocytes to exogenous oxidative stress and their functional capacity of oxidative burst upon activation. Following a blind, placebo controlled, randomized, crossover design, ten healthy subjects ingested, in two different occasions, a high fat and high carbohydrates meal with Snello cookie (HFHCM-S) or with control cookies (HFHCM-C). Snello cookie, a functional food covered by dark chocolate and containing glucomannan, inulin, fructooligosaccharides, and Bacillus coagulans strain GanedenBC30, significantly improved postprandial metabolic stress (insulin, glucose, and triglycerides) and reduced the postprandial increase of uric acid. HFHCM-S improved PLIR of lymphocytes, but not of monocytes and granulocytes. Both meals increased granulocytes' count and reduced the lipoperoxidation induced by both exogenous free radicals and reactive oxygen species (ROS) produced by oxidative burst. Our results suggest that the healthy status of the subjects could be a limitation of this pilot study for PLIR evaluation on cells that produce ROS by oxidative burst. In conclusion, the relationship between PLIR and postprandial dysmetabolism requires further investigations.

  17. Relationship between the Peroxidation of Leukocytes Index Ratio and the Improvement of Postprandial Metabolic Stress by a Functional Food

    Directory of Open Access Journals (Sweden)

    Ilaria Peluso

    2016-01-01

    Full Text Available For the first time, we investigated the relationship between postprandial dysmetabolism and the Peroxidation of Leukocytes Index Ratio (PLIR, a test that measures the resistance of leukocytes to exogenous oxidative stress and their functional capacity of oxidative burst upon activation. Following a blind, placebo controlled, randomized, crossover design, ten healthy subjects ingested, in two different occasions, a high fat and high carbohydrates meal with Snello cookie (HFHCM-S or with control cookies (HFHCM-C. Snello cookie, a functional food covered by dark chocolate and containing glucomannan, inulin, fructooligosaccharides, and Bacillus coagulans strain GanedenBC30, significantly improved postprandial metabolic stress (insulin, glucose, and triglycerides and reduced the postprandial increase of uric acid. HFHCM-S improved PLIR of lymphocytes, but not of monocytes and granulocytes. Both meals increased granulocytes’ count and reduced the lipoperoxidation induced by both exogenous free radicals and reactive oxygen species (ROS produced by oxidative burst. Our results suggest that the healthy status of the subjects could be a limitation of this pilot study for PLIR evaluation on cells that produce ROS by oxidative burst. In conclusion, the relationship between PLIR and postprandial dysmetabolism requires further investigations.

  18. 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.

  19. Cognitive ability correlates positively with son birth and predicts cross-cultural variation of the offspring sex ratio

    Science.gov (United States)

    Dama, Madhukar Shivajirao

    2013-06-01

    Human populations show remarkable variation in the sex ratio at birth which is believed to be related to the parental condition. In the present study, the global variation of sex ratio at birth (SRB, proportion of male offspring born) was analyzed with respect to indirect measure of condition, the intelligence quotient (IQ). IQ correlates strongly with lifespan across nations, which makes it a good indicator of health of the large populations. Relation between three standard measures of average national IQ and SRB was studied using multiple linear regression models. Average national IQ was positively correlated with SRB ( r = 0.54 to 0.57, p difference in general condition of populations.

  20. Herb-drug interactions: challenges and opportunities for improved predictions.

    Science.gov (United States)

    Brantley, Scott J; Argikar, Aneesh A; Lin, Yvonne S; Nagar, Swati; Paine, Mary F

    2014-03-01

    Supported by a usage history that predates written records and the perception that "natural" ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb-drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb-drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb-drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb-drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens.

  1. Herb–Drug Interactions: Challenges and Opportunities for Improved Predictions

    Science.gov (United States)

    Brantley, Scott J.; Argikar, Aneesh A.; Lin, Yvonne S.; Nagar, Swati

    2014-01-01

    Supported by a usage history that predates written records and the perception that “natural” ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb–drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb–drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb–drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb–drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens. PMID:24335390

  2. Digit Ratio (2D:4D) Predicts Self-Reported Measures of General Competitiveness, but Not Behavior in Economic Experiments.

    Science.gov (United States)

    Bönte, Werner; Procher, Vivien D; Urbig, Diemo; Voracek, Martin

    2017-01-01

    The ratio of index finger length to ring finger length (2D:4D) is considered to be a putative biomarker of prenatal androgen exposure (PAE), with previous research suggesting that 2D:4D is associated with human behaviors, especially sex-typical behaviors. This study empirically examines the relationship between 2D:4D and individual competitiveness, a behavioral trait that is found to be sexually dimorphic. We employ two related, but distinct, measures of competitiveness, namely behavioral measures obtained from economic experiments and psychometric self-reported measures. Our analyses are based on two independent data sets obtained from surveys and economic experiments with 461 visitors of a shopping mall (Study I) and 617 university students (Study II). The correlation between behavior in the economic experiment and digit ratios of both hands is not statistically significant in either study. In contrast, we find a negative and statistically significant relationship between psychometric self-reported measures of competitiveness and right hand digit ratios (R2D:4D) in both studies. This relationship is especially strong for younger people. Hence, this study provides some robust empirical evidence for a negative association between R2D:4D and self-reported competitiveness. We discuss potential reasons why digit ratio may relate differently to behaviors in specific economics experiments and to self-reported general competitiveness.

  3. Digit Ratio (2D:4D Predicts Self-Reported Measures of General Competitiveness, but Not Behavior in Economic Experiments

    Directory of Open Access Journals (Sweden)

    Werner Bönte

    2017-12-01

    Full Text Available The ratio of index finger length to ring finger length (2D:4D is considered to be a putative biomarker of prenatal androgen exposure (PAE, with previous research suggesting that 2D:4D is associated with human behaviors, especially sex-typical behaviors. This study empirically examines the relationship between 2D:4D and individual competitiveness, a behavioral trait that is found to be sexually dimorphic. We employ two related, but distinct, measures of competitiveness, namely behavioral measures obtained from economic experiments and psychometric self-reported measures. Our analyses are based on two independent data sets obtained from surveys and economic experiments with 461 visitors of a shopping mall (Study I and 617 university students (Study II. The correlation between behavior in the economic experiment and digit ratios of both hands is not statistically significant in either study. In contrast, we find a negative and statistically significant relationship between psychometric self-reported measures of competitiveness and right hand digit ratios (R2D:4D in both studies. This relationship is especially strong for younger people. Hence, this study provides some robust empirical evidence for a negative association between R2D:4D and self-reported competitiveness. We discuss potential reasons why digit ratio may relate differently to behaviors in specific economics experiments and to self-reported general competitiveness.

  4. 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.

  5. 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.

  6. Improving the reliability of fishery predictions under climate change

    DEFF Research Database (Denmark)

    Brander, Keith

    2015-01-01

    The increasing number of publications assessing impacts of climate change on marine ecosystems and fisheries attests to rising scientific and public interest. A selection of recent papers, dealing more with biological than social and economic aspects, is reviewed here, with particular attention...... to the reliability of projections of climate impacts on future fishery yields. The 2014 Intergovernmental Panel on Climate Change (IPCC) report expresses high confidence in projections that mid- and high-latitude fish catch potential will increase by 2050 and medium confidence that low-latitude catch potential...... understanding of climate impacts, such as how to improve coupled models from physics to fish and how to strengthen confidence in analysis of time series...

  7. Verification and improvement of predictive algorithms for radionuclide migration

    International Nuclear Information System (INIS)

    Carnahan, C.L.; Miller, C.W.; Remer, J.S.

    1984-01-01

    This research addresses issues relevant to numerical simulation and prediction of migration of radionuclides in the environment of nuclear waste repositories. Specific issues investigated are the adequacy of current numerical codes in simulating geochemical interactions affecting radionuclide migration, the level of complexity required in chemical algorithms of transport models, and the validity of the constant-k/sub D/ concept in chemical transport modeling. An initial survey of the literature led to the conclusion that existing numerical codes did not encompass the full range of chemical and physical phenomena influential in radionuclide migration. Studies of chemical algorithms have been conducted within the framework of a one-dimensional numerical code that simulates the transport of chemically reacting solutes in a saturated porous medium. The code treats transport by dispersion/diffusion and advection, and equilibrium-controlled proceses of interphase mass transfer, complexation in the aqueous phase, pH variation, and precipitation/dissolution of secondary solids. Irreversible, time-dependent dissolution of solid phases during transport can be treated. Mass action, transport, and sorptive site constraint equations are expressed in differential/algebraic form and are solved simultaneously. Simulations using the code show that use of the constant-k/sub D/ concept can produce unreliable results in geochemical transport modeling. Applications to a field test and laboratory analogs of a nuclear waste repository indicate that a thermodynamically based simulator of chemical transport can successfully mimic real processes provided that operative chemical mechanisms and associated data have been correctly identified and measured, and have been incorporated in the simulator. 17 references, 10 figures

  8. Improving Radar QPE's in Complex Terrain for Improved Flash Flood Monitoring and Prediction

    Science.gov (United States)

    Cifelli, R.; Streubel, D. P.; Reynolds, D.

    2010-12-01

    Quantitative Precipitation Estimation (QPE) is extremely challenging in regions of complex terrain due to a combination of issues related to sampling. In particular, radar beams are often blocked or scan above the liquid precipitation zone while rain gauge density is often too low to properly characterize the spatial distribution of precipitation. Due to poor radar coverage, rain gauge networks are used by the National Weather Service (NWS) River Forecast Centers as the principal source for QPE across the western U.S. The California Nevada River Forecast Center (CNRFC) uses point rainfall measurements and historical rainfall runoff relationships to derive river stage forecasts. The point measurements are interpolated to a 4 km grid using Parameter-elevation Regressions on Independent Slopes Model (PRISM) data to develop a gridded 6-hour QPE product (hereafter referred to as RFC QPE). Local forecast offices can utilize the Multi-sensor Precipitation Estimator (MPE) software to improve local QPE’s and thus local flash flood monitoring and prediction. MPE uses radar and rain gauge data to develop a combined QPE product at 1-hour intervals. The rain gauge information is used to bias correct the radar precipitation estimates so that, in situations where the rain gauge density and radar coverage are adequate, MPE can take advantage of the spatial coverage of the radar and the “ground truth” of the rain gauges to provide an accurate QPE. The MPE 1-hour QPE analysis should provide better spatial and temporal resolution for short duration hydrologic events as compared to 6-hour analyses. These hourly QPEs are then used to correct radar derived rain rates used by the Flash Flood Monitoring and Prediction (FFMP) software in forecast offices for issuance of flash flood warnings. Although widely used by forecasters across the eastern U.S., MPE is not used extensively by the NWS in the west. Part of the reason for the lack of use of MPE across the west is that there has

  9. Prediction of radiation ratio and sound transmission of complex extruded panel using wavenumber domain Unite element and boundary element methods

    International Nuclear Information System (INIS)

    Kim, H; Ryue, J; Thompson, D J; Müller, A D

    2016-01-01

    Recently, complex shaped aluminium panels have been adopted in many structures to make them lighter and stronger. The vibro-acoustic behaviour of these complex panels has been of interest for many years but conventional finite element and boundary element methods are not efficient to predict their performance at higher frequencies. Where the cross-sectional properties of the panels are constant in one direction, wavenumber domain numerical analysis can be applied and this becomes more suitable for panels with complex cross-sectional geometries. In this paper, a coupled wavenumber domain finite element and boundary element method is applied to predict the sound radiation from and sound transmission through a double-layered aluminium extruded panel, having a typical shape used in railway carriages. The predicted results are compared with measured ones carried out on a finite length panel and good agreement is found. (paper)

  10. Using synchronization in multi-model ensembles to improve prediction

    Science.gov (United States)

    Hiemstra, P.; Selten, F.

    2012-04-01

    In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of

  11. Improving models to predict phenological responses to global change

    Energy Technology Data Exchange (ETDEWEB)

    Richardson, Andrew D. [Harvard College, Cambridge, MA (United States)

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

  12. Radionuclide angiocardiography. Improved diagnosis and quantitation of left-to-right shunts using area ratio techniques in children

    International Nuclear Information System (INIS)

    Alderson, P.O.; Jost, R.G.; Strauss, A.W.; Boonvisut, S.; Markham, J.

    1975-01-01

    A comparison of several reported methods for detection and quantitation of left-to-right shunts by radionuclides was performed in 50 children. Count ratio (C2/C1) techniques were compared with the exponential extrapolation and gamma function area ratio techniques. C2/C1 ratios accurately detected shunts and could reliably separate shunts from normals, but there was a high rate of false positives in children with valvular heart disease. The area ratio methods provided more accurate shunt quantitation and a better separation of patients with valvular heart disease than did the C2/C1 ratio. The gamma function method showed a higher correlation with oximetry than the exponential method, but the difference was not statistically significant. For accurate shunt quantitation and a reliable separation of patients with valvular heart disease from those with shunts, area ratio calculations are preferable to the C2/C1 ratio

  13. 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.

  14. Improvement of the 99mTc-ECD brain uptake ratio (BUR) method for measurement of cerebral blood flow

    International Nuclear Information System (INIS)

    Ito, Shigeki; Takaki, Akihiro; Inoue, Shinya

    2012-01-01

    The brain uptake ratio (BUR) method for the 99m Tc-ethylcysteinate dimer ( 99m Tc-ECD) single photon emission computed tomography (SPECT), a non-invasive measurement method of regional cerebral blood flow (rCBF), has been used in clinical practice in Japan, because it is simple to use. However, the accuracy of this method is limited, as it has problems in the determination of input function and the regression equation. The purpose of this study is to improve the BUR method by reconstructing the determination process of the input function and regression equation based on measurement of the rCBF by H 2 15 O positron emission tomography (PET). The input function was obtained by setting the region of interest on the ascending aorta instead of the aortic arch. The 3DSRT algorithm was used to obtain the anatomically standardized rCBF, and developed a semi-automatic analyzing software using C++ in order to stabilize the repeatability of the improved BUR (IBUR) method. The regression equation for the IBUR method was obtained by the H 2 15 O PET rCBFs in 15 patients with the arterial blood sampling method. All the measurements in this study were performed with the patient in the resting state. A good correlation was observed between the rCBF values measured by H 2 15 O PET and the regional BURs measured by the IBUR method (r=0.86, p 2 15 O PET. This finding indicates the potential clinical usefulness of this method. (author)

  15. 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.,...

  16. 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

  17. 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

  18. 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.

  19. Curcumin improves prostanoid ratio in diabetic mesenteric arteries associated with cyclooxygenase-2 and NF-κB suppression

    Directory of Open Access Journals (Sweden)

    Patumraj S

    2010-12-01

    of PKC-βII within the vascular wall. Also, COX-2 expression and activated NF-κB in the small mesenteric artery of diabetes mellitus rats were markedly increased when compared with the control. Interestingly, curcumin could inhibit the upregulation of all of these biomarkers.Conclusion: These findings show that curcumin can attenuate diabetes-induced vascular dysfunction in association with its potential for COX-2 and NF-κB suppression, PKC inhibition, and improving the ratio of prostanoid products PGI2/TXA2.Keywords: diabetes, endothelial dysfunction, COX-2, prostanoids

  20. 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...

  1. 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.

  2. 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

  3. 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

  4. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios: are they useful for predicting gestational diabetes mellitus during pregnancy?

    Directory of Open Access Journals (Sweden)

    Sargın MA

    2016-04-01

    Full Text Available Mehmet Akif Sargın, Murat Yassa, Bilge Dogan Taymur, Ayhan Celik, Emrah Ergun, Niyazi Tug Department of Obstetrics and Gynecology, Fatih Sultan Mehmet Research and Training Hospital, Istanbul, Turkey Objective: We aimed to investigate whether the neutrophil-to-lymphocyte ratio (NLR and platelet-to-lymphocyte ratio (PLR could be utilized to screen for gestational diabetes mellitus (GDM.Subjects and methods: NLR and PLR were assessed by retrospective analysis of 762 healthy and pregnant women with GDM. The patients were stratified into four groups, as follows: GDM (n=144, impaired glucose tolerance (n=76, only screen positive (n=238, and control (n=304.Results: The leukocyte, neutrophil, and lymphocyte counts were significantly higher in the study groups compared with the control group (P=0.001; P<0.01. There were no statistically significant differences between the groups with respect to the NLR and PLR (P>0.05.Conclusion: We do not recommend that blood NLR and PLR can be used to screen for GDM. However, increase in the leukocyte count is an important marker for GDM as it provides evidence of subclinical inflammation. Keywords: inflammation, lymphocytes, neutrophils, platelets, pregnancy

  5. Predictive role of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios for diagnosis of acute appendicitis during pregnancy

    Directory of Open Access Journals (Sweden)

    Fatih Mehmet Yazar

    2015-11-01

    Full Text Available Acute appendicitis (AA is not uncommon during pregnancy but can be difficult to diagnose. This study evaluated the neutrophil-to-lymphocyte ratio (NLR and platelet-to-lymphocyte ratio (PLR in addition to conventional diagnostic indicators of the disease to diagnose AA during pregnancy. Age, gestational age, white blood cell (WBC count, Alvarado scores, C-reactive protein (CRP, lymphocyte count, NLR and PLR were compared among 28 pregnant women who underwent surgery for AA, 35 pregnant women wrongly suspected as having AA, 29 healthy pregnant women, and 30 nonpregnant healthy women. Mean WBC counts and CRP levels were higher in women with proven AA than in those of control groups (all p < 0.05. Among all the groups, the median NLR and PLR were significantly different in women with proven AA (all p < 0.05. Receiver operating characteristic analysis was used to determine cut-off values for WBC count, CRP, lymphocyte count, NLR and PLR, and multiple logistic regression analysis showed that NLR and PLR used with routine methods could diagnose AA with 90.5% accuracy. Used in addition to routine diagnostic methods, NLR and PLR increased the accuracy of the diagnosis of AA in pregnant women.

  6. 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.

  7. 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.

  8. Improved understanding of physics processes in pedestal structure, leading to improved predictive capability for ITER

    International Nuclear Information System (INIS)

    Groebner, R.J.; Snyder, P.B.; Leonard, A.W.; Chang, C.S.; Maingi, R.; Boyle, D.P.; Diallo, A.; Hughes, J.W.; Davis, E.M.; Ernst, D.R.; Landreman, M.; Xu, X.Q.; Boedo, J.A.; Cziegler, I.; Diamond, P.H.; Eldon, D.P.; Callen, J.D.; Canik, J.M.; Elder, J.D.; Fulton, D.P.

    2013-01-01

    Joint experiment/theory/modelling research has led to increased confidence in predictions of the pedestal height in ITER. This work was performed as part of a US Department of Energy Joint Research Target in FY11 to identify physics processes that control the H-mode pedestal structure. The study included experiments on C-Mod, DIII-D and NSTX as well as interpretation of experimental data with theory-based modelling codes. This work provides increased confidence in the ability of models for peeling–ballooning stability, bootstrap current, pedestal width and pedestal height scaling to make correct predictions, with some areas needing further work also being identified. A model for pedestal pressure height has made good predictions in existing machines for a range in pressure of a factor of 20. This provides a solid basis for predicting the maximum pedestal pressure height in ITER, which is found to be an extrapolation of a factor of 3 beyond the existing data set. Models were studied for a number of processes that are proposed to play a role in the pedestal n e and T e profiles. These processes include neoclassical transport, paleoclassical transport, electron temperature gradient turbulence and neutral fuelling. All of these processes may be important, with the importance being dependent on the plasma regime. Studies with several electromagnetic gyrokinetic codes show that the gradients in and on top of the pedestal can drive a number of instabilities. (paper)

  9. Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification By Spectral Deconvolution Ratio Analysis

    Directory of Open Access Journals (Sweden)

    Fausto Carnevale Neto

    2016-09-01

    Full Text Available Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY with Automated Mass Spectral Deconvolution and Identification System software (AMDIS. Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

  10. Ankle Brachial Index Compared With Different Lipid Ratios to Predict Coronary Events in Patients with Coronary Artery Disease

    Directory of Open Access Journals (Sweden)

    Zinat Nadia Hatmi

    2014-02-01

    Multivariable adjusted relations revealed that HDL-C and #8804;34 Mg/dl significantly increased the risk of future UA, HDL-C and #8804;53 Mg/dl and sedentary life style increased the risk of MI. CONCLUSION: Multivariate adjusted relationships revealed that HDL-C and #8804;34 Mg/dl was a strong predictor of unstable angina pectoris after 15 months of follow up period. HDL-C and #8804;53 Mg/dl and physical inactivity were associated with increased risk of MI after 15 months. Of the lipid ratios the strongest predictors for developing future MI and unstable angina were TC/HDL-C and LDL-C/HDL-C. [TAF Prev Med Bull 2014; 13(1.000: 29-36

  11. Individual stress vulnerability is predicted by short-term memory and AMPA receptor subunit ratio in the hippocampus.

    Science.gov (United States)

    Schmidt, Mathias V; Trümbach, Dietrich; Weber, Peter; Wagner, Klaus; Scharf, Sebastian H; Liebl, Claudia; Datson, Nicole; Namendorf, Christian; Gerlach, Tamara; Kühne, Claudia; Uhr, Manfred; Deussing, Jan M; Wurst, Wolfgang; Binder, Elisabeth B; Holsboer, Florian; Müller, Marianne B

    2010-12-15

    Increased vulnerability to aversive experiences is one of the main risk factors for stress-related psychiatric disorders as major depression. However, the molecular bases of vulnerability, on the one hand, and stress resilience, on the other hand, are still not understood. Increasing clinical and preclinical evidence suggests a central involvement of the glutamatergic system in the pathogenesis of major depression. Using a mouse paradigm, modeling increased stress vulnerability and depression-like symptoms in a genetically diverse outbred strain, and we tested the hypothesis that differences in AMPA receptor function may be linked to individual variations in stress vulnerability. Vulnerable and resilient animals differed significantly in their dorsal hippocampal AMPA receptor expression and AMPA receptor binding. Treatment with an AMPA receptor potentiator during the stress exposure prevented the lasting effects of chronic social stress exposure on physiological, neuroendocrine, and behavioral parameters. In addition, spatial short-term memory, an AMPA receptor-dependent behavior, was found to be predictive of individual stress vulnerability and response to AMPA potentiator treatment. Finally, we provide evidence that genetic variations in the AMPA receptor subunit GluR1 are linked to the vulnerable phenotype. Therefore, we propose genetic variations in the AMPA receptor system to shape individual stress vulnerability. Those individual differences can be predicted by the assessment of short-term memory, thereby opening up the possibility for a specific treatment by enhancing AMPA receptor function.

  12. 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....

  13. 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.

  14. Stability Improvement of High-Pressure-Ratio Turbocharger Centrifugal Compressor by Asymmetric Flow Control-Part I: Non-Axisymmetrical Flow in Centrifugal Compressor.

    Science.gov (United States)

    Yang, Mingyang; Zheng, Xinqian; Zhang, Yangjun; Bamba, Takahiro; Tamaki, Hideaki; Huenteler, Joern; Li, Zhigang

    2013-03-01

    This is Part I of a two-part paper documenting the development of a novel asymmetric flow control method to improve the stability of a high-pressure-ratio turbocharger centrifugal compressor. Part I focuses on the nonaxisymmetrical flow in a centrifugal compressor induced by the nonaxisymmetrical geometry of the volute while Part II describes the development of an asymmetric flow control method to avoid the stall on the basis of the characteristic of nonaxisymmetrical flow. To understand the asymmetries, experimental measurements and corresponding numerical simulation were carried out. The static pressure was measured by probes at different circumferential and stream-wise positions to gain insights about the asymmetries. The experimental results show that there is an evident nonaxisymmetrical flow pattern throughout the compressor due to the asymmetric geometry of the overhung volute. The static pressure field in the diffuser is distorted at approximately 90 deg in the rotational direction of the volute tongue throughout the diffuser. The magnitude of this distortion slightly varies with the rotational speed. The magnitude of the static pressure distortion in the impeller is a function of the rotational speed. There is a significant phase shift between the static pressure distributions at the leading edge of the splitter blades and the impeller outlet. The numerical steady state simulation neglects the aforementioned unsteady effects found in the experiments and cannot predict the phase shift, however, a detailed asymmetric flow field structure is obviously obtained.

  15. 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.

  16. 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)

  17. 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.

  18. 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.)

  19. 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.)

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Increased ratio of serum matrix metalloproteinase-9 against TIMP-1 predicts poor wound healing in diabetic foot ulcers.

    Science.gov (United States)

    Li, Zhihong; Guo, Shuqin; Yao, Fang; Zhang, Yunliang; Li, Tingting

    2013-01-01

    Little is known about serum concentrations of Matrix Metalloproteinase-9 (MMP-9), MMP-2, TIMP-1 and TIMP-2 in diabetic patients with foot ulcers. This study demonstrates their relationship with wound healing. Ninety-four patients with diabetic foot ulcers were recruited in the study. Serum MMP-9, MMP-2, TIMP-1 and TIMP-2 were measured at the first clinic visit and the end of 4-week treatment and followed up till 12 weeks. According to the decreasing rate of ulcer healing area at the fourth week, we divided those cases into good and poor healers. Through analyses, we explore the possible relationship among those factors and degree of wound healing. The median level of serum MMP-9 in good healers was lower than poor healers at first visit (124.2 μg/L vs 374.6 μg/L, phealing than MMP-9 alone before therapy and after 4 week treatment (r = -0.6475 vs -0.3251, r = -0.7096 vs -0.1231, respectively). Receiver Operator Curve (ROC) showed that the cutoff for MMP-9/TIMP-1 ratio at healing and might provide a novel target for the future therapy in diabetic foot ulcers. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Neutrophil-to-lymphocyte ratio in predicting prognosis and course of community community-acquired pneumonia in hospitalized patients.

    Directory of Open Access Journals (Sweden)

    T. O. Pertseva

    2018-04-01

    Full Text Available Currently, a marker which could be used both to assess the severity of community acquired pneumonia (CAP and determine the risk of complications is being searched. According to some authors, Neutrophil-to-Lymphocyte Ratio (NLR could be such a marker. Therefore, the aim of our research was to determine the diagnostic significance of NLR in patients with CAP and to establish the relationship of NLR with other clinical and laboratory parameters. We conducted a retrospective analysis of 171 case histories of patients with CAP of 3 and 4 clinical groups, with the calculation of NLR (according to the common blood count. In the course of the work, it was found that NLR reflects a balance between the response of neutrophils and lymphocytes and this parameter is associated with the severity of systemic inflammation in patients with CAP. NLR has good diagnostic value in determining the mortality risk in patients with CAP, specially an increase in the level of NLR (more than 10 is associated with a high risk of life-threatening complications.

  6. 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).

  7. 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

  8. 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

  9. Peripheral venous blood neutrophil-to-lymphocyte ratio predicts survival in patients with advanced gastric cancer treated with neoadjuvant chemotherapy

    Directory of Open Access Journals (Sweden)

    Chen L

    2017-05-01

    Full Text Available Li Chen,1 Yanjiao Zuo,1 Lihua Zhu,2 Yuxin Zhang,3 Sen Li,1 Fei Ma,4 Yu Han,5 Hongjiang Song,1 Yingwei Xue11Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, Heilongjiang, 2Department of Pathogen Biology, School of Basic Medical Sciences, North China University of Science and Technology, Tangshan, Hebei, 3Department of General Surgery, Mudanjiang First People’s Hospital, Mudanjiang, 4Department of Breast Surgery, 5Department of Gastrointestinal Oncology, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, Heilongjiang, People’s Republic of ChinaBackground: Accurate and useful predictors of gastric carcinoma treated with neoadjuvant chemotherapy are lacking at present. We aim to explore the potential prognostic significance of the neutrophil-to-lymphocyte ratio (NLR in advanced gastric cancer receiving S-1 plus oxaliplatin (SOX or oxaliplatin and capecitabine (XELOX regimen.Methods: We enrolled 91 patients with advanced gastric cancer treated with neoadjuvant chemotherapy from August 2008 to September 2015. The peripheral venous blood samples were collected before neoadjuvant chemotherapy. The NLR was divided into two groups: low NLR <2.17 group and high NLR ≥2.17 group. Univariate analysis on disease-free survival (DFS and overall survival (OS were generated using the Kaplan–Meier method and compared using the log-rank test. Prognostic factors were assessed by univariate analyses, and the independent prognostic factors were evaluated using multivariate analysis (Cox’s proportional-hazards regression model.Results: The univariate analysis showed that median DFS and median OS were worse for high NLR values than low NLR values before neoadjuvant chemotherapy (median DFS: 19.97 and 26.87 months, respectively, P=0.299; median OS: 25.83 and 29.73 months, respectively, P=0.405. Multivariate analysis showed that the NLR before neoadjuvant

  10. Post-treatment neutrophil-to-lymphocyte ratio predicts for overall survival in brain metastases treated with stereotactic radiosurgery.

    Science.gov (United States)

    Chowdhary, Mudit; Switchenko, Jeffrey M; Press, Robert H; Jhaveri, Jaymin; Buchwald, Zachary S; Blumenfeld, Philip A; Marwaha, Gaurav; Diaz, Aidnag; Wang, Dian; Abrams, Ross A; Olson, Jeffrey J; Shu, Hui-Kuo G; Curran, Walter J; Patel, Kirtesh R

    2018-05-30

    Neutrophil-to-lymphocyte ratio (NLR) is a surrogate for systemic inflammatory response and its elevation has been shown to be a poor prognostic factor in various malignancies. Stereotactic radiosurgery (SRS) can induce a leukocyte-predominant inflammatory response. This study investigates the prognostic impact of post-SRS NLR in patients with brain metastases (BM). BM patients treated with SRS from 2003 to 2015 were retrospectively identified. NLR was calculated from the most recent full blood counts post-SRS. Overall survival (OS) and intracranial outcomes were calculated using the Kaplan-Meier method and cumulative incidence with competing risk for death, respectively. 188 patients with 328 BM treated with SRS had calculable post-treatment NLR values. Of these, 51 (27.1%) had a NLR > 6. The overall median imaging follow-up was 13.2 (14.0 vs. 8.7 for NLR ≤ 6.0 vs. > 6.0) months. Baseline patient and treatment characteristics were well balanced, except for lower rate of ECOG performance status 0 in the NLR > 6 cohort (33.3 vs. 44.2%, p = 0.026). NLR > 6 was associated with worse 1- and 2-year OS: 59.9 vs. 72.9% and 24.6 vs. 43.8%, (p = 0.028). On multivariable analysis, NLR > 6 (HR: 1.53; 95% CI 1.03-2.26, p = 0.036) and presence of extracranial metastases (HR: 1.90; 95% CI 1.30-2.78; p < 0.001) were significant predictors for worse OS. No association was seen with NLR and intracranial outcomes. Post-treatment NLR, a potential marker for post-SRS inflammatory response, is inversely associated with OS in patients with BM. If prospectively validated, NLR is a simple, systemic marker that can be easily used to guide subsequent management.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. Biogas Improvement by Adding Australian Zeolite During the Anaerobic Digestion of C:N Ratio Adjusted Swine Manure

    DEFF Research Database (Denmark)

    Wijesinghe, D. Thushari N.; Dassanayake, Kithsiri B.; Sommer, Sven G.

    2018-01-01

    Abstract: Maintenance of the ideal carbon: nitrogen (C:N) ratio with a minimum level of TAN is a key challenge for achieving maximum potential CH4 production through the anaerobic digestion process of agricultural waste such as swine manure. Biogas production can be enhanced by adding zeolite...... into the anaerobic digestion medium. However, the effects of zeolite addition to C:N ratio adjusted feedstock, on the digester performance is unknown. The objectives of this study were to investigate the effect of Australian zeolite on anaerobic digestion of swine manure with a C:N ratio adjusted to 30...... and to determine the optimal zeolite application rate to achieve the best performance. The Australian zeolite significantly enhanced CH4 production and reduced the lag phase of anaerobic digestion in batch production. The optimal addition rate of zeolite was appeared to be around 40 g/L. The better digester...

  17. 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.

  18. 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.

  19. Improving Stiffness-to-weight Ratio of Spot-welded Structures based upon Nonlinear Finite Element Modelling

    Science.gov (United States)

    Zhang, Shengyong

    2017-07-01

    Spot welding has been widely used for vehicle body construction due to its advantages of high speed and adaptability for automation. An effort to increase the stiffness-to-weight ratio of spot-welded structures is investigated based upon nonlinear finite element analysis. Topology optimization is conducted for reducing weight in the overlapping regions by choosing an appropriate topology. Three spot-welded models (lap, doubt-hat and T-shape) that approximate “typical” vehicle body components are studied for validating and illustrating the proposed method. It is concluded that removing underutilized material from overlapping regions can result in a significant increase in structural stiffness-to-weight ratio.

  20. Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

    Science.gov (United States)

    Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

    2017-11-01

    The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

  1. 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.

  2. 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,

  3. 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.

  4. Parallel Array Bistable Stochastic Resonance System with Independent Input and Its Signal-to-Noise Ratio Improvement

    Directory of Open Access Journals (Sweden)

    Wei Li

    2014-01-01

    with independent components and averaged output; second, we give a deduction of the output signal-to-noise ratio (SNR for this system to show the performance. Our examples show the enhancement of the system and how different parameters influence the performance of the proposed parallel array.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. The Ratio of Partial Pressure Arterial Oxygen and Fraction of Inspired Oxygen 1 Day After Acute Respiratory Distress Syndrome Onset Can Predict the Outcomes of Involving Patients.

    Science.gov (United States)

    Lai, Chih-Cheng; Sung, Mei-I; Liu, Hsiao-Hua; Chen, Chin-Ming; Chiang, Shyh-Ren; Liu, Wei-Lun; Chao, Chien-Ming; Ho, Chung-Han; Weng, Shih-Feng; Hsing, Shu-Chen; Cheng, Kuo-Chen

    2016-04-01

    The initial hypoxemic level of acute respiratory distress syndrome (ARDS) defined according to Berlin definition might not be the optimal predictor for prognosis. We aimed to determine the predictive validity of the stabilized ratio of partial pressure arterial oxygen and fraction of inspired oxygen (PaO2/FiO2 ratio) following standard ventilator setting in the prognosis of patients with ARDS.This prospective observational study was conducted in a single tertiary medical center in Taiwan and compared the stabilized PaO2/FiO2 ratio (Day 1) following standard ventilator settings and the PaO2/FiO2 ratio on the day patients met ARDS Berlin criteria (Day 0). Patients admitted to intensive care units and in accordance with the Berlin criteria for ARDS were collected between December 1, 2012 and May 31, 2015. Main outcome was 28-day mortality. Arterial blood gas and ventilator setting on Days 0 and 1 were obtained.A total of 238 patients met the Berlin criteria for ARDS were enrolled, and they were classified as mild (n = 50), moderate (n = 125), and severe (n = 63) ARDS, respectively. Twelve (5%) patients who originally were classified as ARDS did not continually meet the Berlin definition, and a total of 134 (56%) patients had the changes regarding the severity of ARDS from Day 0 to Day 1. The 28-day mortality rate was 49.1%, and multivariate analysis identified age, PaO2/FiO2 on Day 1, number of organ failures, and positive fluid balance within 5 days as significant risk factors of death. Moreover, the area under receiver-operating curve for mortality prediction using PaO2/FiO2 on Day 1 was significant higher than that on Day 0 (P = 0.016).PaO2/FiO2 ratio on Day 1 after applying mechanical ventilator is a better predictor of outcomes in patients with ARDS than those on Day 0.

  11. The Optimal Cut-Off Value of Neutrophil-to-Lymphocyte Ratio for Predicting Prognosis in Adult Patients with Henoch–Schönlein Purpura

    Science.gov (United States)

    Park, Chan Hyuk; Han, Dong Soo; Jeong, Jae Yoon; Eun, Chang Soo; Yoo, Kyo-Sang; Jeon, Yong Cheol; Sohn, Joo Hyun

    2016-01-01

    Background The development of gastrointestinal (GI) bleeding and end-stage renal disease (ESRD) can be a concern in the management of Henoch–Schönlein purpura (HSP). We aimed to evaluate whether the neutrophil-to-lymphocyte ratio (NLR) is associated with the prognosis of adult patients with HSP. Methods Clinical data including the NLR of adult patients with HSP were retrospectively analyzed. Patients were classified into three groups as follows: (a) simple recovery, (b) wax & wane without GI bleeding, and (c) development of GI bleeding. The optimal cut-off value was determined using a receiver operating characteristics curve and the Youden index. Results A total of 66 adult patients were enrolled. The NLR was higher in the GI bleeding group than in the simple recovery or wax & wane group (simple recovery vs. wax & wane vs. GI bleeding; median [IQR], 2.32 [1.61–3.11] vs. 3.18 [2.16–3.71] vs. 7.52 [4.91–10.23], P<0.001). For the purpose of predicting simple recovery, the optimal cut-off value of NLR was 3.18, and the sensitivity and specificity were 74.1% and 75.0%, respectively. For predicting development of GI bleeding, the optimal cut-off value was 3.90 and the sensitivity and specificity were 87.5% and 88.6%, respectively. Conclusions The NLR is useful for predicting development of GI bleeding as well as simple recovery without symptom relapse. Two different cut-off values of NLR, 3.18 for predicting an easy recovery without symptom relapse and 3.90 for predicting GI bleeding can be used in adult patients with HSP. PMID:27073884

  12. 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

  13. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Science.gov (United States)

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  14. 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.

  15. 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.

  16. 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).

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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...

  5. The contribution of educational class in improving accuracy of cardiovascular risk prediction across European regions

    DEFF Research Database (Denmark)

    Ferrario, Marco M; Veronesi, Giovanni; Chambless, Lloyd E

    2014-01-01

    OBJECTIVE: To assess whether educational class, an index of socioeconomic position, improves the accuracy of the SCORE cardiovascular disease (CVD) risk prediction equation. METHODS: In a pooled analysis of 68 455 40-64-year-old men and women, free from coronary heart disease at baseline, from 47...

  6. 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.

  7. 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 ...

  8. 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

  9. THE OPTIMAL RATIO OF NILE TILAPIA (Oreochromis niloticus AND COMMON CARP (Cyprinus carpio FOR IMPROVING PRODUCTIVITY ON DEEP WATER POND

    Directory of Open Access Journals (Sweden)

    Imam Taufik

    2013-06-01

    Full Text Available Pond productivity can be increased by applied polyculture system in the deep pond. The purpose of this experiment is to examine the optimal ratio between nile tilapia and common carp, in order to increase the productivity. Nine concrete tanks (15 m2 with water depth of 2.2 m and were completed by water inlet, water outlet, and aeration. Both of nile tilapia and common carp with size ranging of 5-8 cm in total length were used. Stock density was 150 ind./m2. The difference ratio of both fish tilapia and carp of fish stocked as a treatment. The fish ratio this experiment were as followed: A 100%; B 80%:20%; C 60%:40%. Fish fed by pellet until at ad libitum. The duration of experiment was 100 days. Parameters such as survival, growth, and productivity were observed every ten days during the experiment period. Water quality parameters were also periodically observed. The results showed that survival of nile tilapia among the treatments were not significantly different (P>0.05 where survival of common carp at B treatment was better than C treatment (P<0.05. The highest of growth of absolute weight (94.86±2.85 g and total length (14.71±1 cm of nile tilapia at B treatment was found (P<0.05 where the best of growth of absolute weight (106.52±10.47 g and total length (11.57±1.78 cm of common carp was also found at B treatment (P<0.05. Biomass productivity at B treatment was the highest compared with A treatment (P<0.05. Combination between polyculture and the deep water pond technology could increase productivity. The polyculture system and the deep water pond technology would be able to keep constant water quality within in the threshold accordance with the regulation for fish culture.

  10. Improvement of the XANAM System and Acquisition of a Peak Signal with a High S/N ratio

    International Nuclear Information System (INIS)

    Suzuki, S; Nakamura, M; Kinoshita, K; Koike, Y; Fujikawa, K; Matsudaira, N; Chun, W-J; Nomura, M; Asakura, K

    2007-01-01

    We have made remarkable progress in detecting X-ray-induced frequency shift signals, which will promote development of a chemically sensitive NC-AFM. A highperformance controller provides a tenfold higher signal to noise ratio than that previously reported. We confirmed that the frequency shift or complementary Z-feedback signal dependence on X-ray energy has a peak. An important feature of the signal is that it does not follow the absorption spectrum of a surface element. These new findings are important to elucidate this novel X-ray-induced phenomenon

  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. 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.

  13. 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...

  14. 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.

  15. Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L. Improved by Accounting for Linkage Disequilibrium

    Directory of Open Access Journals (Sweden)

    Guillaume P. Ramstein

    2016-04-01

    Full Text Available Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.

  16. 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.

  17. 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.

  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. 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

  20. Integration of net zero energy building with smart grid to improve regional electrification ratio towards sustainable development

    Science.gov (United States)

    Latief, Yusuf; Berawi, Mohammed Ali; Supriadi, Leni; Bintang Koesalamwardi, Ario; Petroceany, Jade; Herzanita, Ayu

    2017-12-01

    Indonesia is currently encouraging its physical, social and economy development. Physical development for economic development have to be supported by energy availability. For Indonesia, 90% of electrification ratio is still become an important task that has to be completed by the Government. However, the effort to increase electrification can become an environmental problem if it’s done with BAU scenario. The by-product of electric generation is the GHG, which increasing every year since 2006 from various sectors i.e. industry, housing, commercial, transportation, and energy. Net Zero Energy Building (NZEB) is an energy efficient building which can produce energy independently from clean and renewable sources. The energy that is generated by NZEB can be used for the building itself, and can be exported to the central grid. The integration of NZEB and Smart Grid can solve today’s issue on electrification ratio. Literature study will find benchmarks which can be applied in Indonesia along with possible obstacles in applying this technology.

  1. 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.

  2. 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.

  3. 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.

  4. Clinical significance of the neutrophil-lymphocyte ratio as an early predictive marker for adverse outcomes in patients with acute pancreatitis.

    Science.gov (United States)

    Jeon, Tae Joo; Park, Ji Young

    2017-06-07

    To investigated the prognostic value of the neutrophil-lymphocyte ratio (NLR) in patients with acute pancreatitis and determined an optimal cut-off value for the prediction of adverse outcomes in these patients. We retrospectively analyzed 490 patients with acute pancreatitis diagnosed between March 2007 and December 2012. NLRs were calculated at admission and 24, 48, and 72 h after admission. Patients were grouped according to acute pancreatitis severity and organ failure occurrence, and a comparative analysis was performed to compare the NLR between groups. Among the 490 patients, 70 had severe acute pancreatitis with 31 experiencing organ failure. The severe acute pancreatitis group had a significantly higher NLR than the mild acute pancreatitis group on all 4 d (median, 6.14, 6.71, 5.70, and 4.00 vs 4.74, 4.47, 3.20, and 3.30, respectively, P pancreatitis. Elevated baseline NLR correlates with severe acute pancreatitis and organ failure.

  5. The Multi-center Evaluation of the Accuracy of the Contrast MEdium INduced Pd/Pa RaTiO in Predicting FFR (MEMENTO-FFR) Study.

    Science.gov (United States)

    Leone, Antonio Maria; Martin-Reyes, Roberto; Baptista, Sergio B; Amabile, Nicolas; Raposo, Luis; Franco Pelaez, Juan Antonio; Trani, Carlo; Cialdella, Pio; Basile, Eloisa; Zimbardo, Giuseppe; Burzotta, Francesco; Porto, Italo; Aurigemma, Cristina; Rebuzzi, Antonio G; Faustino, Mariana; Niccoli, Giampaolo; Abreu, Pedro F; Slama, Michel S; Spagnoli, Vincent; Telleria Arrieta, Miren; Amat Santos, Ignacio J; de la Torre Hernandez, Jose M; Lopez Palop, Ramon; Crea, Filippo

    2016-08-20

    Adenosine administration is needed for the achievement of maximal hyperaemia fractional flow reserve (FFR) assessment. The objective was to test the accuracy of Pd/Pa ratio registered during submaximal hyperaemia induced by non-ionic contrast medium (contrast FFR [cFFR]) in predicting FFR and comparing it to the performance of resting Pd/Pa in a collaborative registry of 926 patients enrolled in 10 hospitals from four European countries (Italy, Spain, France and Portugal). Resting Pd/Pa, cFFR and FFR were measured in 1,026 coronary stenoses functionally evaluated using commercially available pressure wires. cFFR was obtained after intracoronary injection of contrast medium, while FFR was measured after administration of adenosine. Resting Pd/Pa and cFFR were significantly higher than FFR (0.93±0.05 vs. 0.87±0.08 vs. 0.84±0.08, ptime and costs.

  6. An improved determination of the ratio of W and Z masses at the CERN anti pp collider

    International Nuclear Information System (INIS)

    Alitti, J.; Ambrosini, G.; Ansari, R.; Autiero, D.; Bareyre, P.; Bertram, I.A.; Blaylock, G.; Bonamy, P.; Borer, K.; Bourliaud, M.; Buskulic, D.; Carboni, G.; Cavalli, D.; Cavasinni, V.; Cenci, P.; Chollet, J.C.; Conta, C.; Costa, G.; Costantini, F.; Cozzi, L.; Cravero, A.; Curatolo, M.; Dell'Acqua, A.; DelPrete, T.; DeWolf, R.S.; DiLella, L.; Ducros, Y.; Egan, G.F.; Einsweiler, K.F.; Esposito, B.; Fayard, L.; Federspiel, A.; Ferrari, R.; Fraternali, M.; Froidevaux, D.; Fumagalli, G.; Gaillard, J.M.; Gianotti, F.; Gildemeister, O.; Goessling, C.; Goggi, V.G.; Gruenendahl, S.; Hara, K.; Hellman, S.; Hrivnac, J.; Hufnagel, H.; Hugentobler, E.; Hultqvist, K.; Iacopini, E.; Incandela, J.; Jakobs, K.; Jenni, P.; Kluge, E.E.; Kurz, N.; Lami, S.; Lariccia, P.; Lefebvre, M.; Linssen, L.; Livan, M.; Lubrano, P.; Magneville, C.; Mandelli, L.; Mapelli, L.; Mazzanti, M.; Meier, K.; Merkel, B.; Meyer, J.P.; Moniez, M.; Moning, R.; Morganti, M.; Mueller, L.; Munday, D.J.; Nessi, M.; Nessi-Tedaldi, F.; Onions, C.; Pal, T.; Parker, M.A.; Parrour, G.; Pastore, F.; Pennacchio, E.; Pentney, J.M.; Pepe, M.; Perini, L.; Petridou, C.; Petroff, P.; Plothow-Besch, H.; Polesello, G.; Poppleton, A.; Pretzl, K.; Primavera, M.; Punturo, M.; Repellin, J.P.; Rimoldi, A.; Sacchi, M.; Scampoli, P.; Schacher, J.; Schmidt, B.; Simak, V.; Singh, S.L.; Sondermann, V.; Spiwoks, R.; Stapnes, S.; Talamonti, C.; Tondini, F.; Tovey, S.N.; Tsesmelis, E.; Unal, G.; Valdata-Nappi, M.; Vercesi, V.; Weidberg, A.R.; Wells, P.S.; White, T.O.; Wood, D.R.; Wotton, S.A.; Zaccone, H.; Zylberstejn, A.

    1992-01-01

    The W and Z bosons masses, m W and m Z , are measured using samples of W→eν and Z→e + e - decays observed in anti pp collisions at √s=630 GeV. The ratio is found to be m W /m Z =0.8813±0.0036±0.0019. This gives a value sin 2 θ W =0.2234±0.0064±0.0033, and in combination with precise m Z measurements from LEP yields m W -80.35±0.33±0.17 GeV. This result is in good agreement with other experiments, and with the standard model for a top quark mass lighter than 250 GeV. (orig.)

  7. Real-time photonic sampling with improved signal-to-noise and distortion ratio using polarization-dependent modulators

    Science.gov (United States)

    Liang, Dong; Zhang, Zhiyao; Liu, Yong; Li, Xiaojun; Jiang, Wei; Tan, Qinggui

    2018-04-01

    A real-time photonic sampling structure with effective nonlinearity suppression and excellent signal-to-noise ratio (SNR) performance is proposed. The key points of this scheme are the polarization-dependent modulators (P-DMZMs) and the sagnac loop structure. Thanks to the polarization sensitive characteristic of P-DMZMs, the differences between transfer functions of the fundamental signal and the distortion become visible. Meanwhile, the selection of specific biases in P-DMZMs is helpful to achieve a preferable linearized performance with a low noise level for real-time photonic sampling. Compared with the quadrature-biased scheme, the proposed scheme is capable of valid nonlinearity suppression and is able to provide a better SNR performance even in a large frequency range. The proposed scheme is proved to be effective and easily implemented for real time photonic applications.

  8. Spectral analysis software improves confidence in plant and soil water stable isotope analyses performed by isotope ratio infrared spectroscopy (IRIS).

    Science.gov (United States)

    West, A G; Goldsmith, G R; Matimati, I; Dawson, T E

    2011-08-30

    Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be

  9. 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.

  10. 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.

  11. 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.

  12. 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