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Sample records for significantly improved predictions

  1. 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.

  2. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions.

    Directory of Open Access Journals (Sweden)

    Tomislav Hengl

    Full Text Available 80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS project was established in 2008. Over the period 2008-2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management--organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na. We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15-75% in Root Mean Squared Error (RMSE across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring

  3. Parameter definition using vibration prediction software leads to significant drilling performance improvements

    Energy Technology Data Exchange (ETDEWEB)

    Amorim, Dalmo; Hanley, Chris Hanley; Fonseca, Isaac; Santos, Juliana [National Oilwell Varco, Houston TX (United States); Leite, Daltro J.; Borella, Augusto; Gozzi, Danilo [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    field monitoring. Vibration prediction diminishes the importance of trial-and-error procedures such as drill-off tests, which are valid only for short sections. It also solves an existing lapse in Mechanical Specific Energy (MSE) real-time drilling control programs applying the theory of Teale, which states that a drilling system is perfectly efficient when it spends the exact energy to overcome the in situ rock strength. Using the proprietary software tool this paper will examine the resonant vibration modes that may be initiated while drilling with different BHA's and drill string designs, showing that the combination of a proper BHA design along with the correct selection of input parameters results in an overall improvement to drilling efficiency. Also, being the BHA predictively analyzed, it will be reduced the potential for vibration or stress fatigue in the drill string components, leading to a safer operation. In the recent years there has been an increased focus on vibration detection, analysis, and mitigation techniques, where new technologies, like the Drilling Dynamics Data Recorders (DDDR), may provide the capability to capture high frequency dynamics data at multiple points along the drilling system. These tools allow the achievement of drilling performance improvements not possible before, opening a whole new array of opportunities for optimization and for verification of predictions calculated by the drill string dynamics modeling software tool. The results of this study will identify how the dynamics from the drilling system, interacting with formation, directly relate to inefficiencies and to the possible solutions to mitigate drilling vibrations in order to improve drilling performance. Software vibration prediction and downhole measurements can be used for non-drilling operations like drilling out casing or reaming, where extremely high vibration levels - devastating to the cutting structure of the bit before it has even touched bottom - have

  4. Survival prediction algorithms miss significant opportunities for improvement if used for case selection in trauma quality improvement programs.

    Science.gov (United States)

    Heim, Catherine; Cole, Elaine; West, Anita; Tai, Nigel; Brohi, Karim

    2016-09-01

    Quality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were 'expected to survive'. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as 'expected'. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement. We conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator. Over 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care. TRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs. Copyright © 2016 Elsevier

  5. Predicting significant torso trauma.

    Science.gov (United States)

    Nirula, Ram; Talmor, Daniel; Brasel, Karen

    2005-07-01

    Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model. Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models. There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models. We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.

  6. 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.

  7. Towards an improved prediction of the free radical scavenging potency of flavonoids: the significance of double PCET mechanisms.

    Science.gov (United States)

    Amić, Ana; Marković, Zoran; Dimitrić Marković, Jasmina M; Stepanić, Višnja; Lučić, Bono; Amić, Dragan

    2014-01-01

    The 1H(+)/1e(-) and 2H(+)/2e(-) proton-coupled electron transfer (PCET) processes of free radical scavenging by flavonoids were theoretically studied for aqueous and lipid environments using the PM6 and PM7 methods. The results reported here indicate that the significant contribution of the second PCET mechanism, resulting in the formation of a quinone/quinone methide, effectively discriminates the active from inactive flavonoids. The predictive potency of descriptors related to the energetics of second PCET mechanisms (the second O-H bond dissociation enthalpy (BDE2) related to hydrogen atom transfer (HAT) mechanism, and the second electron transfer enthalpy (ETE2) related to sequential proton loss electron transfer (SPLET) mechanism) are superior to the currently used indices, which are related to the first 1H(+)/1e(-) processes, and could serve as primary descriptors in development of the QSAR (quantitative structure-activity relationships) of flavonoids. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

    Science.gov (United States)

    Mi, Tian; Merlin, Jerlin Camilus; Deverasetty, Sandeep; Gryk, Michael R; Bill, Travis J; Brooks, Andrew W; Lee, Logan Y; Rathnayake, Viraj; Ross, Christian A; Sargeant, David P; Strong, Christy L; Watts, Paula; Rajasekaran, Sanguthevar; Schiller, Martin R

    2012-01-01

    Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

  9. 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.

  10. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  11. Addendum to the article: Misuse of null hypothesis significance testing: Would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

    Science.gov (United States)

    Bundschuh, Mirco; Newman, Michael C; Zubrod, Jochen P; Seitz, Frank; Rosenfeldt, Ricki R; Schulz, Ralf

    2015-03-01

    We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

  12. Carotid endarterectomy significantly improves postoperative laryngeal sensitivity.

    Science.gov (United States)

    Hammer, Georg Philipp; Tomazic, Peter Valentin; Vasicek, Sarah; Graupp, Matthias; Gugatschka, Markus; Baumann, Anneliese; Konstantiniuk, Peter; Koter, Stephan Herwig

    2016-11-01

    sensory threshold on the operated-on side (6.08 ± 2.02 mm Hg) decreased significantly at the 6-week follow-up, even in relation to the preoperative measure (P = .022). With the exception of one patient with permanent unilateral vocal fold immobility, no signs of nerve injury were detected. In accordance with previous reports, injuries to the recurrent laryngeal nerve during CEA seem to be rare. In most patients, postoperative symptoms (globus, dysphagia, dysphonia) and signs fade within a few weeks without any specific therapeutic intervention. This study shows an improved long-term postoperative superior laryngeal nerve function with regard to laryngopharyngeal sensitivity. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  13. 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.

  14. 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.

  15. Inhaler Reminders Significantly Improve Asthma Patients' Use of Controller Medications

    Science.gov (United States)

    ... controller medications Share | Inhaler reminders significantly improve asthma patients’ use of controller medications Published Online: July 22, ... the burden and risk of asthma, but many patients do not use them regularly. This poor adherence ...

  16. Significant improvement in the thermal annealing process of optical resonators

    Science.gov (United States)

    Salzenstein, Patrice; Zarubin, Mikhail

    2017-05-01

    Thermal annealing performed during process improves the quality of the roughness of optical resonators reducing stresses at the periphery of their surface thus allowing higher Q-factors. After a preliminary realization, the design of the oven and the electronic method were significantly improved thanks to nichrome resistant alloy wires and chopped basalt fibers for thermal isolation during the annealing process. Q-factors can then be improved.

  17. 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.

  18. 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.

  19. 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.

  20. Training directionally selective motion pathways can significantly improve reading efficiency

    Science.gov (United States)

    Lawton, Teri

    2004-06-01

    This study examined whether perceptual learning at early levels of visual processing would facilitate learning at higher levels of processing. This was examined by determining whether training the motion pathways by practicing leftright movement discrimination, as found previously, would improve the reading skills of inefficient readers significantly more than another computer game, a word discrimination game, or the reading program offered by the school. This controlled validation study found that practicing left-right movement discrimination 5-10 minutes twice a week (rapidly) for 15 weeks doubled reading fluency, and significantly improved all reading skills by more than one grade level, whereas inefficient readers in the control groups barely improved on these reading skills. In contrast to previous studies of perceptual learning, these experiments show that perceptual learning of direction discrimination significantly improved reading skills determined at higher levels of cognitive processing, thereby being generalized to a new task. The deficits in reading performance and attentional focus experienced by the person who struggles when reading are suggested to result from an information overload, resulting from timing deficits in the direction-selectivity network proposed by Russell De Valois et al. (2000), that following practice on direction discrimination goes away. This study found that practicing direction discrimination rapidly transitions the inefficient 7-year-old reader to an efficient reader.

  1. Predictive Maintenance (PdM) Centralization for Significant Energy Savings

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Dale

    2010-09-15

    Cost effective predictive maintenance (PdM) technologies and basic energy calculations can mine energy savings form processes or maintenance activities. Centralizing and packaging this information correctly empowers facility maintenance and reliability professionals to build financial justification and support for strategies and personnel to weather global economic downturns and competition. Attendees will learn how to: Systematically build a 'pilot project' for applying PdM and tracking systems; Break down a typical electrical bill to calculate energy savings; Use return on investment (ROI) calculations to identify the best and highest value options, strategies and tips for substantiating your energy reduction maintenance strategies.

  2. Significant Improvement of Catalytic Efficiencies in Ionic Liquids

    International Nuclear Information System (INIS)

    Song, Choong Eui; Yoon, Mi Young; Choi, Doo Seong

    2005-01-01

    The use of ionic liquids as reaction media can confer many advantages upon catalytic reactions over reactions in organic solvents. In ionic liquids, catalysts having polar or ionic character can easily be immobilized without additional structural modification and thus the ionic solutions containing the catalyst can easily be separated from the reagents and reaction products, and then, be reused. More interestingly, switching from an organic solvent to an ionic liquid often results in a significant improvement in catalytic performance (e.g., rate acceleration, (enantio)selectivity improvement and an increase in catalyst stability). In this review, some recent interesting results which can nicely demonstrate these positive 'ionic liquid effect' on catalysis are discussed

  3. Early signs that predict later haemodynamically significant patent ductus arteriosus.

    Science.gov (United States)

    Engür, Defne; Deveci, Murat; Türkmen, Münevver K

    2016-03-01

    Our aim was to determine the optimal cut-off values, sensitivity, specificity, and diagnostic power of 12 echocardiographic parameters on the second day of life to predict subsequent ductal patency. We evaluated preterm infants, born at ⩽32 weeks of gestation, starting on their second day of life, and they were evaluated every other day until ductal closure or until there were clinical signs of re-opening. We measured transductal diameter; pulmonary arterial diastolic flow; retrograde aortic diastolic flow; pulsatility index of the left pulmonary artery and descending aorta; left atrium and ventricle/aortic root ratio; left ventricular output; left ventricular flow velocity time integral; mitral early/late diastolic flow; and superior caval vein diameter and flow as well as performed receiver operating curve analysis. Transductal diameter (>1.5 mm); pulmonary arterial diastolic flow (>25.6 cm/second); presence of retrograde aortic diastolic flow; ductal diameter by body weight (>1.07 mm/kg); left pulmonary arterial pulsatility index (⩽0.71); and left ventricle to aortic root ratio (>2.2) displayed high sensitivity and specificity (p0.9). Parameters with moderate sensitivity and specificity were as follows: left atrial to aortic root ratio; left ventricular output; left ventricular flow velocity time integral; and mitral early/late diastolic flow ratio (p0.05) had low diagnostic value. Left pulmonary arterial pulsatility index, left ventricle/aortic root ratio, and ductal diameter by body weight are useful adjuncts offering a broader outlook for predicting ductal patency.

  4. Bedtime Blood Pressure Chronotherapy Significantly Improves Hypertension Management.

    Science.gov (United States)

    Hermida, Ramón C; Ayala, Diana E; Fernández, José R; Mojón, Artemio; Crespo, Juan J; Ríos, María T; Smolensky, Michael H

    2017-10-01

    Consistent evidence of numerous studies substantiates the asleep blood pressure (BP) mean derived from ambulatory BP monitoring (ABPM) is both an independent and a stronger predictor of cardiovascular disease (CVD) risk than are daytime clinic BP measurements or the ABPM-determined awake or 24-hour BP means. Hence, cost-effective adequate control of sleep-time BP is of marked clinical relevance. Ingestion time, according to circadian rhythms, of hypertension medications of 6 different classes and their combinations significantly improves BP control, particularly sleep-time BP, and reduces adverse effects. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. [Improvement of Phi bodies stain and its clinical significance].

    Science.gov (United States)

    Gong, Xu-Bo; Lu, Xing-Guo; Yan, Li-Juan; Xiao, Xi-Bin; Wu, Dong; Xu, Gen-Bo; Zhang, Xiao-Hong; Zhao, Xiao-Ying

    2009-02-01

    The aim of this study was to improve the dyeing method of hydroperoxidase (HPO), to analyze the morphologic features of Phi bodies and to evaluate the clinical application of this method. 128 bone marrow or peripheral blood smears from patients with myeloid and lymphoid malignancies were stained by improved HPO staining. The Phi bodies were observed with detection rate of Phi bodies in different leukemias. 69 acute myeloid leukemia (AML) specimens were chosen randomly, the positive rate and the number of Phi bodies between the improved HPO and POX stain based on the same substrate of 3, 3'diaminobenzidine were compared. The results showed that the shape of bundle-like Phi bodies was variable, long or short. while the nubbly Phi bodies often presented oval and smooth. Club-like Phi bodies were found in M(3). The detection rates of bundle-like Phi bodies in AML M(1)-M(5) were 42.9% (6/14), 83.3% (15/18), 92.0% (23/25), 52.3% (11/21), 33.3% (5/15) respectively, and those of nubbly Phi bodies were 28.6% (4/14), 66.7% (12/18), 11.1% (3/25), 33.3% (7/21), 20.0% (3/15) respectively. The detection rate of bundle-like Phi bodies in M(3) was significantly higher than that in (M(1) + M(2)) or (M(4) + M(5)) groups. The detection rate of nubbly Phi bodies in (M(1) + M(2)) group was higher than that in M(3) group. In conclusion, after improvement of staining method, the HPO stain becomes simple, the detection rate of Phi bodies is higher than that by the previous method, the positive granules are more obvious, and the results become stable. This improved method plays an important role in differentiating AML from ALL, subtyping AML, and evaluating the therapeutic results.

  6. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper explores the effect of in-depth mobility patterns. Specifically, we study individuals\\' movement behavior, and quantify mobility on the basis of trip frequency, travel purpose and transportation mode. Our hybrid link prediction model is composed of two modules. The first module extracts mobility patterns, including travel purpose and mode, from raw trajectory data. The second module employs the extracted patterns for link prediction. We evaluate our method on two real data sets, GeoLife [15] and Reality Mining [5]. Experimental results show that our hybrid model significantly improves the accuracy of social link prediction, when comparing to primary topology-based solutions. Copyright 2014 ACM.

  7. Ceramic Composite Intermediate Temperature Stress-Rupture Properties Improved Significantly

    Science.gov (United States)

    Morscher, Gregory N.; Hurst, Janet B.

    2002-01-01

    Silicon carbide (SiC) composites are considered to be potential materials for future aircraft engine parts such as combustor liners. It is envisioned that on the hot side (inner surface) of the combustor liner, composites will have to withstand temperatures in excess of 1200 C for thousands of hours in oxidizing environments. This is a severe condition; however, an equally severe, if not more detrimental, condition exists on the cold side (outer surface) of the combustor liner. Here, the temperatures are expected to be on the order of 800 to 1000 C under high tensile stress because of thermal gradients and attachment of the combustor liner to the engine frame (the hot side will be under compressive stress, a less severe stress-state for ceramics). Since these composites are not oxides, they oxidize. The worst form of oxidation for strength reduction occurs at these intermediate temperatures, where the boron nitride (BN) interphase oxidizes first, which causes the formation of a glass layer that strongly bonds the fibers to the matrix. When the fibers strongly bond to the matrix or to one another, the composite loses toughness and strength and becomes brittle. To increase the intermediate temperature stress-rupture properties, researchers must modify the BN interphase. With the support of the Ultra-Efficient Engine Technology (UEET) Program, significant improvements were made as state-of-the-art SiC/SiC composites were developed during the Enabling Propulsion Materials (EPM) program. Three approaches were found to improve the intermediate-temperature stress-rupture properties: fiber-spreading, high-temperature silicon- (Si) doped boron nitride (BN), and outside-debonding BN.

  8. Methylphenidate significantly improves declarative memory functioning of adults with ADHD.

    NARCIS (Netherlands)

    Verster, J.C.; Bekker, E.M.; Kooij, J.J.; Buitelaar, J.K.; Verbaten, M.N.; Volkerts, E.R.; Olivier, B.

    2010-01-01

    BACKGROUND: Declarative memory deficits are common in untreated adults with attention-deficit hyperactivity disorder (ADHD), but limited evidence exists to support improvement after treatment with methylphenidate. The objective of this study was to examine the effects of methylphenidate on memory

  9. 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.

  10. 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

  11. Creating a Middle Grades Environment that Significantly Improves Student Achievement

    Science.gov (United States)

    L'Esperance, Mark E.; Lenker, Ethan; Bullock, Ann; Lockamy, Becky; Mason, Cathy

    2013-01-01

    This article offers an overview of the framework that Sampson County Public Schools (North Carolina) used to critically reflect on the current state of their middle grades schools. The article also highlights the changes that resulted from the district-wide analysis and the ways in which these changes led to a significant increase in the academic…

  12. Low-dose vaporized cannabis significantly improves neuropathic pain.

    Science.gov (United States)

    Wilsey, Barth; Marcotte, Thomas; Deutsch, Reena; Gouaux, Ben; Sakai, Staci; Donaghe, Haylee

    2013-02-01

    We conducted a double-blind, placebo-controlled, crossover study evaluating the analgesic efficacy of vaporized cannabis in subjects, the majority of whom were experiencing neuropathic pain despite traditional treatment. Thirty-nine patients with central and peripheral neuropathic pain underwent a standardized procedure for inhaling medium-dose (3.53%), low-dose (1.29%), or placebo cannabis with the primary outcome being visual analog scale pain intensity. Psychoactive side effects and neuropsychological performance were also evaluated. Mixed-effects regression models demonstrated an analgesic response to vaporized cannabis. There was no significant difference between the 2 active dose groups' results (P > .7). The number needed to treat (NNT) to achieve 30% pain reduction was 3.2 for placebo versus low-dose, 2.9 for placebo versus medium-dose, and 25 for medium- versus low-dose. As these NNTs are comparable to those of traditional neuropathic pain medications, cannabis has analgesic efficacy with the low dose being as effective a pain reliever as the medium dose. Psychoactive effects were minimal and well tolerated, and neuropsychological effects were of limited duration and readily reversible within 1 to 2 hours. Vaporized cannabis, even at low doses, may present an effective option for patients with treatment-resistant neuropathic pain. The analgesia obtained from a low dose of delta-9-tetrahydrocannabinol (1.29%) in patients, most of whom were experiencing neuropathic pain despite conventional treatments, is a clinically significant outcome. In general, the effect sizes on cognitive testing were consistent with this minimal dose. As a result, one might not anticipate a significant impact on daily functioning. Published by Elsevier Inc.

  13. Low Dose Vaporized Cannabis Significantly Improves Neuropathic Pain

    Science.gov (United States)

    Wilsey, Barth; Marcotte, Thomas D.; Deutsch, Reena; Gouaux, Ben; Sakai, Staci; Donaghe, Haylee

    2013-01-01

    We conducted a double-blind, placebo-controlled, crossover study evaluating the analgesic efficacy of vaporized cannabis in subjects, the majority of whom were experiencing neuropathic pain despite traditional treatment. Thirty-nine patients with central and peripheral neuropathic pain underwent a standardized procedure for inhaling either medium dose (3.53%), low dose (1.29%), or placebo cannabis with the primary outcome being VAS pain intensity. Psychoactive side-effects, and neuropsychological performance were also evaluated. Mixed effects regression models demonstrated an analgesic response to vaporized cannabis. There was no significant difference between the two active dose groups’ results (p>0.7). The number needed to treat (NNT) to achieve 30% pain reduction was 3.2 for placebo vs. low dose, 2.9 for placebo vs. medium dose, and 25 for medium vs. low dose. As these NNT are comparable to those of traditional neuropathic pain medications, cannabis has analgesic efficacy with the low dose being, for all intents and purposes, as effective a pain reliever as the medium dose. Psychoactive effects were minimal and well-tolerated, and neuropsychological effects were of limited duration and readily reversible within 1–2 hours. Vaporized cannabis, even at low doses, may present an effective option for patients with treatment-resistant neuropathic pain. PMID:23237736

  14. 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.

  15. 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.

  16. 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.

  17. Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories.

    Science.gov (United States)

    Vaughan, Adam R; Lee, James D; Misztal, Pawel K; Metzger, Stefan; Shaw, Marvin D; Lewis, Alastair C; Purvis, Ruth M; Carslaw, David C; Goldstein, Allen H; Hewitt, C Nicholas; Davison, Brian; Beevers, Sean D; Karl, Thomas G

    2016-07-18

    To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory.

  18. 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.

  19. 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…

  20. Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

    Science.gov (United States)

    Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

    1999-01-01

    Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

  1. Significance of High Resolution GHRSST on prediction of Indian Summer Monsoon

    KAUST Repository

    Jangid, Buddhi Prakash

    2017-02-24

    In this study, the Weather Research and Forecasting (WRF) model was used to assess the importance of very high resolution sea surface temperature (SST) on seasonal rainfall prediction. Two different SST datasets available from the National Centers for Environmental Prediction (NCEP) global model analysis and merged satellite product from Group for High Resolution SST (GHRSST) are used as a lower boundary condition in the WRF model for the Indian Summer Monsoon (ISM) 2010. Before using NCEP SST and GHRSST for model simulation, an initial verification of NCEP SST and GHRSST are performed with buoy measurements. It is found that approximately 0.4 K root mean square difference (RMSD) in GHRSST and NCEP SST when compared with buoy observations available over the Indian Ocean during 01 May to 30 September 2010. Our analyses suggest that use of GHRSST as lower boundary conditions in the WRF model improve the low level temperature, moisture, wind speed and rainfall prediction over ISM region. Moreover, temporal evolution of surface parameters such as temperature, moisture and wind speed forecasts associated with monsoon is also improved with GHRSST forcing as a lower boundary condition. Interestingly, rainfall prediction is improved with the use of GHRSST over the Western Ghats, which mostly not simulated in the NCEP SST based experiment.

  2. Significance of High Resolution GHRSST on prediction of Indian Summer Monsoon

    KAUST Repository

    Jangid, Buddhi Prakash; Kumar, Prashant; Attada, Raju; Kumar, Raj

    2017-01-01

    In this study, the Weather Research and Forecasting (WRF) model was used to assess the importance of very high resolution sea surface temperature (SST) on seasonal rainfall prediction. Two different SST datasets available from the National Centers for Environmental Prediction (NCEP) global model analysis and merged satellite product from Group for High Resolution SST (GHRSST) are used as a lower boundary condition in the WRF model for the Indian Summer Monsoon (ISM) 2010. Before using NCEP SST and GHRSST for model simulation, an initial verification of NCEP SST and GHRSST are performed with buoy measurements. It is found that approximately 0.4 K root mean square difference (RMSD) in GHRSST and NCEP SST when compared with buoy observations available over the Indian Ocean during 01 May to 30 September 2010. Our analyses suggest that use of GHRSST as lower boundary conditions in the WRF model improve the low level temperature, moisture, wind speed and rainfall prediction over ISM region. Moreover, temporal evolution of surface parameters such as temperature, moisture and wind speed forecasts associated with monsoon is also improved with GHRSST forcing as a lower boundary condition. Interestingly, rainfall prediction is improved with the use of GHRSST over the Western Ghats, which mostly not simulated in the NCEP SST based experiment.

  3. 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

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. Integration of biomimicry and nanotechnology for significantly improved detection of circulating tumor cells (CTCs).

    Science.gov (United States)

    Myung, Ja Hye; Park, Sin-Jung; Wang, Andrew Z; Hong, Seungpyo

    2017-12-13

    Circulating tumor cells (CTCs) have received a great deal of scientific and clinical attention as a biomarker for diagnosis and prognosis of many types of cancer. Given their potential significance in clinics, a variety of detection methods, utilizing the recent advances in nanotechnology and microfluidics, have been introduced in an effort of achieving clinically significant detection of CTCs. However, effective detection and isolation of CTCs still remain a tremendous challenge due to their extreme rarity and phenotypic heterogeneity. Among many approaches that are currently under development, this review paper focuses on a unique, promising approach that takes advantages of naturally occurring processes achievable through application of nanotechnology to realize significant improvement in sensitivity and specificity of CTC capture. We provide an overview of successful outcome of this biomimetic CTC capture system in detection of tumor cells from in vitro, in vivo, and clinical pilot studies. We also emphasize the clinical impact of CTCs as biomarkers in cancer diagnosis and predictive prognosis, which provides a cost-effective, minimally invasive method that potentially replaces or supplements existing methods such as imaging technologies and solid tissue biopsy. In addition, their potential prognostic values as treatment guidelines and that ultimately help to realize personalized therapy are discussed. Copyright © 2017. Published by Elsevier B.V.

  9. 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

  10. 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 $\

  11. Artificial neural networks to predict presence of significant pathology in patients presenting to routine colorectal clinics.

    Science.gov (United States)

    Maslekar, S; Gardiner, A B; Monson, J R T; Duthie, G S

    2010-12-01

    Artificial neural networks (ANNs) are computer programs used to identify complex relations within data. Routine predictions of presence of colorectal pathology based on population statistics have little meaning for individual patient. This results in large number of unnecessary lower gastrointestinal endoscopies (LGEs - colonoscopies and flexible sigmoidoscopies). We aimed to develop a neural network algorithm that can accurately predict presence of significant pathology in patients attending routine outpatient clinics for gastrointestinal symptoms. Ethics approval was obtained and the study was monitored according to International Committee on Harmonisation - Good Clinical Practice (ICH-GCP) standards. Three-hundred patients undergoing LGE prospectively completed a specifically developed questionnaire, which included 40 variables based on clinical symptoms, signs, past- and family history. Complete data sets of 100 patients were used to train the ANN; the remaining data was used for internal validation. The primary output used was positive finding on LGE, including polyps, cancer, diverticular disease or colitis. For external validation, the ANN was applied to data from 50 patients in primary care and also compared with the predictions of four clinicians. Clear correlation between actual data value and ANN predictions were found (r = 0.931; P = 0.0001). The predictive accuracy of ANN was 95% in training group and 90% (95% CI 84-96) in the internal validation set and this was significantly higher than the clinical accuracy (75%). ANN also showed high accuracy in the external validation group (89%). Artificial neural networks offer the possibility of personal prediction of outcome for individual patients presenting in clinics with colorectal symptoms, making it possible to make more appropriate requests for lower gastrointestinal endoscopy. © 2010 The Authors. Colorectal Disease © 2010 The Association of Coloproctology of Great Britain and Ireland.

  12. 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)

  13. Accurate prediction of the functional significance of single nucleotide polymorphisms and mutations in the ABCA1 gene.

    Directory of Open Access Journals (Sweden)

    Liam R Brunham

    2005-12-01

    Full Text Available The human genome contains an estimated 100,000 to 300,000 DNA variants that alter an amino acid in an encoded protein. However, our ability to predict which of these variants are functionally significant is limited. We used a bioinformatics approach to define the functional significance of genetic variation in the ABCA1 gene, a cholesterol transporter crucial for the metabolism of high density lipoprotein cholesterol. To predict the functional consequence of each coding single nucleotide polymorphism and mutation in this gene, we calculated a substitution position-specific evolutionary conservation score for each variant, which considers site-specific variation among evolutionarily related proteins. To test the bioinformatics predictions experimentally, we evaluated the biochemical consequence of these sequence variants by examining the ability of cell lines stably transfected with the ABCA1 alleles to elicit cholesterol efflux. Our bioinformatics approach correctly predicted the functional impact of greater than 94% of the naturally occurring variants we assessed. The bioinformatics predictions were significantly correlated with the degree of functional impairment of ABCA1 mutations (r2 = 0.62, p = 0.0008. These results have allowed us to define the impact of genetic variation on ABCA1 function and to suggest that the in silico evolutionary approach we used may be a useful tool in general for predicting the effects of DNA variation on gene function. In addition, our data suggest that considering patterns of positive selection, along with patterns of negative selection such as evolutionary conservation, may improve our ability to predict the functional effects of amino acid variation.

  14. E2F5 status significantly improves malignancy diagnosis of epithelial ovarian cancer

    KAUST Repository

    Kothandaraman, Narasimhan

    2010-02-24

    Background: Ovarian epithelial cancer (OEC) usually presents in the later stages of the disease. Factors, especially those associated with cell-cycle genes, affecting the genesis and tumour progression for ovarian cancer are largely unknown. We hypothesized that over-expressed transcription factors (TFs), as well as those that are driving the expression of the OEC over-expressed genes, could be the key for OEC genesis and potentially useful tissue and serum markers for malignancy associated with OEC.Methods: Using a combination of computational (selection of candidate TF markers and malignancy prediction) and experimental approaches (tissue microarray and western blotting on patient samples) we identified and evaluated E2F5 transcription factor involved in cell proliferation, as a promising candidate regulatory target in early stage disease. Our hypothesis was supported by our tissue array experiments that showed E2F5 expression only in OEC samples but not in normal and benign tissues, and by significantly positively biased expression in serum samples done using western blotting studies.Results: Analysis of clinical cases shows that of the E2F5 status is characteristic for a different population group than one covered by CA125, a conventional OEC biomarker. E2F5 used in different combinations with CA125 for distinguishing malignant cyst from benign cyst shows that the presence of CA125 or E2F5 increases sensitivity of OEC detection to 97.9% (an increase from 87.5% if only CA125 is used) and, more importantly, the presence of both CA125 and E2F5 increases specificity of OEC to 72.5% (an increase from 55% if only CA125 is used). This significantly improved accuracy suggests possibility of an improved diagnostics of OEC. Furthermore, detection of malignancy status in 86 cases (38 benign, 48 early and late OEC) shows that the use of E2F5 status in combination with other clinical characteristics allows for an improved detection of malignant cases with sensitivity

  15. National Emergency Preparedness and Response: Improving for Incidents of National Significance

    National Research Council Canada - National Science Library

    Clayton, Christopher M

    2006-01-01

    The national emergency management system has need of significant improvement in its contingency planning and early consolidation of effort and coordination between federal, state, and local agencies...

  16. 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

  17. 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

  18. 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

  19. Clinical Significance of Hemostatic Parameters in the Prediction for Type 2 Diabetes Mellitus and Diabetic Nephropathy

    Directory of Open Access Journals (Sweden)

    Lianlian Pan

    2018-01-01

    Full Text Available It would be important to predict type 2 diabetes mellitus (T2DM and diabetic nephropathy (DN. This study was aimed at evaluating the predicting significance of hemostatic parameters for T2DM and DN. Plasma coagulation and hematologic parameters before treatment were measured in 297 T2DM patients. The risk factors and their predicting power were evaluated. T2DM patients without complications exhibited significantly different activated partial thromboplastin time (aPTT, platelet (PLT, and D-dimer (D-D levels compared with controls (P<0.01. Fibrinogen (FIB, PLT, and D-D increased in DN patients compared with those without complications (P<0.001. Both aPTT and PLT were the independent risk factors for T2DM (OR: 1.320 and 1.211, P<0.01, resp., and FIB and PLT were the independent risk factors for DN (OR: 1.611 and 1.194, P<0.01, resp.. The area under ROC curve (AUC of aPTT and PLT was 0.592 and 0.647, respectively, with low sensitivity in predicting T2DM. AUC of FIB was 0.874 with high sensitivity (85% and specificity (76% for DN, and that of PLT was 0.564, with sensitivity (60% and specificity (89% based on the cutoff values of 3.15 g/L and 245 × 109/L, respectively. This study suggests that hemostatic parameters have a low predicting value for T2DM, whereas fibrinogen is a powerful predictor for DN.

  20. Frameworks for improvement: clinical audit, the plan-do-study-act cycle and significant event audit.

    Science.gov (United States)

    Gillam, Steve; Siriwardena, A Niroshan

    2013-01-01

    This is the first in a series of articles about quality improvement tools and techniques. We explore common frameworks for improvement, including the model for improvement and its application to clinical audit, plan-do-study-act (PDSA) cycles and significant event analysis (SEA), examining the similarities and differences between these and providing examples of each.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Statistical significance of theoretical predictions: A new dimension in nuclear structure theories (I)

    International Nuclear Information System (INIS)

    DUDEK, J; SZPAK, B; FORNAL, B; PORQUET, M-G

    2011-01-01

    In this and the follow-up article we briefly discuss what we believe represents one of the most serious problems in contemporary nuclear structure: the question of statistical significance of parametrizations of nuclear microscopic Hamiltonians and the implied predictive power of the underlying theories. In the present Part I, we introduce the main lines of reasoning of the so-called Inverse Problem Theory, an important sub-field in the contemporary Applied Mathematics, here illustrated on the example of the Nuclear Mean-Field Approach.

  6. Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

    Science.gov (United States)

    Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

    2014-12-01

    Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

  7. Significant interarm blood pressure difference predicts cardiovascular risk in hypertensive patients: CoCoNet study.

    Science.gov (United States)

    Kim, Su-A; Kim, Jang Young; Park, Jeong Bae

    2016-06-01

    There has been a rising interest in interarm blood pressure difference (IAD), due to its relationship with peripheral arterial disease and its possible relationship with cardiovascular disease. This study aimed to characterize hypertensive patients with a significant IAD in relation to cardiovascular risk. A total of 3699 patients (mean age, 61 ± 11 years) were prospectively enrolled in the study. Blood pressure (BP) was measured simultaneously in both arms 3 times using an automated cuff-oscillometric device. IAD was defined as the absolute difference in averaged BPs between the left and right arm, and an IAD ≥ 10 mm Hg was considered to be significant. The Framingham risk score was used to calculate the 10-year cardiovascular risk. The mean systolic IAD (sIAD) was 4.3 ± 4.1 mm Hg, and 285 (7.7%) patients showed significant sIAD. Patients with significant sIAD showed larger body mass index (P < 0.001), greater systolic BP (P = 0.050), more coronary artery disease (relative risk = 1.356, P = 0.034), and more cerebrovascular disease (relative risk = 1.521, P = 0.072). The mean 10-year cardiovascular risk was 9.3 ± 7.7%. By multiple regression, sIAD was significantly but weakly correlated with the 10-year cardiovascular risk (β = 0.135, P = 0.008). Patients with significant sIAD showed a higher prevalence of coronary artery disease, as well as an increase in 10-year cardiovascular risk. Therefore, accurate measurements of sIAD may serve as a simple and cost-effective tool for predicting cardiovascular risk in clinical settings.

  8. Significant interarm blood pressure difference predicts cardiovascular risk in hypertensive patients

    Science.gov (United States)

    Kim, Su-A; Kim, Jang Young; Park, Jeong Bae

    2016-01-01

    Abstract There has been a rising interest in interarm blood pressure difference (IAD), due to its relationship with peripheral arterial disease and its possible relationship with cardiovascular disease. This study aimed to characterize hypertensive patients with a significant IAD in relation to cardiovascular risk. A total of 3699 patients (mean age, 61 ± 11 years) were prospectively enrolled in the study. Blood pressure (BP) was measured simultaneously in both arms 3 times using an automated cuff-oscillometric device. IAD was defined as the absolute difference in averaged BPs between the left and right arm, and an IAD ≥ 10 mm Hg was considered to be significant. The Framingham risk score was used to calculate the 10-year cardiovascular risk. The mean systolic IAD (sIAD) was 4.3 ± 4.1 mm Hg, and 285 (7.7%) patients showed significant sIAD. Patients with significant sIAD showed larger body mass index (P < 0.001), greater systolic BP (P = 0.050), more coronary artery disease (relative risk = 1.356, P = 0.034), and more cerebrovascular disease (relative risk = 1.521, P = 0.072). The mean 10-year cardiovascular risk was 9.3 ± 7.7%. By multiple regression, sIAD was significantly but weakly correlated with the 10-year cardiovascular risk (β = 0.135, P = 0.008). Patients with significant sIAD showed a higher prevalence of coronary artery disease, as well as an increase in 10-year cardiovascular risk. Therefore, accurate measurements of sIAD may serve as a simple and cost-effective tool for predicting cardiovascular risk in clinical settings. PMID:27310982

  9. Bilirubin nomogram for prediction of significant hyperbilirubinemia in north Indian neonates.

    Science.gov (United States)

    Pathak, Umesh; Chawla, Deepak; Kaur, Saranjit; Jain, Suksham

    2013-04-01

    (i) To construct hour-specific serum total bilirubin (STB) nomogram in neonates born at =35 weeks of gestation; (ii)To evaluate efficacy of pre-discharge bilirubin measurement in predicting hyperbilirubinemia needing treatment. Diagnostic test performance in a prospective cohort study. Teaching hospital in Northern India. Healthy neonates with gestation =35 weeks or birth weight =2000 g. Serum total bilirubin was measured in all enrolled neonates at 24 ± 6, 72-96 and 96-144 h of postnatal age and when indicated clinically. Neonates were followed up during hospital stay and after discharge till completion of 7th postnatal day. Key outcome was significant hyperbilirubinemia (SHB) defined as need of phototherapy based on modified American Academy of Pediatrics (AAP) guidelines. In neonates born at 38 or more weeks of gestation middle line and in neonates born at 37 or less completed weeks of gestation, lower line of phototherapy thresholds were used to initiate phototherapy. For construction of nomogram, STB values were clubbed in six-hour epochs (age ± 3 hours) for postnatal age up to 48 h and twelve-hour epochs (age ± 6 hours) for age beyond 48 h. Predictive ability of the nomogram was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratio, by plotting receiver-operating characteristics (ROC) curve and calculating c-statistic. 997 neonates (birth weight: 2627 ± 536 g, gestation: 37.8 ± 1.5 weeks) were enrolled, of which 931 completed followup. Among enrolled neonates 344 (34.5%) were low birth weight. Rate of exclusive breastfeeding during hospital stay was more than 80%. Bilirubin nomogram was constructed using 40th, 75th and 95th percentile values of hour-specific bilirubin. Pre-discharge STB of =95th percentile was assigned to be in high-risk zone, between 75th and 94th centile in upper-intermediate risk zone, between 40th and 74th centile in lower-intermediate risk zone and below 40th

  10. Utilidad de los puntajes clínicos para mejorar la predicción de enfermedad coronaria significativa después de una prueba de esfuerzo convencional Usefulness of clinical scores to improve prediction of significant coronary heart disease after conventional treadmill exercise testing

    Directory of Open Access Journals (Sweden)

    Fernando A Guerrero

    2008-10-01

    mejoren aún más dicho desempeño.Background: in the last AHA/ACC expert consensus document, clinical scores to improve sensitivity (68% and specificity (77% of the exercise testing, diagnostic method considered a first line diagnostic method for coronary heart disease treatment (one of the main causes of mortality in Colombia and worldwide, are recommended. Nevertheless, few institutions in our country use them and they are difficult to apply in populations different to the ones for which they were developed. For this reason, a study to assess its performance in our environment, is needed. Materials and Methods: Morise and Duke treadmill scores were chosen to assess the reason for its validation in several populations, and were mentioned in the AHA/ACC consensus. The Morise and Duke scores classified patients in at low, middle and high risk for coronary heart disease. Primary objectives: validate the prediction scales for coronary heart disease and determine the best cutoff value for each score in a one year follow-up. Secondary objectives: determine the composite endpoint for acute myocardial infarction, cardiac death, angina requiring hospitalization, coronary obstruction >50% and/or angioplasty and stent implantation. Determine the best cutoff point through the ROC curves. Inclusion Criteria: patients >18 years old with suspected coronary heart disease. Exclusion Criteria: pregnant women with documented coronary heart disease, uninterpretable EKG, incapacity or contraindication for performing exercise stress test for any reason, ST depression 27,5: 18% (45 and diabetes mellitus: 16% (19. Morise score classified 36% (43 patients at low risk, 52% (61 at intermediate risk and 12% (14 at high risk. According to Duke the results were 53% (63, 41% (48 and 6% (7 respectively. When interpreting an isolated exercise testing, cardiologists classified patients: 81% (95 negative, 8% (10 suggestive and 11% (14 positive. The composite endpoint appeared in 11% (14 patients. When

  11. The significance of collateral vessels, as seen on chest CT, in predicting SVC obstruction

    International Nuclear Information System (INIS)

    Yeouk, Young Soo; Kim, Sung Jin; Bae, Il Hun; Kim, Jae Youn; Hwang, Seung Min; Han, Gi Seok; Park, Kil Sun; Kim, Dae Young

    1998-01-01

    To evaluate the significance of collateral veins, as seen on chest CT, in the diagnosis of superior vena cava obstruction. We retrospectively the records of 81 patients in whom collateral veins were seen on chest CT. On spiral CT(n=49), contrast material was infused via power injector, and on conventional CT(n=32), 50 ml bolus infusion was followed by 50 ml drip infusion. Obstruction of the SVC was evaluated on chest CT; if, however, evaluation of the SVC of its major tributaries was difficult, as in five cases, the patient underwent SVC phlebography. Collateral vessels were assigned to one of ten categories. On conventional CT, the jugular venous arch in the only collateral vessel to predict SVC obstruction; on spiral CT, however, collateral vessels are not helpful in the diagnosis of SVC obstruction, but are a nonspecific finding. (author). 12 refs., 2 tab., 2 figs

  12. The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies.

    Science.gov (United States)

    Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming

    2017-06-20

    Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.

  13. Significance of SYT8 For the Detection, Prediction, and Treatment of Peritoneal Metastasis From Gastric Cancer.

    Science.gov (United States)

    Kanda, Mitsuro; Shimizu, Dai; Tanaka, Haruyoshi; Tanaka, Chie; Kobayashi, Daisuke; Hayashi, Masamichi; Iwata, Naoki; Niwa, Yukiko; Yamada, Suguru; Fujii, Tsutomu; Sugimoto, Hiroyuki; Murotani, Kenta; Fujiwara, Michitaka; Kodera, Yasuhiro

    2018-03-01

    To develop novel diagnostic and therapeutic targets specific for peritoneal metastasis of gastric cancer (GC). Advanced GC frequently recurs because of undetected micrometastases even after curative resection. Peritoneal metastasis has been the most frequent recurrent pattern after gastrectomy and is incurable. We conducted a recurrence pattern-specific transcriptome analysis in an independent cohort of 16 patients with stage III GC who underwent curative gastrectomy and adjuvant S-1 for screening candidate molecules specific for peritoneal metastasis of GC. Next, another 340 patients were allocated to discovery and validation sets (1:2) to evaluate the diagnostic and predictive value of the candidate molecule. The results of quantitative reverse-transcription PCR and immunohistochemical analysis were correlated with clinical characteristics and survival. The effects of siRNA-mediated knockdown on phenotype and fluorouracil sensitivity of GC cells were evaluated in vitro, and the therapeutic effects of siRNAs were evaluated using a mouse xenograft model. Synaptotagmin VIII (SYT8) was identified as a candidate biomarker specific to peritoneal metastasis. In the discovery set, the optimal cut-off of SYT8 expression was established as 0.005. Expression levels of SYT8 mRNA in GC tissues were elevated in the validation set comprising patients with peritoneal recurrence or metastasis. SYT8 levels above the cut-off value were significantly and specifically associated with peritoneal metastasis, and served as an independent prognostic marker for peritoneal recurrence-free survival of patients with stage II/III GC. The survival difference between patients with SYT8 levels above and below the cut-off was associated with patients who received adjuvant chemotherapy. Inhibition of SYT8 expression by GC cells correlated with decreased invasion, migration, and fluorouracil resistance. Intraperitoneal administration of SYT8-siRNA inhibited the growth of peritoneal nodules and

  14. Predicting Intentions of a Familiar Significant Other Beyond the Mirror Neuron System

    Directory of Open Access Journals (Sweden)

    Stephanie Cacioppo

    2017-08-01

    Full Text Available Inferring intentions of others is one of the most intriguing issues in interpersonal interaction. Theories of embodied cognition and simulation suggest that this mechanism takes place through a direct and automatic matching process that occurs between an observed action and past actions. This process occurs via the reactivation of past self-related sensorimotor experiences within the inferior frontoparietal network (including the mirror neuron system, MNS. The working model is that the anticipatory representations of others' behaviors require internal predictive models of actions formed from pre-established, shared representations between the observer and the actor. This model suggests that observers should be better at predicting intentions performed by a familiar actor, rather than a stranger. However, little is known about the modulations of the intention brain network as a function of the familiarity between the observer and the actor. Here, we combined functional magnetic resonance imaging (fMRI with a behavioral intention inference task, in which participants were asked to predict intentions from three types of actors: A familiar actor (their significant other, themselves (another familiar actor, and a non-familiar actor (a stranger. Our results showed that the participants were better at inferring intentions performed by familiar actors than non-familiar actors and that this better performance was associated with greater activation within and beyond the inferior frontoparietal network i.e., in brain areas related to familiarity (e.g., precuneus. In addition, and in line with Hebbian principles of neural modulations, the more the participants reported being cognitively close to their partner, the less the brain areas associated with action self-other comparison (e.g., inferior parietal lobule, attention (e.g., superior parietal lobule, recollection (hippocampus, and pair bond (ventral tegmental area, VTA were recruited, suggesting that the

  15. 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

  16. 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

  17. Neuro-Linguistic Programming: Improving Rapport between Track/Cross Country Coaches and Significant Others

    Science.gov (United States)

    Helm, David Jay

    2017-01-01

    This study examines the background information and the components of N.L.P., being eye movements, use of predicates, and posturing, as they apply to improving rapport and empathy between track/cross country coaches and their significant others in the arena of competition to help alleviate the inherent stressors.

  18. Predicting Community College Outcomes: Does High School CTE Participation Have a Significant Effect?

    Science.gov (United States)

    Dietrich, Cecile; Lichtenberger, Eric; Kamalludeen, Rosemaliza

    2016-01-01

    This study explored the relative importance of participation in high school career and technical education (CTE) programs in predicting community college outcomes. A hierarchical generalized linear model (HGLM) was used to predict community college outcome attainment among a random sample of direct community college entrants. Results show that…

  19. 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.

  20. Significant change of predictions related to the future of nuclear power

    International Nuclear Information System (INIS)

    Dumitrache, Ion

    2002-01-01

    During the last two decades of the 20th century, nuclear power contribution increased slowly in the world. This trend was mainly determined by the commissioning of new nuclear power plants, NPP, in the non-developed countries, except for Japan and South Korea. Almost all the forecasts offered the image of the stagnant nuclear power business. Sweden, Germany, Holland and Belgium Governments made clear the intention to stop the production of electricity based on fission. Recently, despite the negative effects on nuclear power of the terrorism events of September 11, 2001, the predictions related to the nuclear power future become much more optimistic. USA, Japan, South Korea and Canada made clear that new NPPs will offer their significant electricity contribution several decades, even after years 2020-2030. Moreover, several old NPP from USA obtained the license for an additional 20 years period of operation. The analysis indicated that most of the existing NPP in USA may increase the level of the maximum global power defined by the initial design. In the European Union the situation is much more complicated. About 35% of the electricity is based now on fission. Several countries, like Sweden and Germany, maintain the position of phasing out the NPPs, as soon as the licensed life-time is over. Finland decided to build a new power plant. France is very favorable to nuclear power, but does not need more energy. In the UK several very old NPP will be shut down, and companies like BNFL and British Energy intend to build new NPP, based on Westinghouse or AECL-Canada advanced reactors. Switzerland and Spain are favorable to the future use of nuclear power. In the eastern part of Europe, almost all the countries intend to base their electricity production on coal, fission, hydro and gas, nuclear contribution being significant. The most impressive increases of nuclear power output are related to Asia; in China, from 2.2 Gwe in 1999, to 18.7 Gwe in 2020, reference case, or 10

  1. 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...

  2. 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.

  3. 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

  4. The prognostic significance of HOTAIR for predicting clinical outcome in patients with digestive system tumors.

    Science.gov (United States)

    Ma, Gaoxiang; Wang, Qiaoyan; Lv, Chunye; Qiang, Fulin; Hua, Qiuhan; Chu, Haiyan; Du, Mulong; Tong, Na; Jiang, Yejuan; Wang, Meilin; Zhang, Zhengdong; Wang, Jian; Gong, Weida

    2015-12-01

    Although some studies have assessed the prognostic value of HOTAIR in patients with digestive system tumors, the relationship between the HOTAIR and outcome of digestive system tumors remains unknown. The PubMed was searched to identify the eligible studies. Here, we performed a meta-analysis with 11 studies, including a total of 903 cases. Pooled hazard ratios (HRs) and 95 % confidence interval (CI) of HOTAIR for cancer survival were calculated. We found that the pooled HR elevated HOTAIR expression in tumor tissues was 2.36 (95 % CI 1.88-2.97) compared with patients with low HOTAIR expression. Moreover, subgroup analysis revealed that HOTAIR overexpression was also markedly associated with short survival for esophageal squamous cell carcinoma (HR 2.19, 95 % CI 1.62-2.94) and gastric cancer (HR 1.66, 95 % CI 1.02-2.68). In addition, up-regulated HOTAIR was significantly related to survival of digestive system cancer among the studies with more follow-up time (follow time ≥ 5 years) (HR 2.51, 95 % CI 1.99-3.17). When stratified by HR resource and number of patients, the result indicated consistent results with the overall analysis. Subgroup analysis on ethnicities did not change the prognostic influence of elevated HOTAIR expression. Additionally, we conducted an independent validation cohort including 71 gastric cancer cases, in which patients with up-regulated HOTAIR expression had an unfavorable outcome with HR of 2.10 (95 % CI 1.10-4.03). The results suggest that aberrant HOTAIR expression may serve as a candidate positive marker to predict the prognosis of patients with carcinoma of digestive system.

  5. Rehearsal significantly improves immediate and delayed recall on the Rey Auditory Verbal Learning Test.

    Science.gov (United States)

    Hessen, Erik

    2011-10-01

    A repeated observation during memory assessment with the Rey Auditory Verbal Learning Test (RAVLT) is that patients who spontaneously employ a memory rehearsal strategy by repeating the word list more than once achieve better scores than patients who only repeat the word list once. This observation led to concern about the ability of the standard test procedure of RAVLT and similar tests in eliciting the best possible recall scores. The purpose of the present study was to test the hypothesis that a rehearsal recall strategy of repeating the word list more than once would result in improved scores of recall on the RAVLT. We report on differences in outcome after standard administration and after experimental administration on Immediate and Delayed Recall measures from the RAVLT of 50 patients. The experimental administration resulted in significantly improved scores for all the variables employed. Additionally, it was found that patients who failed effort screening showed significantly poorer improvement on Delayed Recall compared with those who passed the effort screening. The general clear improvement both in raw scores and T-scores demonstrates that recall performance can be significantly influenced by the strategy of the patient or by small variations in instructions by the examiner.

  6. Costello Syndrome with Severe Nodulocystic Acne: Unexpected Significant Improvement of Acanthosis Nigricans after Oral Isotretinoin Treatment

    Directory of Open Access Journals (Sweden)

    Leelawadee Sriboonnark

    2015-01-01

    Full Text Available We report the case of 17-year-old female diagnosed with Costello syndrome. Genetic testing provided a proof with G12S mutation in the HRAS gene since 3 years of age with a presentation of severe nodulocystic acne on her face. After 2 months of oral isotretinoin treatment, improvement in her acne was observed. Interestingly, an unexpected significant improvement of acanthosis nigricans on her neck and dorsum of her hands was found as well. We present this case as a successful treatment option by using oral isotretinoin for the treatment of acanthosis nigricans in Costello syndrome patients.

  7. Determination of significance in Ecological Impact Assessment: Past change, current practice and future improvements

    Energy Technology Data Exchange (ETDEWEB)

    Briggs, Sam; Hudson, Malcolm D., E-mail: mdh@soton.ac.uk

    2013-01-15

    Ecological Impact Assessment (EcIA) is an important tool for conservation and achieving sustainable development. 'Significant' impacts are those which disturb or alter the environment to a measurable degree. Significance is a crucial part of EcIA, our understanding of the concept in practice is vital if it is to be effective as a tool. This study employed three methods to assess how the determination of significance has changed through time, what current practice is, and what would lead to future improvements. Three data streams were collected: interviews with expert stakeholders, a review of 30 Environmental Statements and a broad-scale survey of the United Kingdom Institute of Ecology and Environmental Management (IEEM) members. The approach taken in the determination of significance has become more standardised and subjectivity has become constrained through a transparent framework. This has largely been driven by a set of guidelines produced by IEEM in 2006. The significance of impacts is now more clearly justified and the accuracy with which it is determined has improved. However, there are limitations to accuracy and effectiveness of the determination of significance. These are the quality of baseline survey data, our scientific understanding of ecological processes and the lack of monitoring and feedback of results. These in turn are restricted by the limited resources available in consultancies. The most notable recommendations for future practice are the implementation of monitoring and the publication of feedback, the creation of a central database for baseline survey data and the streamlining of guidance. - Highlights: Black-Right-Pointing-Pointer The assessment of significance has changed markedly through time. Black-Right-Pointing-Pointer The IEEM guidelines have driven a standardisation of practice. Black-Right-Pointing-Pointer Currently limited by quality of baseline data and scientific understanding. Black-Right-Pointing-Pointer Monitoring

  8. 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.

  9. Histone deacetylase inhibitor significantly improved the cloning efficiency of porcine somatic cell nuclear transfer embryos.

    Science.gov (United States)

    Huang, Yongye; Tang, Xiaochun; Xie, Wanhua; Zhou, Yan; Li, Dong; Yao, Chaogang; Zhou, Yang; Zhu, Jianguo; Lai, Liangxue; Ouyang, Hongsheng; Pang, Daxin

    2011-12-01

    Valproic acid (VPA), a histone deacetylase inbibitor, has been shown to generate inducible pluripotent stem (iPS) cells from mouse and human fibroblasts with a significant higher efficiency. Because successful cloning by somatic cell nuclear transfer (SCNT) undergoes a full reprogramming process in which the epigenetic state of a differentiated donor nuclear is converted into an embryonic totipotent state, we speculated that VPA would be useful in promoting cloning efficiency. Therefore, in the present study, we examined whether VPA can promote the developmental competence of SCNT embryos by improving the reprogramming state of donor nucleus. Here we report that 1 mM VPA for 14 to 16 h following activation significantly increased the rate of blastocyst formation of porcine SCNT embryos constructed from Landrace fetal fibroblast cells compared to the control (31.8 vs. 11.4%). However, we found that the acetylation level of Histone H3 lysine 14 and Histone H4 lysine 5 and expression level of Oct4, Sox2, and Klf4 was not significantly changed between VPA-treated and -untreated groups at the blastocyst stage. The SCNT embryos were transferred to 38 surrogates, and the cloning efficiency in the treated group was significantly improved compared with the control group. Taken together, we have demonstrated that VPA can improve both in vitro and in vivo development competence of porcine SCNT embryos.

  10. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper

  11. Communication: Proper treatment of classically forbidden electronic transitions significantly improves detailed balance in surface hopping

    Energy Technology Data Exchange (ETDEWEB)

    Sifain, Andrew E. [Department of Physics and Astronomy, University of Southern California, Los Angeles, California 90089-0485 (United States); Wang, Linjun [Department of Chemistry, Zhejiang University, Hangzhou 310027 (China); Prezhdo, Oleg V. [Department of Physics and Astronomy, University of Southern California, Los Angeles, California 90089-0485 (United States); Department of Chemistry, University of Southern California, Los Angeles, California 90089-1062 (United States)

    2016-06-07

    Surface hopping is the most popular method for nonadiabatic molecular dynamics. Many have reported that it does not rigorously attain detailed balance at thermal equilibrium, but does so approximately. We show that convergence to the Boltzmann populations is significantly improved when the nuclear velocity is reversed after a classically forbidden hop. The proposed prescription significantly reduces the total number of classically forbidden hops encountered along a trajectory, suggesting that some randomization in nuclear velocity is needed when classically forbidden hops constitute a large fraction of attempted hops. Our results are verified computationally using two- and three-level quantum subsystems, coupled to a classical bath undergoing Langevin dynamics.

  12. An integrated PRA module for fast determination of risk significance and improvement effectiveness

    International Nuclear Information System (INIS)

    Chao, Chun-Chang; Lin, Jyh-Der

    2004-01-01

    With the widely use of PRA technology in risk-informed applications, to predict the changes of CDF and LERF becomes a standard process for risk-informed applications. This paper describes an integrated PRA module prepared for risk-informed applications. The module contains a super risk engine, a super fault tree engine, an advanced PRA model and a tool for data base maintenance. The individual element of the module also works well for purpose other than risk-informed applications. The module has been verified and validated through a series of scrupulous benchmark tests with similar software. The results of the benchmark tests showed that the module has remarkable accuracy and speed even for an extremely large-size top-logic fault tree as well as for the case in which large amount of MCSs may be generated. The risk monitor for nuclear power plants in Taiwan is the first application to adopt the module. The results predicted by the risk monitor are now accepted by the regulatory agency. A tool to determine the risk significance according to the inspection findings will be the next application to adopt the module in the near future. This tool classified the risk significance into four different color codes according to the level of increase on CDF. Experience of application showed that the flexibility, the accuracy and speed of the module make it useful in any risk-informed applications when risk indexes must be determined by resolving a PRA model. (author)

  13. Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

    Directory of Open Access Journals (Sweden)

    Sers Christine T

    2010-12-01

    Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

  14. The challenges of ESRD care in developing economies: sub-Saharan African opportunities for significant improvement.

    Science.gov (United States)

    Bamgboye, Ebun Ladipo

    Chronic kidney disease (CKD) is a significant cause of morbidity and mortality in sub-Saharan Africa. This, along with other noncommunicable diseases like hypertension, diabetes, and heart diseases, poses a double burden on a region that is still struggling to cope with the scourge of communicable diseases like malaria, tuberculosis, HIV, and more recently Ebola. Causes of CKD in the region are predominantly glomerulonephritis and hypertension, although type 2 diabetes is also becoming a significant cause as is the retroviral disease. Patients are generally younger than in the developed world, and there is a significant male preponderance. Most patients are managed by hemodialysis, with peritoneal dialysis and kidney transplantation being available in only few countries in the region. Government funding and support for dialysis is often unavailable, and when available, often with restrictions. There is a dearth of trained manpower to treat the disease, and many countries have a limited number of units, which are often ill-equipped to deal adequately with the number of patients who require end-stage renal disease (ESRD) care in the region. Although there has been a significant improvement when compared with the situation, even as recently as 10 years ago, there is also the potential for further improvement, which would significantly improve the outcomes in patients with ESRD in the region. The information in this review was obtained from a combination of renal registry reports (published and unpublished), published articles, responses to a questionnaire sent to nephrologists prior to the World Congress of Nephrology (WCN) in Cape Town, and from nephrologists attending the WCN in Cape Town (March 13 - 17, 2015).

  15. 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.

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

    Science.gov (United States)

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

    2014-07-01

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

  17. 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. Significant Improvements in Pyranometer Nighttime Offsets Using High-Flow DC Ventilation

    Energy Technology Data Exchange (ETDEWEB)

    Kutchenreiter, Mark; Michalski, J.J.; Long, C.N.; Habte, Aron

    2017-05-22

    Accurate solar radiation measurements using pyranometers are required to understand radiative impacts on the Earth's energy budget, solar energy production, and to validate radiative transfer models. Ventilators of pyranometers, which are used to keep the domes clean and dry, also affect instrument thermal offset accuracy. This poster presents a high-level overview of the ventilators for single-black-detector pyranometers and black-and-white pyranometers. For single-black-detector pyranometers with ventilators, high-flow-rate (50-CFM and higher), 12-V DC fans lower the offsets, lower the scatter, and improve the predictability of nighttime offsets compared to lower-flow-rate (35-CFM), 120-V AC fans operated in the same type of environmental setup. Black-and-white pyranometers, which are used to measure diffuse horizontal irradiance, sometimes show minor improvement with DC fan ventilation, but their offsets are always small, usually no more than 1 W/m2, whether AC- or DC-ventilated.

  19. Significant increase of Echinococcus multilocularis prevalencein foxes, but no increased predicted risk for humans

    NARCIS (Netherlands)

    Maas, M.; Dam-Deisz, W.D.C.; Roon, van A.M.; Takumi, K.; Giessen, van der J.W.B.

    2014-01-01

    The emergence of the zoonotic tapeworm Echinococcus multilocularis, causative agent ofalveolar echinococcosis (AE), poses a public health risk. A previously designed risk mapmodel predicted a spread of E. multilocularis and increasing numbers of alveolar echinococ-cosis patients in the province of

  20. The significance of parenchymal changes of acute cellular rejection in predicting chronic liver graft rejection

    NARCIS (Netherlands)

    Gouw, ASH; van den Heuvel, MC; van den Berg, AP; Slooff, NJH; de Jong, KP; Poppema, S

    2002-01-01

    Background. Chronic rejection (CR) in liver allografts shows a rapid onset and progressive course, leading to graft failure within the first year after transplantation. Most cases are preceded by episodes of acute cellular rejection (AR), but histological features predictive for the transition

  1. 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.

  2. 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.

  3. PXD101 significantly improves nuclear reprogramming and the in vitro developmental competence of porcine SCNT embryos

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Jun-Xue; Kang, Jin-Dan; Li, Suo; Jin, Long; Zhu, Hai-Ying; Guo, Qing; Gao, Qing-Shan; Yan, Chang-Guo; Yin, Xi-Jun, E-mail: yinxj33@msn.com

    2015-01-02

    Highlights: • First explored that the effects of PXD101 on the development of SCNT embryos in vitro. • 0.5 μM PXD101 treated for 24 h improved the development of porcine SCNT embryos. • Level of AcH3K9 was significantly higher than control group at early stages. - Abstract: In this study, we investigated the effects of the histone deacetylase inhibitor PXD101 (belinostat) on the preimplantation development of porcine somatic cell nuclear transfer (SCNT) embryos and their expression of the epigenetic markers histone H3 acetylated at lysine 9 (AcH3K9). We compared the in vitro developmental competence of SCNT embryos treated with various concentrations of PXD101 for 24 h. Treatment with 0.5 μM PXD101 significantly increased the proportion of SCNT embryos that reached the blastocyst stage, in comparison to the control group (23.3% vs. 11.5%, P < 0.05). We tested the in vitro developmental competence of SCNT embryos treated with 0.5 μM PXD101 for various amounts of times following activation. Treatment for 24 h significantly improved the development of porcine SCNT embryos, with a significantly higher proportion of embryos reaching the blastocyst stage in comparison to the control group (25.7% vs. 10.6%, P < 0.05). PXD101-treated SCNT embryos were transferred into two surrogate sows, one of whom became pregnant and four fetuses developed. PXD101 treatment significantly increased the fluorescence intensity of immunostaining for AcH3K9 in embryos at the pseudo-pronuclear and 2-cell stages. At these stages, the fluorescence intensities of immunostaining for AcH3K9 were significantly higher in PXD101-treated embryos than in control untreated embryos. In conclusion, this study demonstrates that PXD101 can significantly improve the in vitro and in vivo developmental competence of porcine SCNT embryos and can enhance their nuclear reprogramming.

  4. 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....

  5. 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

  6. 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

  7. Unified Health Gamification can significantly improve well-being in corporate environments.

    Science.gov (United States)

    Shahrestani, Arash; Van Gorp, Pieter; Le Blanc, Pascale; Greidanus, Fabrizio; de Groot, Kristel; Leermakers, Jelle

    2017-07-01

    There is a multitude of mHealth applications that aim to solve societal health problems by stimulating specific types of physical activities via gamification. However, physical health activities cover just one of the three World Health Organization (WHO) dimensions of health. This paper introduces the novel notion of Unified Health Gamification (UHG), which covers besides physical health also social and cognitive health and well-being. Instead of rewarding activities in the three WHO dimensions using different mHealth competitions, UHG combines the scores for such activities on unified leaderboards and lets people interact in social circles beyond personal interests. This approach is promising in corporate environments since UHG can connect the employees with intrinsic motivation for physical health with those who have quite different interests. In order to evaluate this approach, we realized an app prototype and we evaluated it in two corporate pilot studies. In total, eighteen pilot users participated voluntarily for six weeks. Half of the participants were recruited from an occupational health setting and the other half from a treatment setting. Our results suggest that the UHG principles are worth more investigation: various positive health effects were found based on a validated survey. The mean mental health improved significantly at one pilot location and at the level of individual pilot participants, multiple other effects were found to be significant: among others, significant mental health improvements were found for 28% of the participants. Most participants intended to use the app beyond the pilot, especially if it would be further developed.

  8. The presence, predictive utility, and clinical significance of body dysmorphic symptoms in women with eating disorders

    Science.gov (United States)

    2013-01-01

    Background Both eating disorders (EDs) and body dysmorphic disorder (BDD) are disorders of body image. This study aimed to assess the presence, predictive utility, and impact of clinical features commonly associated with BDD in women with EDs. Methods Participants recruited from two non-clinical cohorts of women, symptomatic and asymptomatic of EDs, completed a survey on ED (EDE-Q) and BDD (BDDE-SR) psychopathology, psychological distress (K-10), and quality of life (SF-12). Results A strong correlation was observed between the total BDDE-SR and the global EDE-Q scores (r = 0.79, p 0.05) measured appearance checking, reassurance-seeking, camouflaging, comparison-making, and social avoidance. In addition to these behaviors, inspection of sensitivity (Se) and specificity (Sp) revealed that BDDE-SR items measuring preoccupation and dissatisfaction with appearance were most predictive of ED cases (Se and Sp > 0.60). Higher total BDDE-SR scores were associated with greater distress on the K-10 and poorer quality of life on the SF-12 (all p < 0.01). Conclusions Clinical features central to the model of BDD are common in, predictive of, and associated with impairment in women with EDs. Practice implications are that these features be included in the assessment and treatment of EDs. PMID:24999401

  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. Significance of satellite sign and spot sign in predicting hematoma expansion in spontaneous intracerebral hemorrhage.

    Science.gov (United States)

    Yu, Zhiyuan; Zheng, Jun; Ali, Hasan; Guo, Rui; Li, Mou; Wang, Xiaoze; Ma, Lu; Li, Hao; You, Chao

    2017-11-01

    Hematoma expansion is related to poor outcome in spontaneous intracerebral hemorrhage (ICH). Recently, a non-enhanced computed tomography (CT) based finding, termed the 'satellite sign', was reported to be a novel predictor for poor outcome in spontaneous ICH. However, it is still unclear whether the presence of the satellite sign is related to hematoma expansion. Initial computed tomography angiography (CTA) was conducted within 6h after ictus. Satellite sign on non-enhanced CT and spot sign on CTA were detected by two independent reviewers. The sensitivity and specificity of both satellite sign and spot sign were calculated. Receiver-operator analysis was conducted to evaluate their predictive accuracy for hematoma expansion. This study included 153 patients. Satellite sign was detected in 58 (37.91%) patients and spot sign was detected in 38 (24.84%) patients. Among 37 patients with hematoma expansion, 22 (59.46%) had satellite sign and 23 (62.16%) had spot sign. The sensitivity and specificity of satellite sign for prediction of hematoma expansion were 59.46% and 68.97%, respectively. The sensitivity and specificity of spot sign were 62.16% and 87.07%, respectively. The area under the curve (AUC) of satellite sign was 0.642 and the AUC of spot sign was 0.746. (P=0.157) CONCLUSION: Our results suggest that the satellite sign is an independent predictor for hematoma expansion in spontaneous ICH. Although spot sign has the higher predictive accuracy, satellite sign is still an acceptable predictor for hematoma expansion when CTA is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Thermosensitive Hydrogel Mask Significantly Improves Skin Moisture and Skin Tone; Bilateral Clinical Trial

    Directory of Open Access Journals (Sweden)

    Anna Quattrone

    2017-06-01

    Full Text Available Objective: A temperature-sensitive state-changing hydrogel mask was used in this study. Once it comes into contact with the skin and reaches the body temperature, it uniformly and quickly releases the active compounds, which possess moisturizing, anti-oxidant, anti-inflammatory and regenerative properties. Methods: An open label clinical trial was conducted to evaluate the effects of the test product on skin hydration, skin tone and skin ageing. Subjects applied the product to one side of their face and underwent Corneometer® and Chromameter measurements, Visual assessment of facial skin ageing and facial photography. All assessments and Self-Perception Questionnaires (SPQ were performed at baseline, after the first application of the test product and after four applications. Results: After a single treatment we observed an increase in skin moisturisation, an improvement of skin tone/luminosity and a reduction in signs of ageing, all statistically significant. After four applications a further improvement in all measured parameters was recorded. These results were confirmed by the subjects’ own perceptions, as reported in the SPQ both after one and four applications. Conclusion: The hydrogel mask tested in this study is very effective in improving skin hydration, skin radiance and luminosity, in encouraging an even skin tone and in reducing skin pigmentation.

  12. Significance of MPEG-7 textural features for improved mass detection in mammography.

    Science.gov (United States)

    Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

    2006-01-01

    The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

  13. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  14. Carfilzomib significantly improves the progression-free survival of high-risk patients in multiple myeloma.

    Science.gov (United States)

    Avet-Loiseau, Hervé; Fonseca, Rafael; Siegel, David; Dimopoulos, Meletios A; Špička, Ivan; Masszi, Tamás; Hájek, Roman; Rosiñol, Laura; Goranova-Marinova, Vesselina; Mihaylov, Georgi; Maisnar, Vladimír; Mateos, Maria-Victoria; Wang, Michael; Niesvizky, Ruben; Oriol, Albert; Jakubowiak, Andrzej; Minarik, Jiri; Palumbo, Antonio; Bensinger, William; Kukreti, Vishal; Ben-Yehuda, Dina; Stewart, A Keith; Obreja, Mihaela; Moreau, Philippe

    2016-09-01

    The presence of certain high-risk cytogenetic abnormalities, such as translocations (4;14) and (14;16) and deletion (17p), are known to have a negative impact on survival in multiple myeloma (MM). The phase 3 study ASPIRE (N = 792) demonstrated that progression-free survival (PFS) was significantly improved with carfilzomib, lenalidomide, and dexamethasone (KRd), compared with lenalidomide and dexamethasone (Rd) in relapsed MM. This preplanned subgroup analysis of ASPIRE was conducted to evaluate KRd vs Rd by baseline cytogenetics according to fluorescence in situ hybridization. Of 417 patients with known cytogenetic risk status, 100 patients (24%) were categorized with high-risk cytogenetics (KRd, n = 48; Rd, n = 52) and 317 (76%) were categorized with standard-risk cytogenetics (KRd, n = 147; Rd, n = 170). For patients with high-risk cytogenetics, treatment with KRd resulted in a median PFS of 23.1 months, a 9-month improvement relative to treatment with Rd. For patients with standard-risk cytogenetics, treatment with KRd led to a 10-month improvement in median PFS vs Rd. The overall response rates for KRd vs Rd were 79.2% vs 59.6% (high-risk cytogenetics) and 91.2% vs 73.5% (standard-risk cytogenetics); approximately fivefold as many patients with high- or standard-risk cytogenetics achieved a complete response or better with KRd vs Rd (29.2% vs 5.8% and 38.1% vs 6.5%, respectively). KRd improved but did not abrogate the poor prognosis associated with high-risk cytogenetics. This regimen had a favorable benefit-risk profile in patients with relapsed MM, irrespective of cytogenetic risk status, and should be considered a standard of care in these patients. This trial was registered at www.clinicaltrials.gov as #NCT01080391. © 2016 by The American Society of Hematology.

  15. 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.

  16. 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.

  17. Bone Mass and Strength are Significantly Improved in Mice Overexpressing Human WNT16 in Osteocytes.

    Science.gov (United States)

    Alam, Imranul; Reilly, Austin M; Alkhouli, Mohammed; Gerard-O'Riley, Rita L; Kasipathi, Charishma; Oakes, Dana K; Wright, Weston B; Acton, Dena; McQueen, Amie K; Patel, Bhavmik; Lim, Kyung-Eun; Robling, Alexander G; Econs, Michael J

    2017-04-01

    Recently, we demonstrated that osteoblast-specific overexpression of human WNT16 increased both cortical and trabecular bone mass and structure in mice. To further identify the cell-specific role of Wnt16 in bone homeostasis, we created transgenic (TG) mice overexpressing human WNT16 in osteocytes using Dmp1 promoter (Dmp1-hWNT16 TG) on C57BL/6 (B6) background. We analyzed bone phenotypes and serum bone biomarkers, performed gene expression analysis and measured dynamic bone histomorphometry in Dmp1-hWNT16 TG and wild-type (WT) mice. Compared to WT mice, Dmp1-hWNT16 TG mice exhibited significantly higher whole-body, spine and femoral aBMD, BMC and trabecular (BV/TV, Tb.N, and Tb.Th) and cortical (bone area and thickness) parameters in both male and female at 12 weeks of age. Femur stiffness and ultimate force were also significantly improved in the Dmp1-hWNT16 TG female mice, compared to sex-matched WT littermates. In addition, female Dmp1-hWNT16 TG mice displayed significantly higher MS/BS, MAR and BFR/BS compared to the WT mice. Gene expression analysis demonstrated significantly higher mRNA level of Alp in both male and female Dmp1-hWNT16 TG mice and significantly higher levels of Osteocalcin, Opg and Rankl in the male Dmp1-hWNT16 TG mice in bone tissue compared to sex-matched WT mice. These results indicate that WNT16 plays a critical role for acquisition of both cortical and trabecular bone mass and strength. Strategies designed to use WNT16 as a target for therapeutic interventions will be valuable to treat osteoporosis and other low bone mass conditions.

  18. Radiotherapy is associated with significant improvement in local and regional control in Merkel cell carcinoma

    International Nuclear Information System (INIS)

    Kang, Susan H; Haydu, Lauren E; Goh, Robin Yeong Hong; Fogarty, Gerald B

    2012-01-01

    Merkel cell carcinoma (MCC) is a rare tumour of skin. This study is a retrospective audit of patients with MCC from St Vincent’s and Mater Hospital, Sydney, Australia. The aim of this study was to investigate the influence of radiotherapy (RT) on the local and regional control of MCC lesions and survival of patients with MCC. The data bases in anatomical pathology, RT and surgery. We searched for patients having a diagnosis of MCC between 1996 and 2007. Patient, tumour and treatment characteristics were collected and analysed. Univariate survival analysis of categorical variables was conducted with the Kaplan-Meier method together with the Log-Rank test for statistical significance. Continuous variables were assessed using the Cox regression method. Multivariate analysis was performed for significant univariate results. Sixty seven patients were found. Sixty two who were stage I-III and were treated with radical intent were analysed. 68% were male. The median age was 74 years. Forty-two cases (68%) were stage I or II, and 20 cases (32%) were stage III. For the subset of 42 stage I and II patients, those that had RT to their primary site had a 2-year local recurrence free survival of 89% compared with 36% for patients not receiving RT (p<0.001). The cumulative 2-year regional recurrence free survival for patients having adjuvant regional RT was 84% compared with 43% for patients not receiving this treatment (p<0.001). Immune status at initial surgery was a significant predictor for OS and MCCSS. In a multivariate analysis combining macroscopic size (mm) and immune status at initial surgery, only immune status remained a significant predictor of overall survival (HR=2.096, 95% CI: 1.002-4.385, p=0.049). RT is associated with significant improvement in local and regional control in Merkel cell carcinoma. Immunosuppression is an important factor in overall survival

  19. Use of data mining to predict significant factors and benefits of bilateral cochlear implantation.

    Science.gov (United States)

    Ramos-Miguel, Angel; Perez-Zaballos, Teresa; Perez, Daniel; Falconb, Juan Carlos; Ramosb, Angel

    2015-11-01

    Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90%. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70% benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.

  20. 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.

  1. Significant Improvement of Organic Thin-Film Transistor Mobility Utilizing an Organic Heterojunction Buffer Layer

    International Nuclear Information System (INIS)

    Pan Feng; Qian Xian-Rui; Huang Li-Zhen; Wang Hai-Bo; Yan Dong-Hang

    2011-01-01

    High-mobility vanadyl phthalocyanine (VOPc)/5,5‴-bis(4-fluorophenyl)-2,2':5',2″:5″,2‴-quaterthiophene (F2-P4T) thin-film transistors are demonstrated by employing a copper hexadecafluorophthalocyanine (F 16 CuPc)/copper phthalocyanine (CuPc) heterojunction unit, which are fabricated at different substrate temperatures, as a buffer layer. The highest mobility of 4.08cm 2 /Vs is achieved using a F 16 CuPc/CuPc organic heterojunction buffer layer fabricated at high substrate temperature. Compared with the random small grain-like morphology of the room-temperature buffer layer, the high-temperature organic heterojunction presents a large-sized fiber-like film morphology, resulting in an enhanced conductivity. Thus the contact resistance of the transistor is significantly reduced and an obvious improvement in device mobility is obtained. (cross-disciplinary physics and related areas of science and technology)

  2. Significant improvement of optical traps by tuning standard water immersion objectives

    International Nuclear Information System (INIS)

    Reihani, S Nader S; Mir, Shahid A; Richardson, Andrew C; Oddershede, Lene B

    2011-01-01

    Focused infrared lasers are widely used for micromanipulation and visualization of biological specimens. An inherent practical problem is that off-the-shelf commercial microscope objectives are designed for use with visible and not infrared wavelengths. Less aberration is introduced by water immersion objectives than by oil immersion ones, however, even water immersion objectives induce significant aberration. We present a simple method to reduce the spherical aberration induced by water immersion objectives, namely by tuning the correction collar of the objective to a value that is ∼ 10% lower than the physical thickness of the coverslip. This results in marked improvements in optical trapping strengths of up to 100% laterally and 600% axially from a standard microscope objective designed for use in the visible range. The results are generally valid for any water immersion objective with any numerical aperture

  3. 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.

  4. Significant improvement in the electrical characteristics of Schottky barrier diodes on molecularly modified Gallium Nitride surfaces

    Science.gov (United States)

    Garg, Manjari; Naik, Tejas R.; Pathak, C. S.; Nagarajan, S.; Rao, V. Ramgopal; Singh, R.

    2018-04-01

    III-Nitride semiconductors face the issue of localized surface states, which causes fermi level pinning and large leakage current at the metal semiconductor interface, thereby degrading the device performance. In this work, we have demonstrated the use of a Self-Assembled Monolayer (SAM) of organic molecules to improve the electrical characteristics of Schottky barrier diodes (SBDs) on n-type Gallium Nitride (n-GaN) epitaxial films. The electrical characteristics of diodes were improved by adsorption of SAM of hydroxyl-phenyl metallated porphyrin organic molecules (Zn-TPPOH) onto the surface of n-GaN. SAM-semiconductor bonding via native oxide on the n-GaN surface was confirmed using X-ray photoelectron spectroscopy measurements. Surface morphology and surface electronic properties were characterized using atomic force microscopy and Kelvin probe force microscopy. Current-voltage characteristics of different metal (Cu, Ni) SBDs on bare n-GaN were compared with those of Cu/Zn-TPPOH/n-GaN and Ni/Zn-TPPOH/n-GaN SBDs. It was found that due to the molecular monolayer, the surface potential of n-GaN was decreased by ˜350 mV. This caused an increase in the Schottky barrier height of Cu and Ni SBDs from 1.13 eV to 1.38 eV and 1.07 eV to 1.22 eV, respectively. In addition to this, the reverse bias leakage current was reduced by 3-4 orders of magnitude for both Cu and Ni SBDs. Such a significant improvement in the electrical performance of the diodes can be very useful for better device functioning.

  5. pEPito: a significantly improved non-viral episomal expression vector for mammalian cells

    Directory of Open Access Journals (Sweden)

    Ogris Manfred

    2010-03-01

    Full Text Available Abstract Background The episomal replication of the prototype vector pEPI-1 depends on a transcription unit starting from the constitutively expressed Cytomegalovirus immediate early promoter (CMV-IEP and directed into a 2000 bp long matrix attachment region sequence (MARS derived from the human β-interferon gene. The original pEPI-1 vector contains two mammalian transcription units and a total of 305 CpG islands, which are located predominantly within the vector elements necessary for bacterial propagation and known to be counterproductive for persistent long-term transgene expression. Results Here, we report the development of a novel vector pEPito, which is derived from the pEPI-1 plasmid replicon but has considerably improved efficacy both in vitro and in vivo. The pEPito vector is significantly reduced in size, contains only one transcription unit and 60% less CpG motives in comparison to pEPI-1. It exhibits major advantages compared to the original pEPI-1 plasmid, including higher transgene expression levels and increased colony-forming efficiencies in vitro, as well as more persistent transgene expression profiles in vivo. The performance of pEPito-based vectors was further improved by replacing the CMV-IEP with the human CMV enhancer/human elongation factor 1 alpha promoter (hCMV/EF1P element that is known to be less affected by epigenetic silencing events. Conclusions The novel vector pEPito can be considered suitable as an improved vector for biotechnological applications in vitro and for non-viral gene delivery in vivo.

  6. Electronic monitoring in combination with direct observation as a means to significantly improve hand hygiene compliance.

    Science.gov (United States)

    Boyce, John M

    2017-05-01

    Monitoring hand hygiene compliance among health care personnel (HCP) is an essential element of hand hygiene promotion programs. Observation by trained auditors is considered the gold standard method for establishing hand hygiene compliance rates. Advantages of observational surveys include the unique ability to establish compliance with all of the World Health Organization "My 5 Moments for Hand Hygiene" initiative Moments and to provide just-in-time coaching. Disadvantages include the resources required for observational surveys, insufficient sample sizes, and nonstandardized methods of conducting observations. Electronic and camera-based systems can monitor hand hygiene performance on all work shifts without a Hawthorne effect and provide significantly more data regarding hand hygiene performance. Disadvantages include the cost of installation, variable accuracy in estimating compliance rates, issues related to acceptance by HCP, insufficient data regarding their cost-effectiveness and influence on health care-related infection rates, and the ability of most systems to monitor only surrogates for Moments 1, 4, and 5. Increasing evidence suggests that monitoring only Moments 1, 4, and 5 provides reasonable estimates of compliance with all 5 Moments. With continued improvement of electronic monitoring systems, combining electronic monitoring with observational methods may provide the best information as part of a multimodal strategy to improve and sustain hand hygiene compliance rates among HCP. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

  7. An On-Chip RBC Deformability Checker Significantly Improves Velocity-Deformation Correlation

    Directory of Open Access Journals (Sweden)

    Chia-Hung Dylan Tsai

    2016-10-01

    Full Text Available An on-chip deformability checker is proposed to improve the velocity–deformation correlation for red blood cell (RBC evaluation. RBC deformability has been found related to human diseases, and can be evaluated based on RBC velocity through a microfluidic constriction as in conventional approaches. The correlation between transit velocity and amount of deformation provides statistical information of RBC deformability. However, such correlations are usually only moderate, or even weak, in practical evaluations due to limited range of RBC deformation. To solve this issue, we implemented three constrictions of different width in the proposed checker, so that three different deformation regions can be applied to RBCs. By considering cell responses from the three regions as a whole, we practically extend the range of cell deformation in the evaluation, and could resolve the issue about the limited range of RBC deformation. RBCs from five volunteer subjects were tested using the proposed checker. The results show that the correlation between cell deformation and transit velocity is significantly improved by the proposed deformability checker. The absolute values of the correlation coefficients are increased from an average of 0.54 to 0.92. The effects of cell size, shape and orientation to the evaluation are discussed according to the experimental results. The proposed checker is expected to be useful for RBC evaluation in medical practices.

  8. Significance of collateral vessels on the prediction of superior vena cava syndrome on CT

    International Nuclear Information System (INIS)

    Kim, Hyun Sook; Kim, Hyung Jin; Lee, Hyeng Gon; Ahn, In Oak; Chung, Sung Hoon

    1993-01-01

    Although visible collateral vessels on computed tomography (CT) has been considered as an important finding in superior vena cava (SVC) syndrome, there is no systematical analysis concerning correlation between the CT evidence of collateral vessels and clinical evidence of SVC syndrome. The purpose of this study is to evaluate how accurately we predict the clinical presence of SVC syndrome by the collateral vessels in patients with apparent SVC obstruction in CT. Forty seven patients having a CT evidence of obstruction or compression of SVC and/or its major tributaries were included in this study. Lung cancer was the most common underlying disease (n=40). The enhanced CT scans were obtained through either arm vein using a combined bolus and drip-infusion technique. Analyzing the CT scans, we particularly paid attention to the site and pattern of venous compromise, presence of collateral vessels, and if present, their location, without knowing whether symptoms and sign were present or nor, and then compared them with clinical data by a thorough review of charts, To verify the frequency of visible collateral vessels in normal subjects, we also evaluated the CT scans of 50 patients without mediastinal disease and clinical SVC syndrome as a control group. On CT, collateral vessels were found in 24 patients, among whom three patient had a single collateral and 21 patients had two or more collateral channels. There were two false positive cases, in which clinically overt SVC syndrome appeared 10 days and three months after CT examination respectively, and one false negative case. The presence of collateral vessels on CT, respectively, and one false negative case. The presence of collateral vessels on CT, regardless of the number and location of collateral vessels and pattern of venous obstruction, was a good clue for predicting the presence of clinical SVC syndrome with the sensitivity and the specificity of 95.7% and 91.7%, respectively. In control group, collateral

  9. 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.

  10. Patient-specific metrics of invasiveness reveal significant prognostic benefit of resection in a predictable subset of gliomas.

    Directory of Open Access Journals (Sweden)

    Anne L Baldock

    Full Text Available Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas.In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient's tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness.We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532 from gross total resection over subtotal/biopsy, while those with nodular (less diffuse tumors showed a significant benefit (P = 0.00142 with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors.These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection.

  11. Fabrication of CoZn alloy nanowire arrays: Significant improvement in magnetic properties by annealing process

    International Nuclear Information System (INIS)

    Koohbor, M.; Soltanian, S.; Najafi, M.; Servati, P.

    2012-01-01

    Highlights: ► Increasing the Zn concentration changes the structure of NWs from hcp to amorphous. ► Increasing the Zn concentration significantly reduces the Hc value of NWs. ► Magnetic properties of CoZn NWs can be significantly enhanced by appropriate annealing. ► The pH of electrolyte has no significant effect on the properties of the NW arrays. ► Deposition frequency has considerable effects on the magnetic properties of NWs. - Abstract: Highly ordered arrays of Co 1−x Zn x (0 ≤ x ≤ 0.74) nanowires (NWs) with diameters of ∼35 nm and high length-to-diameter ratios (up to 150) were fabricated by co-electrodeposition of Co and Zn into pores of anodized aluminum oxide (AAO) templates. The Co and Zn contents of the NWs were adjusted by varying the ratio of Zn and Co ion concentrations in the electrolyte. The effect of the Zn content, electrodeposition conditions (frequency and pH) and annealing on the structural and magnetic properties (e.g., coercivity (Hc) and squareness (Sq)) of NW arrays were investigated using X-ray diffraction (XRD), scanning electron microscopy, electron diffraction, and alternating gradient force magnetometer (AGFM). XRD patterns reveal that an increase in the concentration of Zn ions of the electrolyte forces the hcp crystal structure of Co NWs to change into an amorphous phase, resulting in a significant reduction in Hc. It was found that the magnetic properties of NWs can be significantly improved by appropriate annealing process. The highest values for Hc (2050 Oe) and Sq (0.98) were obtained for NWs electrodeposited using 0.95/0.05 Co:Zn concentrations at 200 Hz and annealed at 575 °C. While the pH of electrolyte is found to have no significant effect on the structural and magnetic properties of the NW arrays, the electrodeposition frequency has considerable effects on the magnetic properties of the NW arrays. The changes in magnetic property of NWs are rooted in a competition between shape anisotropy and

  12. Fabrication of CoZn alloy nanowire arrays: Significant improvement in magnetic properties by annealing process

    Energy Technology Data Exchange (ETDEWEB)

    Koohbor, M. [Department of Physics, University of Kurdistan, Sanandaj (Iran, Islamic Republic of); Soltanian, S., E-mail: s.soltanian@gmail.com [Department of Physics, University of Kurdistan, Sanandaj (Iran, Islamic Republic of); Department of Electrical and Computer Engineering, University of British Columbia, Vancouver (Canada); Najafi, M. [Department of Physics, University of Kurdistan, Sanandaj (Iran, Islamic Republic of); Department of Physics, Hamadan University of Technology, Hamadan (Iran, Islamic Republic of); Servati, P. [Department of Electrical and Computer Engineering, University of British Columbia, Vancouver (Canada)

    2012-01-05

    Highlights: Black-Right-Pointing-Pointer Increasing the Zn concentration changes the structure of NWs from hcp to amorphous. Black-Right-Pointing-Pointer Increasing the Zn concentration significantly reduces the Hc value of NWs. Black-Right-Pointing-Pointer Magnetic properties of CoZn NWs can be significantly enhanced by appropriate annealing. Black-Right-Pointing-Pointer The pH of electrolyte has no significant effect on the properties of the NW arrays. Black-Right-Pointing-Pointer Deposition frequency has considerable effects on the magnetic properties of NWs. - Abstract: Highly ordered arrays of Co{sub 1-x}Zn{sub x} (0 {<=} x {<=} 0.74) nanowires (NWs) with diameters of {approx}35 nm and high length-to-diameter ratios (up to 150) were fabricated by co-electrodeposition of Co and Zn into pores of anodized aluminum oxide (AAO) templates. The Co and Zn contents of the NWs were adjusted by varying the ratio of Zn and Co ion concentrations in the electrolyte. The effect of the Zn content, electrodeposition conditions (frequency and pH) and annealing on the structural and magnetic properties (e.g., coercivity (Hc) and squareness (Sq)) of NW arrays were investigated using X-ray diffraction (XRD), scanning electron microscopy, electron diffraction, and alternating gradient force magnetometer (AGFM). XRD patterns reveal that an increase in the concentration of Zn ions of the electrolyte forces the hcp crystal structure of Co NWs to change into an amorphous phase, resulting in a significant reduction in Hc. It was found that the magnetic properties of NWs can be significantly improved by appropriate annealing process. The highest values for Hc (2050 Oe) and Sq (0.98) were obtained for NWs electrodeposited using 0.95/0.05 Co:Zn concentrations at 200 Hz and annealed at 575 Degree-Sign C. While the pH of electrolyte is found to have no significant effect on the structural and magnetic properties of the NW arrays, the electrodeposition frequency has considerable effects on

  13. Compression stockings significantly improve hemodynamic performance in post-thrombotic syndrome irrespective of class or length.

    Science.gov (United States)

    Lattimer, Christopher R; Azzam, Mustapha; Kalodiki, Evi; Makris, Gregory C; Geroulakos, George

    2013-07-01

    Graduated elastic compression (GEC) stockings have been demonstrated to reduce the morbidity associated with post-thrombotic syndrome. The ideal length or compression strength required to achieve this is speculative and related to physician preference and patient compliance. The aim of this study was to evaluate the hemodynamic performance of four different stockings and determine the patient's preference. Thirty-four consecutive patients (40 legs, 34 male) with post-thrombotic syndrome were tested with four different stockings (Mediven plus open toe, Bayreuth, Germany) of their size in random order: class 1 (18-21 mm Hg) and class II (23-32 mm Hg), below-knee (BK) and above-knee thigh-length (AK). The median age, Venous Clinical Severity Score, Venous Segmental Disease Score, and Villalta scale were 62 years (range, 31-81 years), 8 (range, 1-21), 5 (range, 2-10), and 10 (range, 2-22), respectively. The C of C0-6EsAs,d,pPr,o was C0 = 2, C2 = 1, C3 = 3, C4a = 12, C4b = 7, C5 = 12, C6 = 3. Obstruction and reflux was observed on duplex in 47.5% legs, with deep venous reflux alone in 45%. Air plethysmography was used to measure the venous filling index (VFI), venous volume, and time to fill 90% of the venous volume. Direct pressure measurements were obtained while lying and standing using the PicoPress device (Microlab Elettronica, Nicolò, Italy). The pressure sensor was placed underneath the test stocking 5 cm above and 2 cm posterior to the medial malleolus. At the end of the study session, patients stated their preferred stocking based on comfort. The VFI, venous volume, and time to fill 90% of the venous volume improved significantly with all types of stocking versus no compression. In class I, the VFI (mL/s) improved from a median of 4.9 (range, 1.7-16.3) without compression to 3.7 (range, 0-14) BK (24.5%) and 3.6 (range, 0.6-14.5) AK (26.5%). With class II, the corresponding improvement was to 4.0 (range, 0.3-16.2) BK (18.8%) and 3.7 (range, 0.5-14.2) AK (24

  14. Significant improvement of intestinal microbiota of gibel carp (Carassius auratus gibelio) after traditional Chinese medicine feeding.

    Science.gov (United States)

    Wu, Z B; Gatesoupe, F-J; Li, T T; Wang, X H; Zhang, Q Q; Feng, D Y; Feng, Y Q; Chen, H; Li, A H

    2018-03-01

    Increasing attention has been attracted to intestinal microbiota, due to interactions with nutrition, metabolism and immune defence of the host. Traditional Chinese medicine (TCM) feed additives have been applied in aquaculture to improve fish health, but the interaction with fish gut microbiota is still poorly understood. This study aimed to explore the effect of adding TCM in feed on the intestinal microbiota of gibel carp (Carassius auratus gibelio). Bacterial communities of 16 fish intestinal contents and one water sample were characterized by high-throughput sequencing and analysis of the V4-V5 region of the 16S rRNA gene. The results showed that the composition and structure of the bacterial community were significantly altered by the TCM feeding. Some phyla increased markedly (Proteobacteria, Actinobacteria, Acidobacteria, etc.), while Fusobacteria were significantly reduced. Concurrently, the richness and diversity of the taxonomic units increased, and the microbiota composition of TCM-treated fish was more homogeneous among individuals. At the genus level, the addition of TCM tended to reduce the incidence of potential pathogens (Aeromonas, Acinetobacter and Shewanella), while stimulating the emergence of some potential probiotics (Lactobacillus, Lactococcus, Bacillus and Pseudomonas). These data suggested that the feed additive could regulate the fish intestinal microbiota by reinforcing the microbial balance. This study may provide useful information for further application of TCM for diseases prevention and stress management in aquaculture. © 2017 The Society for Applied Microbiology.

  15. Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography

    Science.gov (United States)

    Boudria, Yacine; Feltane, Amal; Besio, Walter

    2014-06-01

    Objective. Brain-computer interfaces (BCIs) based on electroencephalography (EEG) have been shown to accurately detect mental activities, but the acquisition of high levels of control require extensive user training. Furthermore, EEG has low signal-to-noise ratio and low spatial resolution. The objective of the present study was to compare the accuracy between two types of BCIs during the first recording session. EEG and tripolar concentric ring electrode (TCRE) EEG (tEEG) brain signals were recorded and used to control one-dimensional cursor movements. Approach. Eight human subjects were asked to imagine either ‘left’ or ‘right’ hand movement during one recording session to control the computer cursor using TCRE and disc electrodes. Main results. The obtained results show a significant improvement in accuracies using TCREs (44%-100%) compared to disc electrodes (30%-86%). Significance. This study developed the first tEEG-based BCI system for real-time one-dimensional cursor movements and showed high accuracies with little training.

  16. Induction-heating MOCVD reactor with significantly improved heating efficiency and reduced harmful magnetic coupling

    KAUST Repository

    Li, Kuang-Hui; Alotaibi, Hamad S.; Sun, Haiding; Lin, Ronghui; Guo, Wenzhe; Torres-Castanedo, Carlos G.; Liu, Kaikai; Galan, Sergio V.; Li, Xiaohang

    2018-01-01

    In a conventional induction-heating III-nitride metalorganic chemical vapor deposition (MOCVD) reactor, the induction coil is outside the chamber. Therefore, the magnetic field does not couple with the susceptor well, leading to compromised heating efficiency and harmful coupling with the gas inlet and thus possible overheating. Hence, the gas inlet has to be at a minimum distance away from the susceptor. Because of the elongated flow path, premature reactions can be more severe, particularly between Al- and B-containing precursors and NH3. Here, we propose a structure that can significantly improve the heating efficiency and allow the gas inlet to be closer to the susceptor. Specifically, the induction coil is designed to surround the vertical cylinder of a T-shaped susceptor comprising the cylinder and a top horizontal plate holding the wafer substrate within the reactor. Therefore, the cylinder coupled most magnetic field to serve as the thermal source for the plate. Furthermore, the plate can block and thus significantly reduce the uncoupled magnetic field above the susceptor, thereby allowing the gas inlet to be closer. The results show approximately 140% and 2.6 times increase in the heating and susceptor coupling efficiencies, respectively, as well as a 90% reduction in the harmful magnetic flux on the gas inlet.

  17. Induction-heating MOCVD reactor with significantly improved heating efficiency and reduced harmful magnetic coupling

    KAUST Repository

    Li, Kuang-Hui

    2018-02-23

    In a conventional induction-heating III-nitride metalorganic chemical vapor deposition (MOCVD) reactor, the induction coil is outside the chamber. Therefore, the magnetic field does not couple with the susceptor well, leading to compromised heating efficiency and harmful coupling with the gas inlet and thus possible overheating. Hence, the gas inlet has to be at a minimum distance away from the susceptor. Because of the elongated flow path, premature reactions can be more severe, particularly between Al- and B-containing precursors and NH3. Here, we propose a structure that can significantly improve the heating efficiency and allow the gas inlet to be closer to the susceptor. Specifically, the induction coil is designed to surround the vertical cylinder of a T-shaped susceptor comprising the cylinder and a top horizontal plate holding the wafer substrate within the reactor. Therefore, the cylinder coupled most magnetic field to serve as the thermal source for the plate. Furthermore, the plate can block and thus significantly reduce the uncoupled magnetic field above the susceptor, thereby allowing the gas inlet to be closer. The results show approximately 140% and 2.6 times increase in the heating and susceptor coupling efficiencies, respectively, as well as a 90% reduction in the harmful magnetic flux on the gas inlet.

  18. 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.

  19. Meta-Analysis of Predictive Significance of the Black Hole Sign for Hematoma Expansion in Intracerebral Hemorrhage.

    Science.gov (United States)

    Zheng, Jun; Yu, Zhiyuan; Guo, Rui; Li, Hao; You, Chao; Ma, Lu

    2018-04-27

    Hematoma expansion is related to unfavorable prognosis in intracerebral hemorrhage (ICH). The black hole sign is a novel marker on non-contrast computed tomography for predicting hematoma expansion. However, its predictive values are different in previous studies. Thus, this meta-analysis was conducted to evaluate the predictive significance of the black hole sign for hematoma expansion in ICH. A systematic literature search was performed. Original researches on the association between the black hole sign and hematoma expansion in ICH were included. Sensitivity and specificity were pooled to assess the predictive accuracy. Summary receiver operating characteristics curve (SROC) was developed. Deeks' funnel plot asymmetry test was used to assess the publication bias. Five studies with a total of 1495 patients were included in this study. The pooled sensitivity and specificity of the black hole sign for predicting hematoma expansion were 0.30 and 0.91, respectively. The area under the curve was 0.78 in SROC curve. There was no significant publication bias. This meta-analysis shows that the black hole sign is a helpful imaging marker for predicting hematoma expansion in ICH. Although the black hole sign has a relatively low sensitivity, its specificity is relatively high. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Improved prediction of aerodynamic noise from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

  1. A new model using routinely available clinical parameters to predict significant liver fibrosis in chronic hepatitis B.

    Directory of Open Access Journals (Sweden)

    Wai-Kay Seto

    Full Text Available OBJECTIVE: We developed a predictive model for significant fibrosis in chronic hepatitis B (CHB based on routinely available clinical parameters. METHODS: 237 treatment-naïve CHB patients [58.4% hepatitis B e antigen (HBeAg-positive] who had undergone liver biopsy were randomly divided into two cohorts: training group (n = 108 and validation group (n = 129. Liver histology was assessed for fibrosis. All common demographics, viral serology, viral load and liver biochemistry were analyzed. RESULTS: Based on 12 available clinical parameters (age, sex, HBeAg status, HBV DNA, platelet, albumin, bilirubin, ALT, AST, ALP, GGT and AFP, a model to predict significant liver fibrosis (Ishak fibrosis score ≥3 was derived using the five best parameters (age, ALP, AST, AFP and platelet. Using the formula log(index+1 = 0.025+0.0031(age+0.1483 log(ALP+0.004 log(AST+0.0908 log(AFP+1-0.028 log(platelet, the PAPAS (Platelet/Age/Phosphatase/AFP/AST index predicts significant fibrosis with an area under the receiving operating characteristics (AUROC curve of 0.776 [0.797 for patients with ALT <2×upper limit of normal (ULN] The negative predictive value to exclude significant fibrosis was 88.4%. This predictive power is superior to other non-invasive models using common parameters, including the AST/platelet/GGT/AFP (APGA index, AST/platelet ratio index (APRI, and the FIB-4 index (AUROC of 0.757, 0.708 and 0.723 respectively. Using the PAPAS index, 67.5% of liver biopsies for patients being considered for treatment with ALT <2×ULN could be avoided. CONCLUSION: The PAPAS index can predict and exclude significant fibrosis, and may reduce the need for liver biopsy in CHB patients.

  2. 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

  3. 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.

  4. Nicotine Significantly Improves Chronic Stress-Induced Impairments of Cognition and Synaptic Plasticity in Mice.

    Science.gov (United States)

    Shang, Xueliang; Shang, Yingchun; Fu, Jingxuan; Zhang, Tao

    2017-08-01

    The aim of this study was to examine if nicotine was able to improve cognition deficits in a mouse model of chronic mild stress. Twenty-four male C57BL/6 mice were divided into three groups: control, stress, and stress with nicotine treatment. The animal model was established by combining chronic unpredictable mild stress (CUMS) and isolated feeding. Mice were exposed to CUMS continued for 28 days, while nicotine (0.2 mg/kg) was also administrated for 28 days. Weight and sucrose consumption were measured during model establishing period. The anxiety and behavioral despair were analyzed using the forced swim test (FST) and open-field test (OFT). Spatial cognition was evaluated using Morris water maze (MWM) test. Following behavioral assessment, both long-term potentiation (LTP) and depotentiation (DEP) were recorded in the hippocampal dentate gyrus (DG) region. Both synaptic and Notch1 proteins were measured by Western. Nicotine increased stressed mouse's sucrose consumption. The MWM test showed that spatial learning and reversal learning in stressed animals were remarkably affected relative to controls, whereas nicotine partially rescued cognitive functions. Additionally, nicotine considerably alleviated the level of anxiety and the degree of behavioral despair in stressed mice. It effectively mitigated the depression-induced impairment of hippocampal synaptic plasticity, in which both the LTP and DEP were significantly inhibited in stressed mice. Moreover, nicotine enhanced the expression of synaptic and Notch1 proteins in stressed animals. The results suggest that nicotine ameliorates the depression-like symptoms and improves the hippocampal synaptic plasticity closely associated with activating transmembrane ion channel receptors and Notch signaling components. Graphical Abstract ᅟ.

  5. Significant improvements in stability and reproducibility of atomic-scale atomic force microscopy in liquid

    International Nuclear Information System (INIS)

    Akrami, S M R; Nakayachi, H; Fukuma, T; Watanabe-Nakayama, T; Asakawa, H

    2014-01-01

    Recent advancement of dynamic-mode atomic force microscopy (AFM) for liquid-environment applications enabled atomic-scale studies on various interfacial phenomena. However, instabilities and poor reproducibility of the measurements often prevent systematic studies. To solve this problem, we have investigated the effect of various tip treatment methods for atomic-scale imaging and force measurements in liquid. The tested methods include Si coating, Ar plasma, Ar sputtering and UV/O 3 cleaning. We found that all the methods provide significant improvements in both the imaging and force measurements in spite of the tip transfer through the air. Among the methods, we found that the Si coating provides the best stability and reproducibility in the measurements. To understand the origin of the fouling resistance of the cleaned tip surface and the difference between the cleaning methods, we have investigated the tip surface properties by x-ray photoelectron spectroscopy and contact angle measurements. The results show that the contaminations adsorbed on the tip during the tip transfer through the air should desorb from the surface when it is immersed in aqueous solution due to the enhanced hydrophilicity by the tip treatments. The tip surface prepared by the Si coating is oxidized when it is immersed in aqueous solution. This creates local spots where stable hydration structures are formed. For the other methods, there is no active mechanism to create such local hydration sites. Thus, the hydration structure formed under the tip apex is not necessarily stable. These results reveal the desirable tip properties for atomic-scale AFM measurements in liquid, which should serve as a guideline for further improvements of the tip treatment methods. (paper)

  6. Significant improvement of accuracy and precision in the determination of trace rare earths by fluorescence analysis

    International Nuclear Information System (INIS)

    Ozawa, L.; Hersh, H.N.

    1976-01-01

    Most of the rare earths in yttrium, gadolinium and lanthanum oxides emit characteristic fluorescent line spectra under irradiation with photons, electrons and x rays. The sensitivity and selectivity of the rare earth fluorescences are high enough to determine the trace amounts (0.01 to 100 ppM) of rare earths. The absolute fluorescent intensities of solids, however, are markedly affected by the synthesis procedure, level of contamination and crystal perfection, resulting in poor accuracy and low precision for the method (larger than 50 percent error). Special care in preparation of the samples is required to obtain good accuracy and precision. It is found that the accuracy and precision for the determination of trace (less than 10 ppM) rare earths by fluorescence analysis improved significantly, while still maintaining the sensitivity, when the determination is made by comparing the ratio of the fluorescent intensities of the trace rare earths to that of a deliberately added rare earth as reference. The variation in the absolute fluorescent intensity remains, but is compensated for by measuring the fluorescent line intensity ratio. Consequently, the determination of trace rare earths (with less than 3 percent error) is easily made by a photoluminescence technique in which the rare earths are excited directly by photons. Accuracy is still maintained when the absolute fluorescent intensity is reduced by 50 percent through contamination by Ni, Fe, Mn or Pb (about 100 ppM). Determination accuracy is also improved for fluorescence analysis by electron excitation and x-ray excitation. For some rare earths, however, accuracy by these techniques is reduced because indirect excitation mechanisms are involved. The excitation mechanisms and the interferences between rare earths are also reported

  7. Single-atom catalysts for CO2 electroreduction with significant activity and selectivity improvements.

    Science.gov (United States)

    Back, Seoin; Lim, Juhyung; Kim, Na-Young; Kim, Yong-Hyun; Jung, Yousung

    2017-02-01

    A single-atom catalyst (SAC) has an electronic structure that is very different from its bulk counterparts, and has shown an unexpectedly high specific activity with a significant reduction in noble metal usage for CO oxidation, fuel cell and hydrogen evolution applications, although physical origins of such performance enhancements are still poorly understood. Herein, by means of density functional theory (DFT) calculations, we for the first time investigate the great potential of single atom catalysts for CO 2 electroreduction applications. In particular, we study a single transition metal atom anchored on defective graphene with single or double vacancies, denoted M@sv-Gr or M@dv-Gr, where M = Ag, Au, Co, Cu, Fe, Ir, Ni, Os, Pd, Pt, Rh or Ru, as a CO 2 reduction catalyst. Many SACs are indeed shown to be highly selective for the CO 2 reduction reaction over a competitive H 2 evolution reaction due to favorable adsorption of carboxyl (*COOH) or formate (*OCHO) over hydrogen (*H) on the catalysts. On the basis of free energy profiles, we identified several promising candidate materials for different products; Ni@dv-Gr (limiting potential U L = -0.41 V) and Pt@dv-Gr (-0.27 V) for CH 3 OH production, and Os@dv-Gr (-0.52 V) and Ru@dv-Gr (-0.52 V) for CH 4 production. In particular, the Pt@dv-Gr catalyst shows remarkable reduction in the limiting potential for CH 3 OH production compared to any existing catalysts, synthesized or predicted. To understand the origin of the activity enhancement of SACs, we find that the lack of an atomic ensemble for adsorbate binding and the unique electronic structure of the single atom catalysts as well as orbital interaction play an important role, contributing to binding energies of SACs that deviate considerably from the conventional scaling relation of bulk transition metals.

  8. Prevalence, significance and predictive value of antiphospholipid antibodies in Crohn’s disease

    Science.gov (United States)

    Sipeki, Nora; Davida, Laszlo; Palyu, Eszter; Altorjay, Istvan; Harsfalvi, Jolan; Antal Szalmas, Peter; Szabo, Zoltan; Veres, Gabor; Shums, Zakera; Norman, Gary L; Lakatos, Peter L; Papp, Maria

    2015-01-01

    AIM: To assess the prevalence and stability of different antiphospholipid antibodies (APLAs) and their association with disease phenotype and progression in inflammatory bowel diseases (IBD) patients. METHODS: About 458 consecutive patients [Crohn’s disease (CD): 271 and ulcerative colitis (UC): 187] were enrolled into a follow-up cohort study in a tertiary IBD referral center in Hungary. Detailed clinical phenotypes were determined at enrollment by reviewing the patients’ medical charts. Disease activity, medical treatment and data about evolvement of complications or surgical interventions were determined prospectively during the follow-up. Disease course (development f complicated disease phenotype and need for surgery), occurrence of thrombotic events, actual state of disease activity according to clinical, laboratory and endoscopic scores and accurate treatment regime were recorded during the follow-up, (median, 57.4 and 61.6 mo for CD and UC). Sera of IBD patients and 103 healthy controls (HC) were tested on individual anti-β2-Glycoprotein-I (anti-β2-GPI IgA/M/G), anti-cardiolipin (ACA IgA/M/G) and anti-phosphatidylserine/prothrombin (anti-PS/PT IgA/M/G) antibodies and also anti-Saccharomyces cerevisiae antibodies (ASCA IgA/G) by enzyme-linked immunosorbent assay (ELISA). In a subgroup of CD (n = 198) and UC patients (n = 103), obtaining consecutive samples over various arbitrary time-points during the disease course, we evaluated the intraindividual stability of the APLA status. Additionally, we provide an overview of studies, performed so far, in which significance of APLAs in IBD were assessed. RESULTS: Patients with CD had significantly higher prevalence of both ACA (23.4%) and anti-PS/PT (20.4%) antibodies than UC (4.8%, P < 0.0001 and 10.2%, P = 0.004) and HC (2.9%, P < 0.0001 and 15.5%, P = NS). No difference was found for the prevalence of anti-β2-GPI between different groups (7.2%-9.7%). In CD, no association was found between APLA and ASCA

  9. Flavonol-rich dark cocoa significantly decreases plasma endothelin-1 and improves cognition in urban children.

    Science.gov (United States)

    Calderón-Garcidueñas, Lilian; Mora-Tiscareño, Antonieta; Franco-Lira, Maricela; Cross, Janet V; Engle, Randall; Aragón-Flores, Mariana; Gómez-Garza, Gilberto; Jewells, Valerie; Medina-Cortina, Humberto; Solorio, Edelmira; Chao, Chih-Kai; Zhu, Hongtu; Mukherjee, Partha S; Ferreira-Azevedo, Lara; Torres-Jardón, Ricardo; D'Angiulli, Amedeo

    2013-01-01

    Air pollution exposures are linked to systemic inflammation, cardiovascular and respiratory morbidity and mortality, neuroinflammation and neuropathology in young urbanites. In particular, most Mexico City Metropolitan Area (MCMA) children exhibit subtle cognitive deficits, and neuropathology studies show 40% of them exhibiting frontal tau hyperphosphorylation and 51% amyloid-β diffuse plaques (compared to 0% in low pollution control children). We assessed whether a short cocoa intervention can be effective in decreasing plasma endothelin 1 (ET-1) and/or inflammatory mediators in MCMA children. Thirty gram of dark cocoa with 680 mg of total flavonols were given daily for 10.11 ± 3.4 days (range 9-24 days) to 18 children (10.55 years, SD = 1.45; 11F/7M). Key metabolite ratios in frontal white matter and in hippocampus pre and during cocoa intervention were quantified by magnetic resonance spectroscopy. ET-1 significantly decreased after cocoa treatment (p = 0.0002). Fifteen children (83%) showed a marginally significant individual improvement in one or both of the applied simple short memory tasks. Endothelial dysfunction is a key feature of exposure to particulate matter (PM) and decreased endothelin-1 bioavailability is likely useful for brain function in the context of air pollution. Our findings suggest that cocoa interventions may be critical for early implementation of neuroprotection of highly exposed urban children. Multi-domain nutraceutical interventions could limit the risk for endothelial dysfunction, cerebral hypoperfusion, neuroinflammation, cognitive deficits, structural volumetric detrimental brain effects, and the early development of the neuropathological hallmarks of Alzheimer's and Parkinson's diseases.

  10. Significantly improving trace thallium removal from surface waters during coagulation enhanced by nanosized manganese dioxide.

    Science.gov (United States)

    Huangfu, Xiaoliu; Ma, Chengxue; Ma, Jun; He, Qiang; Yang, Chun; Jiang, Jin; Wang, Yaan; Wu, Zhengsong

    2017-02-01

    Thallium (Tl) is an element of high toxicity and significant accumulation in human body. There is an urgent need for the development of appropriate strategies for trace Tl removal in drinking water treatment plants. In this study, the efficiency and mechanism of trace Tl (0.5 μg/L) removal by conventional coagulation enhanced by nanosized manganese dioxide (nMnO 2 ) were explored in simulated water and two representative surface waters (a river water and a reservoir water obtained from Northeast China). Experimental results showed that nMnO 2 significantly improve Tl(I) removal from selected waters. The removal efficiency was dramatically higher in the simulated water, demonstrating by less than 0.1 μg/L Tl residual. The enhancement of trace Tl removal in the surface waters decreased to a certain extent. Both adjusting water pH to alkaline condition and preoxidation of Tl(I) to Tl(III) benefit trace Tl removal from surface waters. Data also indicated that competitive cation of Ca 2+ decreased the efficiency of trace Tl removal, resulting from the reduction of Tl adsorption on nMnO 2 . Humic acid could largely low Tl removal efficiency during nMnO 2 enhanced coagulation processes. Trace elemental Tl firstly adsorbed on nMnO 2 and then removed accompanying with nMnO 2 settling. The information obtained in the present study may provide a potential strategy for drinking water treatment plants threatened by trace Tl. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Prediction of significant conduction disease through noninvasive assessment of cardiac calcification.

    Science.gov (United States)

    Mainigi, Sumeet K; Chebrolu, Lakshmi Hima Bindu; Romero-Corral, Abel; Mehta, Vinay; Machado, Rodolfo Rozindo; Konecny, Tomas; Pressman, Gregg S

    2012-10-01

    Cardiac calcification is associated with coronary artery disease, arrhythmias, conduction disease, and adverse cardiac events. Recently, we have described an echocardiographic-based global cardiac calcification scoring system. The objective of this study was to evaluate the severity of cardiac calcification in patients with permanent pacemakers as based on this scoring system. Patients with a pacemaker implanted within the 2-year study period with a previous echocardiogram were identified and underwent blinded global cardiac calcium scoring. These patients were compared to matched control patients without a pacemaker who also underwent calcium scoring. The study group consisted of 49 patients with pacemaker implantation who were compared to 100 matched control patients. The mean calcium score in the pacemaker group was 3.3 ± 2.9 versus 1.8 ± 2.0 (P = 0.006) in the control group. Univariate and multivariate analysis revealed glomerular filtration rate and calcium scoring to be significant predictors of the presence of a pacemaker. Echocardiographic-based calcium scoring correlates with the presence of severe conduction disease requiring a pacemaker. © 2012, Wiley Periodicals, Inc.

  12. Significant effect of Ca2+ on improving the heat resistance of lactic acid bacteria.

    Science.gov (United States)

    Huang, Song; Chen, Xiao Dong

    2013-07-01

    The heat resistance of lactic acid bacteria (LAB) has been extensively investigated due to its highly practical significance. Reconstituted skim milk (RSM) has been found to be one of the most effective protectant wall materials for microencapsulating microorganisms during convective drying, such as spray drying. In addition to proteins and carbohydrate, RSM is rich in calcium. It is not clear which component is critical in the RSM protection mechanism. This study investigated the independent effect of calcium. Ca(2+) was added to lactose solution to examine its influence on the heat resistance of Lactobacillus rhamnosus ZY, Lactobacillus casei Zhang, Lactobacillus plantarum P8 and Streptococcus thermophilus ND03. The results showed that certain Ca(2+) concentrations enhanced the heat resistance of the LAB strains to different extents, that is produced higher survival and shorter regrowth lag times of the bacterial cells. In some cases, the improvements were dramatic. More scientifically insightful and more intensive instrumental study of the Ca(2+) behavior around and in the cells should be carried out in the near future. In the meantime, this work may lead to the development of more cost-effective wall materials with Ca(2+) added as a prime factor. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  13. Targeting Heparin to Collagen within Extracellular Matrix Significantly Reduces Thrombogenicity and Improves Endothelialization of Decellularized Tissues.

    Science.gov (United States)

    Jiang, Bin; Suen, Rachel; Wertheim, Jason A; Ameer, Guillermo A

    2016-12-12

    Thrombosis within small-diameter vascular grafts limits the development of bioartificial, engineered vascular conduits, especially those derived from extracellular matrix (ECM). Here we describe an easy-to-implement strategy to chemically modify vascular ECM by covalently linking a collagen binding peptide (CBP) to heparin to form a heparin derivative (CBP-heparin) that selectively binds a subset of collagens. Modification of ECM with CBP-heparin leads to increased deposition of functional heparin (by ∼7.2-fold measured by glycosaminoglycan composition) and a corresponding reduction in platelet binding (>70%) and whole blood clotting (>80%) onto the ECM. Furthermore, addition of CBP-heparin to the ECM stabilizes long-term endothelial cell attachment to the lumen of ECM-derived vascular conduits, potentially through recruitment of heparin-binding growth factors that ultimately improve the durability of endothelialization in vitro. Overall, our findings provide a simple yet effective method to increase deposition of functional heparin on the surface of ECM-based vascular grafts and thereby minimize thrombogenicity of decellularized tissue, overcoming a significant challenge in tissue engineering of bioartificial vessels and vascularized organs.

  14. Significant Improvement in Chronic Persistent Headaches Caused by Small Rathke Cleft Cysts After Transsphenoidal Surgery.

    Science.gov (United States)

    Fukui, Issei; Hayashi, Yasuhiko; Kita, Daisuke; Sasagawa, Yasuo; Oishi, Masahiro; Tachibana, Osamu; Nakada, Mitsutoshi

    2017-03-01

    Rathke cleft cysts (RCC) usually are asymptomatic and can be observed via the use of conservative methods. Some patients with RCCs, however, have severe headaches even if they are small enough to be confined to the sella, and these small RCCs seldom have been discussed. This study presents an investigation into clinical characteristics of small RCCs associated with severe headaches, demonstrating efficacy and safety of endoscopic transsphenoidal surgery (ETSS) to relieve headaches. In this study, 13 patients with small RCCs (maximum diameter HIT-6) score was calculated both pre- and postoperatively to evaluate headache severity. All patients complained of severe headaches, which disturbed their daily life. Most headaches were nonpulsating and localized in the frontal area. Characteristically, 6 patients (46%) experienced severe headaches with sudden onset that continued chronically. HIT-6 score was 64 on average, meaning headaches affected daily life severely. After surgical decompression of the cyst, headache in all of the patients improved dramatically and HIT-6 score decreased significantly to 37, suggesting that headaches were diminished. No newly developed deficiencies of the anterior pituitary lobe function were detected. Postoperative occurrence of diabetes insipidus was found in 2 patients, both of which were transient. No recurring cysts were found. Severe headaches can develop from small RCCs. In the present study, ETSS was performed on such patients effectively and safely to relieve their headaches. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. New pulmonary vein Doppler echocardiographic index predicts significant interatrial shunting in secundum atrial septal defect.

    Science.gov (United States)

    Lam, Yat-Yin; Fang, Fang; Yip, Gabriel Wai-Kwok; Li, Zhi-An; Yang, Ya; Yu, Cheuk-Man

    2012-09-20

    The relation between pulmonary venous flow (PVF) pattern and degree of left-to-right interatrial shunting (IAS) in patients with secundum atrial septal defect (ASD) is unknown. Fifty consecutive ASD patients (14 males, 36 ± 17 years) received transthoracic echocardiography (TTE) before and 1 day after transcatheter closure and their results were compared to 40 controls. The ratio of pulmonary-to-systemic flows (Qp/Qs) was assessed by TTE and invasive oximetry. Pre-closure PV systolic (PVs), diastolic (PVd) velocities and velocity-time integral (PV-VTI) increased, time from onset of ECG Q-wave to the peak PV diastolic wave (Q-PVd) shortened and atrial reversal (PVar) velocity significantly decreased as compared to normals. These findings normalized after closure. Patients with large IAS (defined as invasive Qp/Qs ≥ 2) had higher PVs, PVd and PV-VTI, shorter Q-PVd but lower PVar (all pIAS. Invasive Qp/Qs ratios correlated with PVs, PVd, PV-VTI, Q-PVd and TTE-derived Qp/Qs ratios, ASD sizes and RV end-diastolic dimensions (all pIAS after multivariate analysis. The corresponding sensitivity, specificity and AUC were 89%, 82% and 0.90 respectively for a PV-VTI of 30 cm (pIAS have distinguishable PVF features. Doppler evaluation of PV-VTI is a novel additional tool for assessing the magnitude of shunting in these patients non-invasively. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  16. PREDICTIVE SIGNIFICANCE OF ANTI-HLA AUTOANTIBODIES IN HEART TRANSPLANT RECIPIENTS

    Directory of Open Access Journals (Sweden)

    O. P. Shevchenko

    2013-01-01

    Full Text Available Aim. The aim of this study was to define the role of preformed anti-HLA antibodies (anti-HLA in antibody-mediated rejection (AMR and cardiac allograft vasculopathy (CAV after heart transplantation. Materials and Methods. 140 heart transplant recipients were followed after heart transplantation performed for 106 dilated and 34 – ischemic cardiomyopathy. Anti-HLA was determined before transplantation by ELISA. Results. Recipients were divided into 2 groups: anti-HLA positive (n = 45, 32,1% and anti-HLA negative (n = 95, 67,9%. The incidence of AMR in anti-HLA positive group was 12 (26,67% and 11 (11,58% in anti-HLA negative group. Risk of AMR was significantly higher in anti-HLA positive recipients (RR 2,3: 95% CI 1,02–4,81, р = 0,03. During first three years after transplantation CAV was diagnosed in 9 (20% of anti-HLA positive recipients and in 7 (6,8% of patients without anti-HLA. (RR 2,7: 95% CI 1,08–6,82, р = 0,03. Survival in freedom from CAV in anti-HLA negative recipients was much higher than in anti-HLA positive recipients (0,89 ± 0,07, 0,72 ± 0,06, resp. (p = 0,02.Conclusions. The presence of preformed anti-HLA antibodies in candidates for heart transplantation increase the risk of AMR and CAV post transplantation in 2,3 and 2,7 times, respectively. 

  17. Successful percutaneous coronary intervention significantly improves coronary sinus blood flow as assessed by transthoracic echocardiography.

    Science.gov (United States)

    Lyubarova, Radmila; Boden, William E; Fein, Steven A; Schulman-Marcus, Joshua; Torosoff, Mikhail

    2018-06-01

    Transthoracic echocardiography (TTE) has been used to assess coronary sinus blood flow (CSBF), which reflects total coronary arterial blood flow. Successful angioplasty is expected to improve coronary arterial blood flow. Changes in CSBF after percutaneous coronary intervention (PCI), as assessed by TTE, have not been systematically evaluated. TTE can be utilized to reflect increased CSBF after a successful, clinically indicated PCI. The study cohort included 31 patients (18 females, 62 ± 11 years old) referred for diagnostic cardiac catheterization for suspected coronary artery disease and possible PCI, when clinically indicated. All performed PCIs were successful, with good angiographic outcome. CSBF per cardiac cycle (mL/beat) was measured using transthoracic two-dimensional and Doppler flow imaging as the product of coronary sinus (CS) area and CS flow time-velocity integral. CSBF per minute (mL/min) was calculated as the product of heart rate and CSBF per cardiac cycle. In each patient, CSBF was assessed prospectively, before and after cardiac catheterization with and without clinically indicated PCI. Within- and between-group differences in CSBF before and after PCI were assessed using repeated measures analysis of variance. Technically adequate CSBF measurements were obtained in 24 patients (77%). In patients who did not undergo PCI, there was no significant change in CSBF (278.1 ± 344.1 versus 342.7 ± 248.5, p = 0.36). By contrast, among patients who underwent PCI, CSBF increased significantly (254.3 ± 194.7 versus 618.3 ± 358.5 mL/min, p < 0.01, p-interaction = 0.03). Other hemodynamic and echocardiographic parameters did not change significantly before and after cardiac catheterization in either treatment group. Transthoracic echocardiographic assessment can be employed to document CSBF changes after angioplasty. Future studies are needed to explore the clinical utility of this noninvasive metric.

  18. 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.

  19. 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.

  20. Faculty Decisions on Serials Subscriptions Differ Significantly from Decisions Predicted by a Bibliometric Tool.

    Directory of Open Access Journals (Sweden)

    Sue F. Phelps

    2016-03-01

    of the faculty choices. The p-value for this relationship was less than 0.0001, also indicating that the result was not by chance. A quadratic model plotted alongside the previous linear model follows a similar pattern. The p-value of the comparison is 0.0002, which indicates the quadratic model’s fit cannot be explained by random chance. Main Results – The authors point out three outstanding findings. First, the match rate between faculty valuations and bibliometric scores for serials is 65%. This exceeds the 50% rate that would indicate random association, but also indicates a statistically significant difference between faculty and bibliometric valuations. Secondly, the match rate with the bibliometric scores for titles that faculty chose to keep (73% was higher than those they chose to cancel (54%. Thirdly, the match rate increased with higher bibliometric scores. Conclusions – Though the authors identify only a modest degree of similarity between faculty and bibliometric valuations of serials, it is noted that there is more agreement in the higher valued serials than the lower valued serials. With that in mind, librarians might focus faculty review on the lower scoring titles in the future, taking into consideration that unique faculty interests may drive selection at that level and would need to be balanced with the mission of the library.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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)

  6. A critical review of predictive models for the onset of significant void in forced-convection subcooled boiling

    International Nuclear Information System (INIS)

    Dorra, H.; Lee, S.C.; Bankoff, S.G.

    1993-06-01

    This predictive models for the onset of significant void (OSV) in forced-convection subcooled boiling are reviewed and compared with extensive data. Three analytical models and seven empirical correlations are considered in this review. These models and correlations are put onto a common basis and are compared, again on a common basis, with a variety of data. The evaluation of their range of validity and applicability under various operating conditions are discussed. The results show that the correlations of Saha-Zuber seems to be the best model to predict OSV in vertical subcooled boiling flow

  7. Heat storage in forest biomass significantly improves energy balance closure particularly during stable conditions

    Science.gov (United States)

    Lindroth, A.; Mölder, M.; Lagergren, F.

    2009-08-01

    Temperature measurements in trunks and branches in a mature ca. 100 years-old mixed pine and spruce forest in central Sweden were used to estimate the heat storage in the tree biomass. The estimated heat flux in the sample trees and data on biomass distributions were used to scale up to stand level biomass heat fluxes. The rate of change of sensible and latent heat storage in the air layer below the level of the flux measurements was estimated from air temperature and humidity profile measurements and soil heat flux was estimated from heat flux plates and soil temperature measurements. The fluxes of sensible and latent heat from the forest were measured with an eddy covariance system in a tower. The analysis was made for a two-month period in summer of 1995. The tree biomass heat flux was the largest of the estimated storage components and varied between 40 and -35 W m-2 on summer days with nice weather. Averaged over two months the diurnal maximum of total heat storage was 45 W m-2 and the minimum was -35 W m-2. The soil heat flux and the sensible heat storage in air were out of phase with the biomass flux and they reached maximum values that were about 75% of the maximum of the tree biomass heat storage. The energy balance closure improved significantly when the total heat storage was added to the turbulent fluxes. The slope of a regression line with sum of fluxes and storage as independent and net radiation as dependent variable, increased from 0.86 to 0.95 for half-hourly data and the scatter was also reduced. The most significant finding was, however, that during nights with strongly stable conditions when the sensible heat flux dropped to nearly zero, the total storage matched the net radiation nearly perfectly. Another interesting result was that the mean energy imbalance started to increase when the Richardson number became more negative than ca. -0.1. In fact, the largest energy deficit occurred at maximum instability. Our conclusion is that eddy

  8. Significant improvement of eczema with skin care and food elimination in small children.

    Science.gov (United States)

    Norrman, Gunilla; Tomicić, Sara; Böttcher, Malin Fagerås; Oldaeus, Göran; Strömberg, Leif; Fälth-magnusson, Karin

    2005-10-01

    To evaluate common methods of investigation and treatment in children younger than 2 y of age with eczema, with or without sensitization to food allergens. One hundred and twenty-three children younger than 2 y of age with eczema and suspected food allergy were included in this prospective study. The children underwent skin-prick test with cow's milk, fresh hen's egg white and wheat. Specific IgE to milk and egg white was analysed. The eczema extent and severity was estimated with SCORAD before and after treatment. Children with a positive skin-prick test were instructed to exclude that food item from their diet. All children were treated with emollients and topical steroids when needed. Sixty-two of the children were skin-prick positive to at least one of the allergens; 62% had mild, 30% moderate and 8% severe eczema at their first visit. After treatment, 90% had mild, 10% moderate and 0% severe eczema. Forty-six per cent of the children had circulating IgE antibodies to milk or egg white. Ten per cent had specific IgE but negative skin-prick test to the same allergen. This subgroup improved their eczema significantly without elimination diet. The conventional treatments for children with eczema, i.e. skin care and food elimination, are effective. The beneficial effect of skin care as the first step should not be neglected, and it may not be necessary to eliminate food allergens to relieve skin symptoms in all food-sensitized children with eczema.

  9. Introduction of e-learning in dental radiology reveals significantly improved results in final examination.

    Science.gov (United States)

    Meckfessel, Sandra; Stühmer, Constantin; Bormann, Kai-Hendrik; Kupka, Thomas; Behrends, Marianne; Matthies, Herbert; Vaske, Bernhard; Stiesch, Meike; Gellrich, Nils-Claudius; Rücker, Martin

    2011-01-01

    Because a traditionally instructed dental radiology lecture course is very time-consuming and labour-intensive, online courseware, including an interactive-learning module, was implemented to support the lectures. The purpose of this study was to evaluate the perceptions of students who have worked with web-based courseware as well as the effect on their results in final examinations. Users (n(3+4)=138) had access to the e-program from any networked computer at any time. Two groups (n(3)=71, n(4)=67) had to pass a final exam after using the e-course. Results were compared with two groups (n(1)=42, n(2)=48) who had studied the same content by attending traditional lectures. In addition a survey of the students was statistically evaluated. Most of the respondents reported a positive attitude towards e-learning and would have appreciated more access to computer-assisted instruction. Two years after initiating the e-course the failure rate in the final examination dropped significantly, from 40% to less than 2%. The very positive response to the e-program and improved test scores demonstrated the effectiveness of our e-course as a learning aid. Interactive modules in step with clinical practice provided learning that is not achieved by traditional teaching methods alone. To what extent staff savings are possible is part of a further study. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  10. Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files.

    Science.gov (United States)

    Sun, Xiaobo; Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng; Qin, Zhaohui S

    2018-06-01

    Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)-based high-performance computing (HPC) implementation, and the popular VCFTools. Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.

  11. Cyclosporin A significantly improves preeclampsia signs and suppresses inflammation in a rat model.

    Science.gov (United States)

    Hu, Bihui; Yang, Jinying; Huang, Qian; Bao, Junjie; Brennecke, Shaun Patrick; Liu, Huishu

    2016-05-01

    Preeclampsia is associated with an increased inflammatory response. Immune suppression might be an effective treatment. The aim of this study was to examine whether Cyclosporin A (CsA), an immunosuppressant, improves clinical characteristics of preeclampsia and suppresses inflammation in a lipopolysaccharide (LPS) induced preeclampsia rat model. Pregnant rats were randomly divided into 4 groups: group 1 (PE) rats each received LPS via tail vein on gestational day (GD) 14; group 2 (PE+CsA5) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (5mg/kg, ip) on GDs 16, 17 and 18; group 3 (PE+CsA10) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (10mg/kg, ip) on GDs 16, 17 and 18; group 4 (pregnant control, PC) rats were treated with the vehicle (saline) used for groups 1, 2 and 3. Systolic blood pressure, urinary albumin, biometric parameters and the levels of serum cytokines were measured on day 20. CsA treatment significantly reduced LPS-induced systolic blood pressure and the mean 24-h urinary albumin excretion. Pro-inflammatory cytokines IL-6, IL-17, IFN-γ and TNF-α were increased in the LPS treatment group but were reduced in (LPS+CsA) group (Ppreeclampsia signs and attenuated inflammatory responses in the LPS induced preeclampsia rat model which suggests that immunosuppressant might be an alternative management option for preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. 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.

  13. Combination of blood tests for significant fibrosis and cirrhosis improves the assessment of liver-prognosis in chronic hepatitis C.

    Science.gov (United States)

    Boursier, J; Brochard, C; Bertrais, S; Michalak, S; Gallois, Y; Fouchard-Hubert, I; Oberti, F; Rousselet, M-C; Calès, P

    2014-07-01

    Recent longitudinal studies have emphasised the prognostic value of noninvasive tests of liver fibrosis and cross-sectional studies have shown their combination significantly improves diagnostic accuracy. To compare the prognostic accuracy of six blood fibrosis tests and liver biopsy, and evaluate if test combination improves the liver-prognosis assessment in chronic hepatitis C (CHC). A total of 373 patients with compensated CHC, liver biopsy (Metavir F) and blood tests targeting fibrosis (APRI, FIB4, Fibrotest, Hepascore, FibroMeter) or cirrhosis (CirrhoMeter) were included. Significant liver-related events (SLRE) and liver-related deaths were recorded during follow-up (started the day of biopsy). During the median follow-up of 9.5 years (3508 person-years), 47 patients had a SLRE and 23 patients died from liver-related causes. For the prediction of first SLRE, most blood tests allowed higher prognostication than Metavir F [Harrell C-index: 0.811 (95% CI: 0.751-0.868)] with a significant increase for FIB4: 0.879 [0.832-0.919] (P = 0.002), FibroMeter: 0.870 [0.812-0.922] (P = 0.005) and APRI: 0.861 [0.813-0.902] (P = 0.039). Multivariate analysis identified FibroMeter, CirrhoMeter and sustained viral response as independent predictors of first SLRE. CirrhoMeter was the only independent predictor of liver-related death. The combination of FibroMeter and CirrhoMeter classifications into a new FM/CM classification improved the liver-prognosis assessment compared to Metavir F staging or single tests by identifying five subgroups of patients with significantly different prognoses. Some blood fibrosis tests are more accurate than liver biopsy for determining liver prognosis in CHC. A new combination of two complementary blood tests, one targeted for fibrosis and the other for cirrhosis, optimises assessment of liver-prognosis. © 2014 John Wiley & Sons Ltd.

  14. Waste Minimization Improvements Achieved Through Six Sigma Analysis Result In Significant Cost Savings

    International Nuclear Information System (INIS)

    Mousseau, Jeffrey D.; Jansen, John R.; Janke, David H.; Plowman, Catherine M.

    2003-01-01

    Improved waste minimization practices at the Department of Energy's (DOE) Idaho National Engineering and Environmental Laboratory (INEEL) are leading to a 15% reduction in the generation of hazardous and radioactive waste. Bechtel, BWXT Idaho, LLC (BBWI), the prime management and operations contractor at the INEEL, applied the Six Sigma improvement process to the INEEL Waste Minimization Program to review existing processes and define opportunities for improvement. Our Six Sigma analysis team: composed of an executive champion, process owner, a black belt and yellow belt, and technical and business team members used this statistical based process approach to analyze work processes and produced ten recommendations for improvement. Recommendations ranged from waste generator financial accountability for newly generated waste to enhanced employee recognition programs for waste minimization efforts. These improvements have now been implemented to reduce waste generation rates and are producing positive results

  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. 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.

  17. 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.

  18. 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

  19. Contemporary Management of Acute Aortic Occlusion Has Evolved but Outcomes Have Not Significantly Improved.

    Science.gov (United States)

    Robinson, William P; Patel, Rupal K; Columbo, Jesse A; Flahive, Julie; Aiello, Francesco A; Baril, Donald T; Schanzer, Andres; Messina, Louis M

    2016-07-01

    hospitalization. AAO is now more commonly caused by in situ thrombosis rather than embolism. A high index of suspicion for AAO is required for prompt diagnosis and treatment, particularly when patients present with profound lower extremity neurologic deficit. In comparison with previous reports, the contemporary management of AAO includes increased use of axillobifemoral bypass and now involves endovascular revascularization, although a variety of open surgical procedures are utilized. However, the in-hospital mortality and morbidity of AAO has not decreased significantly over the last 2 decades and mid-term survival remains limited. Further study is required to identify strategies that improve outcomes after AAO. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Efficiency improvement of nuclear power plant operation: the significant role of advanced nuclear fuel technologies

    International Nuclear Information System (INIS)

    Van Velde, AA. de; Burtak, F.

    2000-01-01

    In this paper authors deals with nuclear fuel cycle and their economic aspects. At Siemens, the developments focusing on the reduction of fuel cycle costs are currently directed on .further batch average burnup increase, .improvement of fuel reliability, .enlargement of fuel operation margins, .improvement of methods for fuel design and core analysis. These items will be presented in detail in the full paper and illustrated by the global operating experience of Siemens fuel for both PWRs and BWRs. (authors)

  1. Reestablishing Open Rotor as an Option for Significant Fuel Burn Improvements

    Science.gov (United States)

    Van Zante, Dale

    2011-01-01

    A low-noise open rotor system is being tested in collaboration with General Electric and CFM International, a 50/50 joint company between Snecma and GE. Candidate technologies for lower noise will be investigated as well as installation effects such as pylon integration. Current test status is presented as well as future scheduled testing which includes the FAA/CLEEN test entry. Pre-test predictions show that Open Rotors have the potential for revolutionary fuel burn savings.

  2. 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

  3. Significant pre-accession factors predicting success or failure during a Marine Corps officer’s initial service obligation

    OpenAIRE

    Johnson, Jacob A.

    2015-01-01

    Approved for public release; distribution is unlimited Increasing diversity and equal opportunity in the military is a congressional and executive priority. At the same time, improving recruiting practices is a priority of the commandant of the Marine Corps. In an effort to provide information to the Marine Corps that may improve recruiting practice and enable retention of a higher quality and more diverse officer corps, probit econometric models are estimated to identify significant facto...

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. Millisecond photo-thermal process on significant improvement of supercapacitor’s performance

    International Nuclear Information System (INIS)

    Wang, Kui; Wang, Jixiao; Wu, Ying; Zhao, Song; Wang, Zhi; Wang, Shichang

    2016-01-01

    Graphical abstract: A high way for charge transfer is created by a millisecond photo-thermal process which could decrease contact resistance among nanomaterials and improve the electrochemical performances. - Highlights: • Improve conductivity among nanomaterials with a millisecond photo-thermal process. • The specific capacitance can increase about 25% with an photo-thermal process. • The circle stability and rate capability can be improved above 10% with photo-thermal process. • Provide a new way that create electron path to improve electrochemical performance. - Abstract: Supercapacitors fabricated with nanomaterials usually have high specific capacitance and excellent performance. However, the small size of nanomaterials renders a considerable limitation of the contact area among nanomaterials, which is harmful to charge carrier transfer. This fact may hinder the development and application of nanomaterials in electrochemical storage systems. Here, a millisecond photo-thermal process was introduced to create a charge carries transfer path to decrease the contact resistance among nanomaterials, and enhance the electrochemical performance of supercapacitors. Polyaniline (PANI) nanowire, as a model nanomaterial, was used to modify electrodes under different photo-thermal process conditions. The modified electrodes were characterized by scanning electronic microscopy (SEM), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and the results were analysed by equivalent circuit simulation. These results demonstrate that the photo-thermal process can alter the morphology of PANI nanowires, lower the charge transfer resistances and thus improve the performance of electrodes. The specific capacitance increase of the modified electrodes is about 25%. The improvement of the circle stability and rate capability are above 10%. To the best of our knowledge, this is the first attempt on research the effect of photo-thermal process on the conductivity

  9. A Review of New and Developing Technology to Significantly Improve Mars Sample-Return Missions

    Science.gov (United States)

    Carsey, F.; Brophy, J.; Gilmore, M.; Rodgers, D.; Wilcox, B.

    2000-07-01

    A JPL development activity was initiated in FY 1999 for the purpose of examining and evaluating technologies that could materially improve future (i.e., beyond the 2005 launch) Mars sample return missions. The scope of the technology review was comprehensive and end-to-end; the goal was to improve mass, cost, risk, and scientific return. A specific objective was to assess approaches to sample return with only one Earth launch. While the objective of the study was specifically for sample-return, in-situ missions can also benefit from using many of the technologies examined.

  10. Prostate health index (phi) and prostate cancer antigen 3 (PCA3) significantly improve diagnostic accuracy in patients undergoing prostate biopsy.

    Science.gov (United States)

    Perdonà, Sisto; Bruzzese, Dario; Ferro, Matteo; Autorino, Riccardo; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; Longo, Michele; Spinelli, Rosa; Di Lorenzo, Giuseppe; Oliva, Andrea; De Sio, Marco; Damiano, Rocco; Altieri, Vincenzo; Terracciano, Daniela

    2013-02-15

    Prostate health index (phi) and prostate cancer antigen 3 (PCA3) have been recently proposed as novel biomarkers for prostate cancer (PCa). We assessed the diagnostic performance of these biomarkers, alone or in combination, in men undergoing first prostate biopsy for suspicion of PCa. One hundred sixty male subjects were enrolled in this prospective observational study. PSA molecular forms, phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay), and other established biomarkers (tPSA, fPSA, and %fPSA) were assessed before patients underwent a 18-core first prostate biopsy. The discriminating ability between PCa-negative and PCa-positive biopsies of Beckman coulter phi and PCA3 score and other used biomarkers were determined. One hundred sixty patients met inclusion criteria. %p2PSA (p2PSA/fPSA × 100), phi and PCA3 were significantly higher in patients with PCa compared to PCa-negative group (median values: 1.92 vs. 1.55, 49.97 vs. 36.84, and 50 vs. 32, respectively, P ≤ 0.001). ROC curve analysis showed that %p2PSA, phi, and PCA3 are good indicator of malignancy (AUCs = 0.68, 0.71, and 0.66, respectively). A multivariable logistic regression model consisting of both the phi index and PCA3 score allowed to reach an overall diagnostic accuracy of 0.77. Decision curve analysis revealed that this "combined" marker achieved the highest net benefit over the examined range of the threshold probability. phi and PCA3 showed no significant difference in the ability to predict PCa diagnosis in men undergoing first prostate biopsy. However, diagnostic performance is significantly improved by combining phi and PCA3. Copyright © 2012 Wiley Periodicals, Inc.

  11. Non-invasive prediction of hemodynamically significant coronary artery stenoses by contrast density difference in coronary CT angiography

    Energy Technology Data Exchange (ETDEWEB)

    Hell, Michaela M., E-mail: michaela.hell@uk-erlangen.de [Department of Cardiology, University of Erlangen (Germany); Dey, Damini [Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Taper Building, Room A238, 8700 Beverly Boulevard, Los Angeles, CA 90048 (United States); Marwan, Mohamed; Achenbach, Stephan; Schmid, Jasmin; Schuhbaeck, Annika [Department of Cardiology, University of Erlangen (Germany)

    2015-08-15

    Highlights: • Overestimation of coronary lesions by coronary computed tomography angiography and subsequent unnecessary invasive coronary angiography and revascularization is a concern. • Differences in plaque characteristics and contrast density difference between hemodynamically significant and non-significant stenoses, as defined by invasive fractional flow reserve, were assessed. • At a threshold of ≥24%, contrast density difference predicted hemodynamically significant lesions with a specificity of 75%, sensitivity of 33%, PPV of 35% and NPV of 73%. • The determination of contrast density difference required less time than transluminal attenuation gradient measurement. - Abstract: Objectives: Coronary computed tomography angiography (CTA) allows the detection of obstructive coronary artery disease. However, its ability to predict the hemodynamic significance of stenoses is limited. We assessed differences in plaque characteristics and contrast density difference between hemodynamically significant and non-significant stenoses, as defined by invasive fractional flow reserve (FFR). Methods: Lesion characteristics of 59 consecutive patients (72 lesions) in whom invasive FFR was performed in at least one coronary artery with moderate to high-grade stenoses in coronary CTA were evaluated by two experienced readers. Coronary CTA data sets were acquired on a second-generation dual-source CT scanner using retrospectively ECG-gated spiral acquisition or prospectively ECG-triggered axial acquisition mode. Plaque volume and composition (non-calcified, calcified), remodeling index as well as contrast density difference (defined as the percentage decline in luminal CT attenuation/cross-sectional area over the lesion) were assessed using a semi-automatic software tool (Autoplaq). Additionally, the transluminal attenuation gradient (defined as the linear regression coefficient between intraluminal CT attenuation and length from the ostium) was determined

  12. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2007-01-01

    Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited. Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions. Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied. The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was dependent on the composition of the solutes present. For more atmospherically representative higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus

  13. 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.

  14. Reducing dysfunctional beliefs about sleep does not significantly improve insomnia in cognitive behavioral therapy.

    Science.gov (United States)

    Okajima, Isa; Nakajima, Shun; Ochi, Moeko; Inoue, Yuichi

    2014-01-01

    The present study examined to examine whether improvement of insomnia is mediated by a reduction in sleep-related dysfunctional beliefs through cognitive behavioral therapy for insomnia. In total, 64 patients with chronic insomnia received cognitive behavioral therapy for insomnia consisting of 6 biweekly individual treatment sessions of 50 minutes in length. Participants were asked to complete the Athens Insomnia Scale and the Dysfunctional Beliefs and Attitudes about Sleep scale both at the baseline and at the end of treatment. The results showed that although cognitive behavioral therapy for insomnia greatly reduced individuals' scores on both scales, the decrease in dysfunctional beliefs and attitudes about sleep with treatment did not seem to mediate improvement in insomnia. The findings suggest that sleep-related dysfunctional beliefs endorsed by patients with chronic insomnia may be attenuated by cognitive behavioral therapy for insomnia, but changes in such beliefs are not likely to play a crucial role in reducing the severity of insomnia.

  15. Reducing Dysfunctional Beliefs about Sleep Does Not Significantly Improve Insomnia in Cognitive Behavioral Therapy

    OpenAIRE

    Okajima, Isa; Nakajima, Shun; Ochi, Moeko; Inoue, Yuichi

    2014-01-01

    The present study examined to examine whether improvement of insomnia is mediated by a reduction in sleep-related dysfunctional beliefs through cognitive behavioral therapy for insomnia. In total, 64 patients with chronic insomnia received cognitive behavioral therapy for insomnia consisting of 6 biweekly individual treatment sessions of 50 minutes in length. Participants were asked to complete the Athens Insomnia Scale and the Dysfunctional Beliefs and Attitudes about Sleep scale both at the...

  16. Significant performance improvement obtained in a wireless mesh network using a beamswitching antenna

    CSIR Research Space (South Africa)

    Lysko, AA

    2012-09-01

    Full Text Available mesh network operated in a fixed 11 Mbps mode. The throughput improvement in multi-hop communication obtained in the presence of an interferer is tenfold, from 0.2 Mbps to 2 Mbps. Index Terms?antenna, smart antenna, wireless mesh network, WMN... efficiency in the communications, and active research and development of new methods and technologies enabling this at the physical layer, including multiple antenna techniques, such as multiple input multiple output (MIMO) and smart antennas...

  17. Clinical significance and predictive factors of early massive recurrence after radiofrequency ablation in patients with a single small hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Ju-Yeon Cho

    2016-12-01

    Full Text Available Background/Aims Radiofrequency ablation (RFA is one of the most frequently applied curative treatments in patients with a single small hepatocellular carcinoma (HCC. However, the clinical significance of and risk factors for early massive recurrence after RFA—a dreadful event limiting further curative treatment—have not been fully evaluated. Methods In total, 438 patients with a single HCC of size ≤3 cm who underwent percutaneous RFA as an initial treatment between 2006 and 2009 were included. Baseline patient characteristics, overall survival, predictive factors, and recurrence after RFA were evaluated. In addition, the incidence, impact on survival, and predictive factors of early massive recurrence, and initial recurrence beyond the Milan criteria within 2 years were also investigated. Results During the median follow-up of 68.4 months, recurrent HCC was confirmed in 302 (68.9% patients, with early massive recurrence in 27 patients (6.2%. The 1-, 3-, and 5-year overall survival rates were 95.4%, 84.7%, and 81.8%, respectively, in patients with no recurrence, 99.6%, 86.4%, and 70.1% in patients with recurrence within the Milan criteria or late recurrence, and 92.6%, 46.5%, and 0.05% in patients with early massive recurrence. Multivariable analysis identified older age, Child-Pugh score B or C, and early massive recurrence as predictive of poor overall survival. A tumor size of ≥2 cm and tumor location adjacent to the colon were independent risk factors predictive of early massive recurrence. Conclusions Early massive recurrence is independently predictive of poor overall survival after RFA in patients with a single small HCC. Tumors sized ≥2 cm and located adjacent to the colon appear to be independent risk factors for early massive recurrence.

  18. 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.

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

    Science.gov (United States)

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

    2009-07-01

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

  20. Intraoperative Sensorcaine significantly improves postoperative pain management in outpatient reduction mammaplasty.

    Science.gov (United States)

    Culliford, Alfred T; Spector, Jason A; Flores, Roberto L; Louie, Otway; Choi, Mihye; Karp, Nolan S

    2007-09-15

    Breast reduction is one of the most frequently performed plastic surgical procedures in the United States; more than 160,500 patients underwent the procedure in 2005. Many outpatient reduction mammaplasty patients report the greatest postoperative discomfort in the first 48 hours. The authors' investigated the effect of intraoperative topical application of the long-acting local anesthetic agent bupivacaine (Sensorcaine or Marcaine) on postoperative pain, time to postanesthesia care unit discharge, and postoperative use of narcotic medication. In a prospective, randomized, single-blind trial, intraoperative use of Sensorcaine versus placebo (normal saline) was compared. Postoperative pain was quantified using the visual analogue scale, and time to discharge from the postanesthesia care unit was recorded. Patients documented their outpatient pain medication usage. Of the 37 patients enrolled in the study, 20 were treated with intraoperative topical Sensorcaine and 17 received placebo. Patients treated with Sensorcaine were discharged home significantly faster (2.9 hours versus 3.8 hours, p = 0.002). The control arm consistently had higher pain scores in the postanesthesia care unit (although not statistically significant) than the Sensorcaine group using the visual analogue scale system. Furthermore, patients receiving Sensorcaine required significantly less narcotic medication while recovering at home (mean, 3.5 tablets of Vicodin) than the control group (mean, 6.4 tablets; p = 0.001). There were no complications resulting from Sensorcaine usage. This prospective, randomized, single-blind study demonstrates that a single dose of intraoperative Sensorcaine provides a safe, inexpensive, and efficacious way to significantly shorten the length of postanesthesia care unit stay and significantly decrease postoperative opioid analgesic use in patients undergoing ambulatory reduction mammaplasty.

  1. Nitrite addition to acidified sludge significantly improves digestibility, toxic metal removal, dewaterability and pathogen reduction

    Science.gov (United States)

    Du, Fangzhou; Keller, Jürg; Yuan, Zhiguo; Batstone, Damien J.; Freguia, Stefano; Pikaar, Ilje

    2016-12-01

    Sludge management is a major issue for water utilities globally. Poor digestibility and dewaterability are the main factors determining the cost for sludge management, whereas pathogen and toxic metal concentrations limit beneficial reuse. In this study, the effects of low level nitrite addition to acidified sludge to simultaneously enhance digestibility, toxic metal removal, dewaterability and pathogen reduction were investigated. Waste activated sludge (WAS) from a full-scale waste water treatment plant was treated at pH 2 with 10 mg NO2--N/L for 5 h. Biochemical methane potential tests showed an increase in the methane production of 28%, corresponding to an improvement from 247 ± 8 L CH4/kg VS to 317 ± 1 L CH4/kg VS. The enhanced removal of toxic metals further increased the methane production by another 18% to 360 ± 6 L CH4/kg VS (a total increase of 46%). The solids content of dewatered sludge increased from 14.6 ± 1.4% in the control to 18.2 ± 0.8%. A 4-log reduction for both total coliforms and E. coli was achieved. Overall, this study highlights the potential of acidification with low level nitrite addition as an effective and simple method achieving multiple improvements in terms of sludge management.

  2. Efficiency improvement of nuclear power plant operation: the significant role of advanced nuclear fuel technologies

    International Nuclear Information System (INIS)

    Velde Van de, A.; Burtak, F.

    2001-01-01

    Due to the increased liberalisation of the power markets, nuclear power generation is being exposed to high cost reduction pressure. In this paper we highlight the role of advanced nuclear fuel technologies to reduce the fuel cycle costs and therefore increase the efficiency of nuclear power plant operation. The key factor is a more efficient utilisation of the fuel and present developments at Siemens are consequently directed at (i) further increase of batch average burnup, (ii) improvement of fuel reliability, (iii) enlargement of fuel operation margins and (iv) improvement of methods for fuel design and core analysis. As a result, the nuclear fuel cycle costs for a typical LWR have been reduced during the past decades by about US$ 35 million per year. The estimated impact of further burnup increases on the fuel cycle costs is expected to be an additional saving of US$10 - 15 million per year. Due to the fact that the fuel will operate closer to design limits, a careful approach is required when introducing advanced fuel features in reload quantities. Trust and co-operation between the fuel vendors and the utilities is a prerequisite for the common success. (authors)

  3. Significant improvement of mouse cloning technique by treatment with trichostatin A after somatic nuclear transfer

    International Nuclear Information System (INIS)

    Kishigami, Satoshi; Mizutani, Eiji; Ohta, Hiroshi; Hikichi, Takafusa; Thuan, Nguyen Van; Wakayama, Sayaka; Bui, Hong-Thuy; Wakayama, Teruhiko

    2006-01-01

    The low success rate of animal cloning by somatic cell nuclear transfer (SCNT) is believed to be associated with epigenetic errors including abnormal DNA hypermethylation. Recently, we elucidated by using round spermatids that, after nuclear transfer, treatment of zygotes with trichostatin A (TSA), an inhibitor of histone deacetylase, can remarkably reduce abnormal DNA hypermethylation depending on the origins of transferred nuclei and their genomic regions [S. Kishigami, N. Van Thuan, T. Hikichi, H. Ohta, S. Wakayama. E. Mizutani, T. Wakayama, Epigenetic abnormalities of the mouse paternal zygotic genome associated with microinsemination of round spermatids, Dev. Biol. (2005) in press]. Here, we found that 5-50 nM TSA-treatment for 10 h following oocyte activation resulted in more efficient in vitro development of somatic cloned embryos to the blastocyst stage from 2- to 5-fold depending on the donor cells including tail tip cells, spleen cells, neural stem cells, and cumulus cells. This TSA-treatment also led to more than 5-fold increase in success rate of mouse cloning from cumulus cells without obvious abnormality but failed to improve ES cloning success. Further, we succeeded in establishment of nuclear transfer-embryonic stem (NT-ES) cells from TSA-treated cloned blastocyst at a rate three times higher than those from untreated cloned blastocysts. Thus, our data indicate that TSA-treatment after SCNT in mice can dramatically improve the practical application of current cloning techniques

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

    Science.gov (United States)

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

    2017-11-24

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

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

    Directory of Open Access Journals (Sweden)

    Assaf Gottlieb

    2017-11-01

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

  6. 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.

  7. 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

  8. The Improvement of Screening the Significant Factors of Oil Blends as Bio lubricant Base Stock

    International Nuclear Information System (INIS)

    Noor Hajarul Ashikin Shamsuddin; Rozaini Abdullah; Zainab Hamzah; Siti Jamilah Hanim Mohd Yusof

    2015-01-01

    A new formulation bio lubricant base stock was developed by blending of waste cooking oil (WCO) with Jatropha curcas oil (JCO). The objective of this research is to evaluate significant factors contributing to the production of oil blends for bio lubricant application. The significant factors used in this study were oil ratio (WCO:JCO), agitation times (min) and agitation speed (rpm). The blended oil bio based lubricant was used to determine the saponification, acid, peroxide and iodine values. The experimental design used in this study was the 2 level-factorial design. In this experiment, it was found that the effect of oil ratio and interaction of oil ratio and agitation speed gave the most significant effect in oil blends as bio lubricant base stock. The highest ratio of oil blend 80 %:20 % WCO:JCO, with low agitation speed of 300 rpm and low agitation time of 30 minutes gave the optimum results. The acid, saponification, peroxide and iodine values obtained were 0.517±0.08 mg KOH/ g, 126.23±1.62 mg/ g, 7.5±2.0 m eq/ kg and 50.42±2.85 mg/ g respectively. A higher ratio of waste cooking oil blends was found to be favourable as bio lubricant base stock. (author)

  9. 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.)

  10. Role of hyaluronic acid and laminin as serum markers for predicting significant fibrosis in patients with chronic hepatitis B

    Directory of Open Access Journals (Sweden)

    Feng Li

    Full Text Available OBJECTIVES: The aim of this study was to evaluate the diagnostic performance of serum HA and LN as serum markers for predicting significant fibrosis in CHB patients. METHODS: Serum HA and LN levels of 87 patients with chronic hepatitis B and 19 blood donors were assayed by RIA. Liver fibrosis stages were determined according to the Metavir scoring-system. The diagnostic performances of all indexes were evaluated by the receiver operating characteristic (ROC curves. RESULTS: Serum HA and LN concentrations increased significantly with the stage of hepatic fibrosis, which showed positive correlation with the stages of liver fibrosis (HA: r = 0.875, p < 0.001; LN: r = 0.610, p < 0.001. There were significant differences of serum HA and LN levels between F2-4 group in comparison with those in F0-F1 group (p < 0.001 and controls (p < 0.001, respectively. From ROC curves, 185.3 ng/mL as the optimal cut-off value of serum HA for diagnosis of significant fibrosis, giving its sensitivity, specificity, PPV, NPV, LR+, LR- and AC of 84.2%, 83.3%, 90.6%, 73.5%, 5.04, 0.19 and 83.9, respectively. While 132.7 ng/mL was the optimal cut-off value of serum LN, the sensitivity, specificity, PPV, NPV, LR+, LR- and AC were 71.9%, 80.0%, 87.2%, 60.0%, 3.59%, 0.35% and 74.7, respectively. Combinations of HA and LN by serial tests showed a perfect specificity and PPV of 100%, at the same time sensitivity declined to 63.2% and LR+ increased to 18.9, while parallel tests revealed a good sensitivity of 94.7%, NPV to 86.4%, and LR- declined to 0.08. CONCLUSIONS: Serum HA and LN concentrations showed positive correlation with the stages of liver fibrosis. Detection of serum HA and LN in predicting significant fibrosis showed good diagnostic performance, which would be further optimized by combination of the two indices. HA and LN would be clinically useful serum markers for predicting significant fibrosis in patients with chronic hepatitis B, when liver biopsy is

  11. EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

    Directory of Open Access Journals (Sweden)

    Matthew H. Savoie

    2012-03-01

    Full Text Available Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article defines a standard for an improved EASE-Grid 2.0 definition, addressing how the changes rectify issues with the original grid definition. Data distributed using the EASE-Grid 2.0 standard will be easier for users to import into standard software packages and will minimize common reprojection errors that users had encountered with the original EASE-Grid definition.

  12. A patient/family-centered strategic plan can drive significant improvement.

    Science.gov (United States)

    Brilli, Richard J; Crandall, Wallace V; Berry, Janet C; Stoverock, Linda; Rosen, Kerry; Budin, Lee; Kelleher, Kelly J; Gleeson, Sean P; Davis, J Terrance

    2014-08-01

    The use of a PFCSP, as a road map to operationalize the hospital's vision, has been a compelling paradigm to achieve significant QI results. The framework is simple yet directly aligns with the IOM domains of quality. It has inspired and helped actively engage hospital personnel in the work required to achieve the goals and vision of the hospital system. Five years after initiating this type of plan, activity is flourishing in each of the domains and midterm results are substantial. We think that the nature of this strategic plan has been an important aspect of our success to date.

  13. Inulin significantly improves serum magnesium levels in proton pump inhibitor-induced hypomagnesaemia.

    Science.gov (United States)

    Hess, M W; de Baaij, J H F; Broekman, M; Bisseling, T M; Haarhuis, B; Tan, A; Te Morsche, R; Hoenderop, J G J; Bindels, R J M; Drenth, J P H

    2016-06-01

    Proton pump inhibitors (PPI) are among the most widely prescribed drugs to treat gastric acid-related disorders. PPI-induced hypomagnesaemia, a defect in intestinal absorption of Mg(2+) , can be a severe side effect of chronic PPI use. To restore serum Mg(2+) concentrations in PPI-induced hypomagnesaemia patients by dietary supplementation with inulin fibres. Eleven patients with PPI-induced hypomagnesaemia and 10 controls were treated with inulin (20 g/day). Each trial consisted of two cycles of 14-day inulin treatment followed by a washout period of 14 days. Patients continued to use their PPI. Serum Mg(2+) levels served as the primary endpoint. Inulin significantly enhanced serum Mg(2+) levels from 0.60 to 0.68 mmol/L in PPI-induced hypomagnesaemia patients, and from 0.84 to 0.93 mmol/L in controls. As a consequence 24 h urinary Mg(2+) excretion was significantly increased in patients with PPI-induced hypomagnesaemia (0.3-2.2 mmol/day). Symptoms related to hypomagnesaemia, including muscle cramps and paraesthesia, were reduced during intervention with inulin. Inulin increases serum Mg(2+) concentrations under PPI maintenance in patients with PPI-induced hypomagnesaemia. © 2016 John Wiley & Sons Ltd.

  14. Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

    Science.gov (United States)

    Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

    2015-09-01

    Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

  15. Progressive degradation of alloy 690 and the development of a significant improvement in alloy 800CR

    International Nuclear Information System (INIS)

    Staehle, Roger W.; Arioka, Koji; Tapping, Robert

    2015-01-01

    The present most widely used alloys for tubing in steam generators and structural materials in water cooled reactors are Alloy 690 and Alloy 800. However, both alloys, while improved over Alloy 600 may not meet the needs of longer range applications in the range of 80-100 years. Alloy 690 sustains damage resulting from the formation of cavities at grain boundaries which eventually cover about 50% of the area of the grain boundaries with the remainder covering being covered with carbides. The cavities seem to nucleate on the carbides leaving the grain boundaries a structure of cavities and carbides. Such a structure will lead the Alloy 690 to fail completely. Normal Alloy 800 does not produce such cavities and probably retains a large amount of its corrosion resistance but does sustain progressive SCC at low rate. A new alloy, 800CR, has been developed in a collaboration among Arioka, Tapping, and Staehle. This alloy is based on a Cr composition of 23.5-27% with the remainder retaining the previous Alloy 800 composition. 800CR sustains a crack velocity about 100 times less than Alloy 690 and a negligible rate of initiation. The 800CR, alloy is now seeking a patent. (authors)

  16. Study of prognostic significance of antenatal ultrasonography and renin angiotensin system activation in predicting disease severity in posterior urethral valves

    Directory of Open Access Journals (Sweden)

    Divya Bhadoo

    2015-01-01

    Full Text Available Aims: Study on prognostic significance of antenatal ultrasonography and renin angiotensin system activation in predicting disease severity in posterior urethral valves. Materials and Methods: Antenatally diagnosed hydronephrosis patients were included. Postnatally, they were divided into two groups, posterior urethral valve (PUV and non-PUV. The studied parameters were: Gestational age at detection, surgical intervention, ultrasound findings, cord blood and follow up plasma renin activity (PRA values, vesico-ureteric reflux (VUR, renal scars, and glomerular filtration rate (GFR. Results: A total of 25 patients were included, 10 PUV and 15 non-PUV. All infants with PUV underwent primary valve incision. GFR was less than 60 ml/min/1.73 m 2 body surface area in 4 patients at last follow-up. Keyhole sign, oligoamnios, absent bladder cycling, and cortical cysts were not consistent findings on antenatal ultrasound in PUV. Cord blood PRA was significantly higher (P < 0.0001 in PUV compared to non-PUV patients. Gestational age at detection of hydronephrosis, cortical cysts, bladder wall thickness, and amniotic fluid index were not significantly correlated with GFR while PRA could differentiate between poor and better prognosis cases with PUV. Conclusions: Ultrasound was neither uniformly useful in diagnosing PUV antenatally, nor differentiating it from cases with non-PUV hydronephrosis. In congenital hydronephrosis, cord blood PRA was significantly higher in cases with PUV compared to non-PUV cases and fell significantly after valve ablation. Cord blood PRA could distinguish between poor and better prognosis cases with PUV.

  17. 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.

  18. 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

  19. 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.

  20. Significant improvement of pig cloning efficiency by treatment with LBH589 after somatic cell nuclear transfer.

    Science.gov (United States)

    Jin, Jun-Xue; Li, Suo; Gao, Qing-Shan; Hong, Yu; Jin, Long; Zhu, Hai-Ying; Yan, Chang-Guo; Kang, Jin-Dan; Yin, Xi-Jun

    2013-10-01

    The low success rate of animal cloning by somatic cell nuclear transfer (SCNT) associates with epigenetic aberrancy, including the abnormal acetylation of histones. Altering the epigenetic status by histone deacetylase inhibitors (HDACi) enhances the developmental potential of SCNT embryos. In the current study, we examined the effects of LBH589 (panobinostat), a novel broad-spectrum HDACi, on the nuclear reprogramming and development of pig SCNT embryos in vitro. In experiment 1, we compared the in vitro developmental competence of nuclear transfer embryos treated with different concentrations of LBH589. Embryos treated with 50 nM LBH589 for 24 hours showed a significant increase in the rate of blastocyst formation compared with the control or embryos treated with 5 or 500 nM LBH589 (32.4% vs. 11.8%, 12.1%, and 10.0%, respectively, P < 0.05). In experiment 2, we examined the in vitro developmental competence of nuclear transfer embryos treated with 50 nM LBH589 for various intervals after activation and 6-dimethylaminopurine. Embryos treated for 24 hours had higher rates of blastocyst formation than the other groups. In experiment 3, when the acetylation of H4K12 was examined in SCNT embryos treated for 6 hours with 50 nM LBH589 by immunohistochemistry, the staining intensities of these proteins in LBH589-treated SCNT embryos were significantly higher than in the control. In experiment 4, LBH589-treated nuclear transfer and control embryos were transferred into surrogate mothers, resulting in three (100%) and two (66.7%) pregnancies, respectively. In conclusion, LBH589 enhances the nuclear reprogramming and developmental potential of SCNT embryos by altering the epigenetic status and expression, and increasing blastocyst quality. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  1. Silver chlorobromide nanocubes with significantly improved uniformity: synthesis and assembly into photonic crystals

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zheng; Okasinski, John S.; Gosztola, David J.; Ren, Yang; Sun, Yugang

    2015-01-01

    Silver chlorobromide (AgClxBr1-x, 0 < x < 1) nanocubes with a highly uniform size, morphology, and crystallinity have been successfully synthesized through a co-precipitation of Ag+ ions with both Cl- and Br- ions in ethylene glycol containing polyvinyl pyrrolidone at mild temperatures. Compositions of the synthesized nanocubes can be easily tuned by controlling the molar ratio of Cl- to Br- ions in the reaction solutions. The size of the nanocubes is determined by varying a number of parameters including the molar ratio of Cl- to Br- ions, injection rate of Ag+ ions, and reaction temperature. The real-time formation of colloidal AgClxBr1-x nanocubes has been monitored, for the first time, by in situ highenergy synchrotron X-ray diffraction. The time-resolved results reveal that a fast injection rate of Ag+ ions is critical for the formation of AgClxBr1-x nanocubes with a highly pure face-centered cubic crystalline phase. The improved uniformity of the AgClxBr1-x nanocubes is beneficial for assembling them into order superlattices (e.g., photonic crystals) even by simply applying centrifugation forces. The stop band of the resulting photonic crystals can be easily tuned from the ultraviolet to the infrared region by using AgClxBr1-x nanocubes with different sizes. The variation of the dielectric constant of AgClxBr1-x associated with the change of the relative concentration of halide ions provides an additional knob to tune the optical properties of photonic crystals.

  2. The Strasbourg Large Refractor and Dome: Significant Improvements and Failed Attempts

    Science.gov (United States)

    Heck, Andre

    2009-01-01

    Founded by the German Empire in the late 19th century, Strasbourg Astronomical Observatory featured several novelties from the start. According to Mueller (1978), the separation of observing buildings from the study area and from the astronomers' residence was a revolution in observatory construction. The instruments were, as much as possible, isolated from the vibrations of the buildings themselves. "Gas flames" and water were used to reduce temperature effects. Thus the Large Dome (ca 11m diameter), housing the Large Refractor (ca 49cm, then the largest in Germany) and covered by zinc over wood, could be cooled down by water running from the top. Reports (including by the French who took over the observatory after World War I) are however somehow nonexistent on the effective usage and actual efficiency of such a system (which must have generated locally a significant amount of humidity). The paper will detail these technical attempts as well as the specificities of the instruments installed in that new observatory intended as a showcase of German astronomy.

  3. 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%).

  4. Factors Related to Significant Improvement of Estimated Glomerular Filtration Rates in Chronic Hepatitis B Patients Receiving Telbivudine Therapy

    Directory of Open Access Journals (Sweden)

    Te-Fu Lin

    2017-01-01

    Full Text Available Background and Aim. The improvement of estimated glomerular filtration rates (eGFRs in chronic hepatitis B (CHB patients receiving telbivudine therapy is well known. The aim of this study was to clarify the kinetics of eGFRs and to identify the significant factors related to the improvement of eGFRs in telbivudine-treated CHB patients in a real-world setting. Methods. Serial eGFRs were calculated every 3 months using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI equation. The patients were classified as CKD-1, -2, or -3 according to a baseline eGFR of ≥90, 60–89, or <60 mL/min/1.73 m2, respectively. A significant improvement of eGFR was defined as a more than 10% increase from the baseline. Results. A total of 129 patients were enrolled, of whom 36% had significantly improved eGFRs. According to a multivariate analysis, diabetes mellitus (DM (p=0.028 and CKD-3 (p=0.043 were both significantly related to such improvement. The rates of significant improvement of eGFR were about 73% and 77% in patients with DM and CKD-3, respectively. Conclusions. Telbivudine is an alternative drug of choice for the treatment of hepatitis B patients for whom renal safety is a concern, especially patients with DM and CKD-3.

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

    Science.gov (United States)

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

    2017-01-01

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

  6. Omega-3 fatty acid therapy dose-dependently and significantly decreased triglycerides and improved flow-mediated dilation, however, did not significantly improve insulin sensitivity in patients with hypertriglyceridemia.

    Science.gov (United States)

    Oh, Pyung Chun; Koh, Kwang Kon; Sakuma, Ichiro; Lim, Soo; Lee, Yonghee; Lee, Seungik; Lee, Kyounghoon; Han, Seung Hwan; Shin, Eak Kyun

    2014-10-20

    Experimental studies demonstrate that higher intake of omega-3 fatty acids (n-3 FA) improves insulin sensitivity, however, we reported that n-3 FA 2g therapy, most commonly used dosage did not significantly improve insulin sensitivity despite reducing triglycerides by 21% in patients. Therefore, we investigated the effects of different dosages of n-3 FA in patients with hypertriglyceridemia. This was a randomized, single-blind, placebo-controlled, parallel study. Age, sex, and body mass index were matched among groups. All patients were recommended to maintain a low fat diet. Forty-four patients (about 18 had metabolic syndrome/type 2 diabetes mellitus) in each group were given placebo, n-3 FA 1 (O1), 2 (O2), or 4 g (O4), respectively daily for 2 months. n-3 FA therapy dose-dependently and significantly decreased triglycerides and triglycerides/HDL cholesterol and improved flow-mediated dilation, compared with placebo (by ANOVA). However, each n-3 FA therapy did not significantly decrease high-sensitivity C-reactive protein and fibrinogen, compared with placebo. O1 significantly increased insulin levels and decreased insulin sensitivity (determined by QUICKI) and O2 significantly decreased plasma adiponectin levels relative to baseline measurements. Of note, when compared with placebo, each n-3 FA therapy did not significantly change insulin, glucose, adiponectin, glycated hemoglobin levels and insulin sensitivity (by ANOVA). We observed similar results in a subgroup of patients with the metabolic syndrome. n-3 FA therapy dose-dependently and significantly decreased triglycerides and improved flow-mediated dilation. Nonetheless, n-3 FA therapy did not significantly improve acute-phase reactants and insulin sensitivity in patients with hypertriglyceridemia, regardless of dosages. Copyright © 2014. Published by Elsevier Ireland Ltd.

  7. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...

  8. Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Duan, X-Y.; Wang, W.; Li, M.; Li, Y.; Guo, Y-M. [PET-CT Center, The First Affiliated Hospital of Xi' an, Jiaotong University, Xi' an, Shaanxi (China)

    2015-02-03

    {sup 18}F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. {sup 18}F-FDG PET/CT scans were performed and different SUV parameters (SUV{sub max}, SUV{sub avg}, SUV{sub T/L}, and SUV{sub T/A}) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUV{sub max}, SUV{sub avg}, and SUV{sub T/L} of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUV{sub T/L} was the primary predictor for tumor differentiation. However, in adenocarcinoma, SUV{sub max} was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUV{sub T/L} appeared to be most useful overall, but SUV{sub max} was the best index for adenocarcinoma tumor differentiation.

  9. Applying a health action model to predict and improve healthy behaviors in coal miners.

    Science.gov (United States)

    Vahedian-Shahroodi, Mohammad; Tehrani, Hadi; Mohammadi, Faeze; Gholian-Aval, Mahdi; Peyman, Nooshin

    2018-05-01

    One of the most important ways to prevent work-related diseases in occupations such as mining is to promote healthy behaviors among miners. This study aimed to predict and promote healthy behaviors among coal miners by using a health action model (HAM). The study was conducted on 200 coal miners in Iran in two steps. In the first step, a descriptive study was implemented to determine predictive constructs and effectiveness of HAM on behavioral intention. The second step involved a quasi-experimental study to determine the effect of an HAM-based education intervention. This intervention was implemented by the researcher and the head of the safety unit based on the predictive construct specified in the first step over 12 sessions of 60 min. The data was collected using an HAM questionnaire and a checklist of healthy behavior. The results of the first step of the study showed that attitude, belief, and normative constructs were meaningful predictors of behavioral intention. Also, the results of the second step revealed that the mean score of attitude and behavioral intention increased significantly after conducting the intervention in the experimental group, while the mean score of these constructs decreased significantly in the control group. The findings of this study showed that HAM-based educational intervention could improve the healthy behaviors of mine workers. Therefore, it is recommended to extend the application of this model to other working groups to improve healthy behaviors.

  10. Prediction and moderation of improvement in cognitive-behavioral and psychodynamic psychotherapy for panic disorder.

    Science.gov (United States)

    Chambless, Dianne L; Milrod, Barbara; Porter, Eliora; Gallop, Robert; McCarthy, Kevin S; Graf, Elizabeth; Rudden, Marie; Sharpless, Brian A; Barber, Jacques P

    2017-08-01

    To identify variables predicting psychotherapy outcome for panic disorder or indicating which of 2 very different forms of psychotherapy-panic-focused psychodynamic psychotherapy (PFPP) or cognitive-behavioral therapy (CBT)-would be more effective for particular patients. Data were from 161 adults participating in a randomized controlled trial (RCT) including these psychotherapies. Patients included 104 women; 118 patients were White, 33 were Black, and 10 were of other races; 24 were Latino(a). Predictors/moderators measured at baseline or by Session 2 of treatment were used to predict change on the Panic Disorder Severity Scale (PDSS). Higher expectancy for treatment gains (Credibility/Expectancy Questionnaire d = -1.05, CI 95% [-1.50, -0.60]), and later age of onset (d = -0.65, CI 95% [-0.98, -0.32]) were predictive of greater change. Both variables were also significant moderators: patients with low expectancy of improvement improved significantly less in PFPP than their counterparts in CBT, whereas this was not the case for patients with average or high levels of expectancy. When patients had an onset of panic disorder later in life (≥27.5 years old), they fared as well in PFPP as CBT. In contrast, at low and mean levels of onset age, CBT was the more effective treatment. Predictive variables suggest possibly fruitful foci for improvement of treatment outcome. In terms of moderation, CBT was the more consistently effective treatment, but moderators identified some patients who would do as well in PFPP as in CBT, thereby widening empirically supported options for treatment of this disorder. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Using AIRS retrievals in the WRF-LETKF system to improve regional numerical weather prediction

    Directory of Open Access Journals (Sweden)

    Takemasa Miyoshi

    2012-09-01

    Full Text Available In addition to conventional observations, atmospheric temperature and humidity profile data from the Atmospheric Infrared Sounder (AIRS Version 5 retrieval products are assimilated into the Weather Research and Forecasting (WRF model, using the local ensemble transform Kalman filter (LETKF. Although a naive assimilation of all available quality-controlled AIRS retrieval data yields an inferior analysis, the additional enhancements of adaptive inflation and horizontal data thinning result in a general improvement of numerical weather prediction skill due to AIRS data. In particular, the adaptive inflation method is enhanced so that it no longer assumes temporal homogeneity of the observing network and allows for a better treatment of the temporally inhomogeneous AIRS data. Results indicate that the improvements due to AIRS data are more significant in longer-lead forecasts. Forecasts of Typhoons Sinlaku and Jangmi in September 2008 show improvements due to AIRS data.

  16. Clinical and angiographic predictors of haemodynamically significant angiographic lesions: development and validation of a risk score to predict positive fractional flow reserve.

    Science.gov (United States)

    Sareen, Nishtha; Baber, Usman; Kezbor, Safwan; Sayseng, Sonny; Aquino, Melissa; Mehran, Roxana; Sweeny, Joseph; Barman, Nitin; Kini, Annapoorna; Sharma, Samin K

    2017-04-07

    Coronary revascularisation based upon physiological evaluation of lesions improves clinical outcomes. Angiographic or visual stenosis assessment alone is insufficient in predicting haemodynamic stenosis severity by fractional flow reserve (FFR) and therefore cannot be used to guide revascularisation, particularly in the lesion subset system formulated. Of 1,023 consecutive lesions (883 patients), 314 (31%) were haemodynamically significant. Characteristics associated with FFR ≤0.8 include male gender, higher SYNTAX score, lesions ≥20 mm, stenosis >50%, bifurcation, calcification, absence of tortuosity and smaller reference diameter. A user-friendly integer score was developed with the five variables demonstrating the strongest association. On prospective validation (in 279 distinct lesions), the increasing value of the score correlated well with increasing haemodynamic significance (C-statistic 0.85). We identified several clinical and angiographic characteristics and formulated a scoring system to guide the approach to intermediate lesions. This may translate into cost savings. Larger studies with prospective validation are required to confirm our results.

  17. Improving MJO Prediction and Simulation Using AGCM Coupled Ocean Model with Refined Vertical Resolution

    Science.gov (United States)

    Tu, Chia-Ying; Tseng, Wan-Ling; Kuo, Pei-Hsuan; Lan, Yung-Yao; Tsuang, Ben-Jei; Hsu, Huang-Hsiung

    2017-04-01

    Precipitation in Taiwan area is significantly influenced by MJO (Madden-Julian Oscillation) in the boreal winter. This study is therefore conducted by toggling the MJO prediction and simulation with a unique model structure. The one-dimensional TKE (Turbulence Kinetic Energy) type ocean model SIT (Snow, Ice, Thermocline) with refined vertical resolution near surface is able to resolve cool skin, as well as diurnal warm layer. SIT can simulate accurate SST and hence give precise air-sea interaction. By coupling SIT with ECHAM5 (MPI-Meteorology), CAM5 (NCAR) and HiRAM (GFDL), the MJO simulations in 20-yrs climate integrations conducted by three SIT-coupled AGCMs are significant improved comparing to those driven by prescribed SST. The horizontal resolutions in ECHAM5, CAM5 and HiRAM are 2-deg., 1-deg and 0.5-deg., respectively. This suggests that the improvement of MJO simulation by coupling SIT is AGCM-resolution independent. This study further utilizes HiRAM coupled SIT to evaluate its MJO forecast skill. HiRAM has been recognized as one of the best model for seasonal forecasts of hurricane/typhoon activity (Zhao et al., 2009; Chen & Lin, 2011; 2013), but was not as successful in MJO forecast. The preliminary result of the HiRAM-SIT experiment during DYNAMO period shows improved success in MJO forecast. These improvements of MJO prediction and simulation in both hindcast experiments and climate integrations are mainly from better-simulated SST diurnal cycle and diurnal amplitude, which is contributed by the refined vertical resolution near ocean surface in SIT. Keywords: MJO Predictability, DYNAMO

  18. TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

    International Nuclear Information System (INIS)

    Krafft, S; Briere, T; Court, L; Martel, M

    2015-01-01

    Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. A total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP

  19. 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…

  20. 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…

  1. 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.

  2. 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 ...

  3. 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.

  4. 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...

  5. 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...

  6. 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

  7. Mid-Treatment Sleep Duration Predicts Clinically Significant Knee Osteoarthritis Pain reduction at 6 months: Effects From a Behavioral Sleep Medicine Clinical Trial.

    Science.gov (United States)

    Salwen, Jessica K; Smith, Michael T; Finan, Patrick H

    2017-02-01

    To determine the relative influence of sleep continuity (sleep efficiency, sleep onset latency, total sleep time [TST], and wake after sleep onset) on clinical pain outcomes within a trial of cognitive behavioral therapy for insomnia (CBT-I) for patients with comorbid knee osteoarthritis and insomnia. Secondary analyses were performed on data from 74 patients with comorbid insomnia and knee osteoarthritis who completed a randomized clinical trial of 8-session multicomponent CBT-I versus an active behavioral desensitization control condition (BD), including a 6-month follow-up assessment. Data used herein include daily diaries of sleep parameters, actigraphy data, and self-report questionnaires administered at specific time points. Patients who reported at least 30% improvement in self-reported pain from baseline to 6-month follow-up were considered responders (N = 31). Pain responders and nonresponders did not differ significantly at baseline across any sleep continuity measures. At mid-treatment, only TST predicted pain response via t tests and logistic regression, whereas other measures of sleep continuity were nonsignificant. Recursive partitioning analyses identified a minimum cut-point of 382 min of TST achieved at mid-treatment in order to best predict pain improvements 6-month posttreatment. Actigraphy results followed the same pattern as daily diary-based results. Clinically significant pain reductions in response to both CBT-I and BD were optimally predicted by achieving approximately 6.5 hr sleep duration by mid-treatment. Thus, tailoring interventions to increase TST early in treatment may be an effective strategy to promote long-term pain reductions. More comprehensive research on components of behavioral sleep medicine treatments that contribute to pain response is warranted. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  8. Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

    2018-02-01

    Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

  9. 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

  10. 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

  11. 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...

  12. 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.

  13. Merging economics and epidemiology to improve the prediction and management of infectious disease.

    Science.gov (United States)

    Perrings, Charles; Castillo-Chavez, Carlos; Chowell, Gerardo; Daszak, Peter; Fenichel, Eli P; Finnoff, David; Horan, Richard D; Kilpatrick, A Marm; Kinzig, Ann P; Kuminoff, Nicolai V; Levin, Simon; Morin, Benjamin; Smith, Katherine F; Springborn, Michael

    2014-12-01

    Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as "economic epidemiology" or "epidemiological economics," the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.

  14. Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

    Science.gov (United States)

    Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

    2018-04-16

    Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

  15. Preoperative Metabolic Syndrome Is Predictive of Significant Gastric Cancer Mortality after Gastrectomy: The Fujian Prospective Investigation of Cancer (FIESTA Study

    Directory of Open Access Journals (Sweden)

    Dan Hu

    2017-02-01

    Full Text Available Metabolic syndrome (MetS has been shown to be associated with an increased risk of gastric cancer. However, the impact of MetS on gastric cancer mortality remains largely unknown. Here, we prospectively examined the prediction of preoperative MetS for gastric cancer mortality by analyzing a subset of data from the ongoing Fujian prospective investigation of cancer (FIESTA study. This study was conducted among 3012 patients with gastric cancer who received radical gastrectomy between 2000 and 2010. The latest follow-up was completed in 2015. Blood/tissue specimens, demographic and clinicopathologic characteristics were collected at baseline. During 15-year follow-up, 1331 of 3012 patients died of gastric cancer. The median survival time (MST of patients with MetS was 31.3 months, which was significantly shorter than that of MetS-free patients (157.1 months. The coexistence of MetS before surgery was associated with a 2.3-fold increased risk for gastric cancer mortality (P < 0.001. The multivariate-adjusted hazard ratios (HRs were increased with invasion depth T1/T2 (HR = 2.78, P < 0.001, regional lymph node metastasis N0 (HR = 2.65, P < 0.001, positive distant metastasis (HR = 2.53, P < 0.001, TNM stage I/II (HR = 3.00, P < 0.001, intestinal type (HR = 2.96, P < 0.001, negative tumor embolus (HR = 2.34, P < 0.001, and tumor size ≤4.5 cm (HR = 2.49, P < 0.001. Further survival tree analysis confirmed the top splitting role of TNM stage, followed by MetS or hyperglycemia with remarkable discrimination ability. In this large cohort study, preoperative MetS, especially hyperglycemia, was predictive of significant gastric cancer mortality in patients with radical gastrectomy, especially for early stage of gastric cancer.

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

    Science.gov (United States)

    Troch, Peter A.

    2017-04-01

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

  17. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    International Nuclear Information System (INIS)

    Rattá, G.A.; Vega, J.; Murari, A.

    2012-01-01

    Highlights: ► A new signal selection methodology to improve disruption prediction is reported. ► The approach is based on Genetic Algorithms. ► An advanced predictor has been created with the new set of signals. ► The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called “Advanced Predictor Of Disruptions” (APODIS), developed for the “Joint European Torus” (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals’ parameters in order to maximize the performance of the predictor is reported. The approach is based on “Genetic Algorithms” (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  18. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    Energy Technology Data Exchange (ETDEWEB)

    Ratta, G.A., E-mail: garatta@gateme.unsj.edu.ar [GATEME, Facultad de Ingenieria, Universidad Nacional de San Juan, Avda. San Martin 1109 (O), 5400 San Juan (Argentina); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 40, 28040 Madrid (Spain); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Murari, A. [Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova (Italy); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer A new signal selection methodology to improve disruption prediction is reported. Black-Right-Pointing-Pointer The approach is based on Genetic Algorithms. Black-Right-Pointing-Pointer An advanced predictor has been created with the new set of signals. Black-Right-Pointing-Pointer The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called 'Advanced Predictor Of Disruptions' (APODIS), developed for the 'Joint European Torus' (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals' parameters in order to maximize the performance of the predictor is reported. The approach is based on 'Genetic Algorithms' (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  19. Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs

    International Nuclear Information System (INIS)

    Yang, Jing; Li, Yuan-Yuan; Li, Yi-Xue; Ye, Zhi-Qiang

    2012-01-01

    Highlights: ► Proper dataset partition can improve the prediction of deleterious nsSNPs. ► Partition according to original residue type at nsSNP is a good criterion. ► Similar strategy is supposed promising in other machine learning problems. -- Abstract: Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid type at the nsSNP site. Using support vector machine (SVM), training classification models on each subset resulted in an overall accuracy of 76.3% or 74.9% depending on the two different partition criteria, while training on the whole dataset obtained an accuracy of only 72.6%. Moreover, the dataset was also randomly divided into 20 subsets, but the corresponding accuracy was only 73.2%. Our results demonstrated that partitioning the whole training dataset into subsets properly, i.e., according to the residue type at the nsSNP site, will improve the performance of the trained classifiers significantly, which should be valuable in developing better tools for predicting the disease-association of nsSNPs.

  20. Improving rational thermal comfort prediction by using subpopulation characteristics: A case study at Hermitage Amsterdam.

    Science.gov (United States)

    Kramer, Rick; Schellen, Lisje; Schellen, Henk; Kingma, Boris

    2017-01-01

    This study aims to improve the prediction accuracy of the rational standard thermal comfort model, known as the Predicted Mean Vote (PMV) model, by (1) calibrating one of its input variables "metabolic rate," and (2) extending it by explicitly incorporating the variable running mean outdoor temperature (RMOT) that relates to adaptive thermal comfort. The analysis was performed with survey data ( n = 1121) and climate measurements of the indoor and outdoor environment from a one year-long case study undertaken at Hermitage Amsterdam museum in the Netherlands. The PMVs were calculated for 35 survey days using (1) an a priori assumed metabolic rate, (2) a calibrated metabolic rate found by fitting the PMVs to the thermal sensation votes (TSVs) of each respondent using an optimization routine, and (3) extending the PMV model by including the RMOT. The results show that the calibrated metabolic rate is estimated to be 1.5 Met for this case study that was predominantly visited by elderly females. However, significant differences in metabolic rates have been revealed between adults and elderly showing the importance of differentiating between subpopulations. Hence, the standard tabular values, which only differentiate between various activities, may be oversimplified for many cases. Moreover, extending the PMV model with the RMOT substantially improves the thermal sensation prediction, but thermal sensation toward extreme cool and warm sensations remains partly underestimated.

  1. Improved prediction for the mass of the W boson in the NMSSM

    International Nuclear Information System (INIS)

    Staal, O.; Zeune, L.

    2015-10-01

    Electroweak precision observables, being highly sensitive to loop contributions of new physics, provide a powerful tool to test the theory and to discriminate between different models of the underlying physics. In that context, the W boson mass, M W , plays a crucial role. The accuracy of the M W measurement has been significantly improved over the last years, and further improvement of the experimental accuracy is expected from future LHC measurements. In order to fully exploit the precise experimental determination, an accurate theoretical prediction for M W in the Standard Model (SM) and extensions of it is of central importance. We present the currently most accurate prediction for the W boson mass in the Next-to-Minimal Supersymmetric extension of the Standard Model (NMSSM), including the full one-loop result and all available higher-order corrections of SM and SUSY type. The evaluation of M W is performed in a flexible framework, which facilitates the extension to other models beyond the SM. We show numerical results for the W boson mass in the NMSSM, focussing on phenomenologically interesting scenarios, in which the Higgs signal can be interpreted as the lightest or second lightest CP-even Higgs boson of the NMSSM. We find that, for both Higgs signal interpretations, the NMSSM M W prediction is well compatible with the measurement. We study the SUSY contributions to M W in detail and investigate in particular the genuine NMSSM effects from the Higgs and neutralino sectors.

  2. Natalizumab Significantly Improves Cognitive Impairment over Three Years in MS: Pattern of Disability Progression and Preliminary MRI Findings.

    Directory of Open Access Journals (Sweden)

    Flavia Mattioli

    Full Text Available Previous studies reported that Multiple Sclerosis (MS patients treated with natalizumab for one or two years exhibit a significant reduction in relapse rate and in cognitive impairment, but the long term effects on cognitive performance are unknown. This study aimed to evaluate the effects of natalizumab on cognitive impairment in a cohort of 24 consecutive patients with relapsing remitting MS treated for 3 years. The neuropsychological tests, as well as relapse number and EDSS, were assessed at baseline and yearly for three years. The impact on cortical atrophy was also considered in a subgroup of them, and are thus to be considered as preliminary. Results showed a significant reduction in the number of impaired neuropsychological tests after three years, a significant decrease in annualized relapse rate at each time points compared to baseline and a stable EDSS. In the neuropsychological assessment, a significant improvement in memory, attention and executive function test scores was detected. Preliminary MRI data show that, while GM volume did not change at 3 years, a significantly greater parahippocampal and prefrontal gray matter density was noticed, the former correlating with neuropsychological improvement in a memory test. This study showed that therapy with Natalizumab is helpful in improving cognitive performance, and is likely to have a protective role on grey matter, over a three years follow-up.

  3. Validation of DAB2IP methylation and its relative significance in predicting outcome in renal cell carcinoma

    Science.gov (United States)

    Zhao, Liang-Yun; Kapur, Payal; Wu, Kai-Jie; Wang, Bin; Yu, Yan-Hong; Liao, Bing; He, Da-Lin; Chen, Wei; Margulis, Vitaly; Hsieh, Jer-Tsong; Luo, Jun-Hang

    2016-01-01

    We have recently reported tumor suppressive role of DAB2IP in RCC development. In this study, We identified one CpG methylation biomarker (DAB2IP CpG1) located UTSS of DAB2IP that was associated with poor overall survival in a cohort of 318 ccRCC patients from the Cancer Genome Atlas (TCGA). We further validated the prognostic accuracy of DAB2IP CpG methylation by pyrosequencing quantitative methylation assay in 224 ccRCC patients from multiple Chinese centers (MCHC set), and 239 patients from University of Texas Southwestern Medical Center at Dallas (UTSW set) by using FFPE samples. DAB2IP CpG1 can predict the overall survival of patients in TCGA, MCHC, and UTSW sets independent of patient age, Fuhrman grade and TNM stage (all p<0.05). DAB2IP CpG1 successfully categorized patients into high-risk and low-risk groups with significant differences of clinical outcome in respective clinical subsets, regardless of age, sex, grade, stage, or race (HR: 1.63-7.83; all p<0.05). The detection of DAB2IP CpG1 methylation was minimally affected by ITH in ccRCC. DAB2IP mRNA expression was regulated by DNA methylation in vitro. DAB2IP CpG1 methylation is a practical and repeatable biomarker for ccRCC, which can provide prognostic value that complements the current staging system. PMID:27129174

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

    Science.gov (United States)

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

    2017-07-01

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

  5. 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

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

    Science.gov (United States)

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

    2017-12-01

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

  7. 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…

  8. 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

  9. Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-10-01

    Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.

  10. 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....

  11. 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

  12. Triaging TIA/minor stroke patients using the ABCD2 score does not predict those with significant carotid disease.

    Science.gov (United States)

    Walker, J; Isherwood, J; Eveson, D; Naylor, A R

    2012-05-01

    'Rapid Access' TIA Clinics use the ABCD(2) score to triage patients as it is not possible to see everyone with a suspected TIA TIA/minor stroke or 'carotid territory' TIA/minor stroke. Between 1.10.2008 and 31.04.2011, 2452 patients were referred to the Leicester Rapid Access TIA Service. After Stroke Physician review, 1273 (52%) were thought to have suffered a minor stroke/TIA. Of these, both FD/ED referrer and Specialist Stroke Consultant ABCD(2) scores and carotid Duplex ultrasound studies were available for 843 (66%). The yield for identifying a ≥50% stenosis or carotid occlusion was 109/843 (12.9%) in patients with 'any territory' TIA/minor stroke and 101/740 (13.6%) in those with a clinical diagnosis of 'carotid territory' TIA/minor stroke. There was no association between ABCD(2) score and the likelihood of encountering significant carotid disease and analyses of the area under the receiver operating characteristic curve (AUC) for FD/ED referrer and stroke specialist ABCD(2) scores showed no prediction of carotid stenosis (FD/ED: AUC 0.50 (95%CI 0.44-0.55, p = 0.9), Specialist: AUC 0.51 (95%CI 0.45-0.57, p = 0.78). The ABCD(2) score was unable to identify TIA/minor stroke patients with a higher prevalence of clinically important ipsilateral carotid disease. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

  13. Significant clinical improvement in radiation-induced lumbosacral poly-radiculopathy by a treatment combining pentoxifylline, tocopherol, and clodronate (Pentoclo)

    Energy Technology Data Exchange (ETDEWEB)

    Delanian, S. [Hop St Louis, Serv Oncol Radiotherapie, APHP, F-75010 Paris, (France); Lefaix, J.L. [CEA-LARIA, CIRIL-GANIL, Caen, (France); Maisonobe, T. [Hop La Pitie Salpetriere, Federat Neurophysiol Clin, APHP, Paris, (France)

    2008-07-01

    Radiation-induced (RI) peripheral neuropathy is a rare and severe delayed complication of radiotherapy that is spontaneously irreversible, with no standard of treatment. We previously developed a successful antioxidant treatment in RI fibrosis and necrosis. Two patients with progressive worsening RI lumbosacral poly-radiculopathy experienced over several years a significant clinical improvement in their neurological sensorimotor symptoms with long-term pentoxifylline-tocopherol-clodronate treatment, and good safety. (authors)

  14. The cumulative effect of small dietary changes may significantly improve nutritional intakes in free-living children and adults

    OpenAIRE

    Bornet , Francis; Paineau , Damien; Beaufils , François; Boulier , Alain; Cassuto , Dominique-Adèle; Chwalow , Judith; Combris , Pierre; Couet , Charles; Jouret , Béatrice; Lafay , Lionel; Laville , Martine; Mahé , Sylvain; Ricour , Claude; Romon , Monique; Simon , Chantal

    2010-01-01

    Abstract Background/Objectives: The ELPAS study was an 8-month randomized controlled dietary modification trial designed to test the hypothesis that family dietary coaching would improve nutritional intakes and weight control in 2026 free-living children and parents (Paineau et al., 2008). It resulted in significant nutritional changes, with beneficial effects on body mass index in adults. In these ancillary analyses, we investigated dietary changes throughout the intervention. ...

  15. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

    Science.gov (United States)

    Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-03-01

    Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  16. Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

    Science.gov (United States)

    Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

    2017-01-01

    The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit

  17. 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.

  18. 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

  19. Acid or erythromycin stress significantly improves transformation efficiency through regulating expression of DNA binding proteins in Lactococcus lactis F44.

    Science.gov (United States)

    Wang, Binbin; Zhang, Huawei; Liang, Dongmei; Hao, Panlong; Li, Yanni; Qiao, Jianjun

    2017-12-01

    Lactococcus lactis is a gram-positive bacterium used extensively in the dairy industry and food fermentation, and its biological characteristics are usually improved through genetic manipulation. However, poor transformation efficiency was the main restriction factor for the construction of engineered strains. In this study, the transformation efficiency of L. lactis F44 showed a 56.1-fold increase in acid condition (pH 5.0); meanwhile, erythromycin stress (0.04 μg/mL) promoted the transformation efficiency more significantly (76.9-fold). Notably, the transformation efficiency of F44e (L. lactis F44 harboring empty pLEB124) increased up to 149.1-fold under the synergistic stresses of acid and erythromycin. In addition, the gene expression of some DNA binding proteins (DprA, RadA, RadC, RecA, RecQ, and SsbA) changed correspondingly. Especially for radA, 25.1-fold improvement was detected when F44e was exposed to pH 5.0. Overexpression of some DNA binding proteins could improve the transformation efficiency. The results suggested that acid or erythromycin stress could improve the transformation efficiency of L. lactis through regulating gene expression of DNA binding proteins. We have proposed a simple but promising strategy for improving the transformation efficiency of L. lactis and other hard-transformed microorganisms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  20. Comparison of measured and predicted thermal mixing tests using improved finite difference technique

    International Nuclear Information System (INIS)

    Hassan, Y.A.; Rice, J.G.; Kim, J.H.

    1983-01-01

    The numerical diffusion introduced by the use of upwind formulations in the finite difference solution of the flow and energy equations for thermal mixing problems (cold water injection after small break LOCA in a PWR) was examined. The relative importance of numerical diffusion in the flow equations, compared to its effect on the energy equation was demonstrated. The flow field equations were solved using both first order accurate upwind, and second order accurate differencing schemes. The energy equation was treated using the conventional upwind and a mass weighted skew upwind scheme. Results presented for a simple test case showed that, for thermal mixing problems, the numerical diffusion was most significant in the energy equation. The numerical diffusion effect in the flow field equations was much less significant. A comparison of predictions using the skew upwind and the conventional upwind with experimental data from a two dimensional thermal mixing text are presented. The use of the skew upwind scheme showed a significant improvement in the accuracy of the steady state predicted temperatures. (orig./HP)

  1. 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.

  2. 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...

  3. 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

  4. MEMS based shock pulse detection sensor for improved rotary Stirling cooler end of life prediction

    Science.gov (United States)

    Hübner, M.; Münzberg, M.

    2018-05-01

    The widespread use of rotary Stirling coolers in high performance thermal imagers used for critical 24/7 surveillance tasks justifies any effort to significantly enhance the reliability and predictable uptime of those coolers. Typically the lifetime of the whole imaging device is limited due to continuous wear and finally failure of the rotary compressor of the Stirling cooler, especially due to failure of the comprised bearings. MTTF based lifetime predictions, even based on refined MTTF models taking operational scenario dependent scaling factors into account, still lack in precision to forecast accurately the end of life (EOL) of individual coolers. Consequently preventive maintenance of individual coolers to avoid failures of the main sensor in critical operational scenarios are very costly or even useless. We have developed an integrated test method based on `Micro Electromechanical Systems', so called MEMS sensors, which significantly improves the cooler EOL prediction. The recently commercially available MEMS acceleration sensors have mechanical resonance frequencies up to 50 kHz. They are able to detect solid borne shock pulses in the cooler structure, originating from e.g. metal on metal impacts driven by periodical forces acting on moving inner parts of the rotary compressor within wear dependent slack and play. The impact driven transient shock pulse analyses uses only the high frequency signal <10kHz and differs therefore from the commonly used broadband low frequencies vibrational analysis of reciprocating machines. It offers a direct indicator of the individual state of wear. The predictive cooler lifetime model based on the shock pulse analysis is presented and results are discussed.

  5. 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

  6. An initiative to improve the management of clinically significant test results in a large health care network.

    Science.gov (United States)

    Roy, Christopher L; Rothschild, Jeffrey M; Dighe, Anand S; Schiff, Gordon D; Graydon-Baker, Erin; Lenoci-Edwards, Jennifer; Dwyer, Cheryl; Khorasani, Ramin; Gandhi, Tejal K

    2013-11-01

    The failure of providers to communicate and follow up clinically significant test results (CSTR) is an important threat to patient safety. The Massachusetts Coalition for the Prevention of Medical Errors has endorsed the creation of systems to ensure that results can be received and acknowledged. In 2008 a task force was convened that represented clinicians, laboratories, radiology, patient safety, risk management, and information systems in a large health care network with the goals of providing recommendations and a road map for improvement in the management of CSTR and of implementing this improvement plan during the sub-force sequent five years. In drafting its charter, the task broadened the scope from "critical" results to "clinically significant" ones; clinically significant was defined as any result that requires further clinical action to avoid morbidity or mortality, regardless of the urgency of that action. The task force recommended four key areas for improvement--(1) standardization of policies and definitions, (2) robust identification of the patient's care team, (3) enhanced results management/tracking systems, and (4) centralized quality reporting and metrics. The task force faced many challenges in implementing these recommendations, including disagreements on definitions of CSTR and on who should have responsibility for CSTR, changes to established work flows, limitations of resources and of existing information systems, and definition of metrics. This large-scale effort to improve the communication and follow-up of CSTR in a health care network continues with ongoing work to address implementation challenges, refine policies, prepare for a new clinical information system platform, and identify new ways to measure the extent of this important safety problem.

  7. The SGLT2 Inhibitor Dapagliflozin Significantly Improves the Peripheral Microvascular Endothelial Function in Patients with Uncontrolled Type 2 Diabetes Mellitus.

    Science.gov (United States)

    Sugiyama, Seigo; Jinnouchi, Hideaki; Kurinami, Noboru; Hieshima, Kunio; Yoshida, Akira; Jinnouchi, Katsunori; Nishimura, Hiroyuki; Suzuki, Tomoko; Miyamoto, Fumio; Kajiwara, Keizo; Jinnouchi, Tomio

    2018-03-30

    Objective Sodium-glucose cotransporter-2 (SGLT2) inhibitors reduce cardiovascular events and decrease the body fat mass in patients with type 2 diabetes mellitus (T2DM). We examined whether or not the SGLT2-inhibitor dapagliflozin can improve the endothelial function associated with a reduction in abdominal fat mass. Methods We prospectively recruited patients with uncontrolled (hemoglobin A1c [HbA1c] >7.0%) T2DM who were not being treated by SGLT2 inhibitors. Patients were treated with add-on dapagliflozin (5 mg/day) or non-SGLT2 inhibitor medicines for 6 months to improve their HbA1c. We measured the peripheral microvascular endothelial function as assessed by reactive hyperemia peripheral arterial tonometry (RH-PAT) and calculated the natural logarithmic transformed value of the RH-PAT index (LnRHI). We then investigated changes in the LnRHI and abdominal fat area using computed tomography (CT). Results The subjects were 54 patients with uncontrolled T2DM (72.2% men) with a mean HbA1c of 8.1%. The HbA1c was significantly decreased in both groups, with no significant difference between the groups. Dapagliflozin treatment, but not non-SGLT2 inhibitor treatment, significantly increased the LnRHI. The changes in the LnRHI were significantly greater in the dapagliflozin group than in the non-SGLT2 inhibitor group. Dapagliflozin treatment, but not non-SGLT2 inhibitor treatment, significantly decreased the abdominal visceral fat area, subcutaneous fat area (SFA), and total fat area (TFA) as assessed by CT and significantly increased the plasma adiponectin levels. The percentage changes in the LnRHI were significantly correlated with changes in the SFA, TFA, systolic blood pressure, and adiponectin. Conclusion Add-on treatment with dapagliflozin significantly improves the glycemic control and endothelial function associated with a reduction in the abdominal fat mass in patients with uncontrolled T2DM.

  8. An improved model to predict nonuniform deformation of Zr-2.5 Nb pressure tubes

    International Nuclear Information System (INIS)

    Lei, Q.M.; Fan, H.Z.

    1997-01-01

    Present circular pressure-tube ballooning models in most fuel channel codes assume that the pressure tube remains circular during ballooning. This model provides adequate predictions of pressure-tube ballooning behaviour when the pressure tube (PT) and the calandria tube (CT) are concentric and when a small (<100 degrees C) top-to-bottom circumferential temperature gradient is present on the pressure tube. However, nonconcentric ballooning is expected to occur under certain postulated CANDU (CANada Deuterium Uranium) accident conditions. This circular geometry assumption prevents the model from accurately predicting nonuniform pressure-tube straining and local PT/CT contact when the pressure tube is subjected to a large circumferential temperature gradient and consequently deforms in a noncircular pattern. This paper describes an improved model that predicts noncircular pressure-tube deformation. Use of this model (once fully validated) will reduce uncertainties in the prediction of pressure-tube ballooning during a postulated loss-of-coolant accident (LOCA) in a CANDU reactor. The noncircular deformation model considers a ring or cross-section of a pressure tube with unit axial length to calculate deformation in the radial and circumferential directions. The model keeps track of the thinning of the pressure-tube wall as well as the shape deviation from a reference circle. Such deviation is expressed in a cosine Fourier series for the lateral symmetry case. The coefficients of the series for the first m terms are calculated by solving a set of algebraic equations at each time step. The model also takes into account the effects of pressure-tube sag or bow on ballooning, using an input value of the offset distance between the centre of the calandria tube and the initial centre of the pressure tube for determining the position radius of the pressure tube. One significant improvement realized in using the noncircular deformation model is a more accurate prediction in

  9. 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

  10. Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry.

    Science.gov (United States)

    Mozer, M C; Wolniewicz, R; Grimes, D B; Johnson, E; Kaushansky, H

    2000-01-01

    Competition in the wireless telecommunications industry is fierce. To maintain profitability, wireless carriers must control churn, which is the loss of subscribers who switch from one carrier to another.We explore techniques from statistical machine learning to predict churn and, based on these predictions, to determine what incentives should be offered to subscribers to improve retention and maximize profitability to the carrier. The techniques include logit regression, decision trees, neural networks, and boosting. Our experiments are based on a database of nearly 47,000 U.S. domestic subscribers and includes information about their usage, billing, credit, application, and complaint history. Our experiments show that under a wide variety of assumptions concerning the cost of intervention and the retention rate resulting from intervention, using predictive techniques to identify potential churners and offering incentives can yield significant savings to a carrier. We also show the importance of a data representation crafted by domain experts. Finally, we report on a real-world test of the techniques that validate our simulation experiments.

  11. EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

    Science.gov (United States)

    Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

    2018-04-24

    Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

  12. 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.

  13. Spontaneous Resolution of Long-Standing Macular Detachment due to Optic Disc Pit with Significant Visual Improvement.

    Science.gov (United States)

    Parikakis, Efstratios A; Chatziralli, Irini P; Peponis, Vasileios G; Karagiannis, Dimitrios; Stratos, Aimilianos; Tsiotra, Vasileia A; Mitropoulos, Panagiotis G

    2014-01-01

    To report a case of spontaneous resolution of a long-standing serous macular detachment associated with an optic disc pit, leading to significant visual improvement. A 63-year-old female presented with a 6-month history of blurred vision and micropsia in her left eye. Her best-corrected visual acuity was 6/24 in the left eye, and fundoscopy revealed serous macular detachment associated with optic disc pit, which was confirmed by optical coherence tomography (OCT). The patient was offered vitrectomy as a treatment alternative, but she preferred to be reviewed conservatively. Three years after initial presentation, neither macular detachment nor subretinal fluid was evident in OCT, while the inner segment/outer segment (IS/OS) junction line was intact. Her visual acuity was improved from 6/24 to 6/12 in her left eye, remaining stable at the 6-month follow-up after resolution. We present a case of spontaneous resolution of a long-standing macular detachment associated with an optic disc pit with significant visual improvement, postulating that the integrity of the IS/OS junction line may be a prognostic factor for final visual acuity and suggesting OCT as an indicator of visual prognosis and the probable necessity of a surgical management.

  14. Spontaneous Resolution ofLong-Standing Macular Detachment due to Optic Disc Pit with Significant Visual Improvement

    Directory of Open Access Journals (Sweden)

    Efstratios A. Parikakis

    2014-03-01

    Full Text Available Purpose: To report a case of spontaneous resolution of a long-standing serous macular detachment associated with an optic disc pit, leading to significant visual improvement. Case Presentation: A 63-year-old female presented with a 6-month history of blurred vision and micropsia in her left eye. Her best-corrected visual acuity was 6/24 in the left eye, and fundoscopy revealed serous macular detachment associated with optic disc pit, which was confirmed by optical coherence tomography (OCT. The patient was offered vitrectomy as a treatment alternative, but she preferred to be reviewed conservatively. Three years after initial presentation, neither macular detachment nor subretinal fluid was evident in OCT, while the inner segment/outer segment (IS/OS junction line was intact. Her visual acuity was improved from 6/24 to 6/12 in her left eye, remaining stable at the 6-month follow-up after resolution. Conclusion: We present a case of spontaneous resolution of a long-standing macular detachment associated with an optic disc pit with significant visual improvement, postulating that the integrity of the IS/OS junction line may be a prognostic factor for final visual acuity and suggesting OCT as an indicator of visual prognosis and the probable necessity of a surgical management.

  15. 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.

  16. Can video games be used to predict or improve laparoscopic skills?

    Science.gov (United States)

    Rosenberg, Bradley H; Landsittel, Douglas; Averch, Timothy D

    2005-04-01

    Performance of laparoscopic surgery requires adequate hand-eye coordination. Video games are an effective way to judge one's hand-eye coordination, and practicing these games may improve one's skills. Our goal was to see if there is a correlation between skill in video games and skill in laparoscopy. Also, we hoped to demonstrate that practicing video games can improve one's laparoscopic skills. Eleven medical students (nine male, two female) volunteered to participate. On day 1, each student played three commercially available video games (Top Spin, XSN Sports; Project Gotham Racing 2, Bizarre Creations; and Amped 2, XSN Sports) for 30 minutes on an X-box (Microsoft, Seattle, WA) and was judged both objectively and subjectively. Next, the students performed four laparoscopic tasks (object transfer, tracing a figure-of-eight, suture placement, and knot-tying) in a swine model and were assessed for time to complete the task, number of errors committed, and hand-eye coordination. The students were then randomized to control (group A) or "training" (i.e., video game practicing; group B) arms. Two weeks later, all students repeated the laparoscopic skills laboratory and were reassessed. Spearman correlation coefficients demonstrated a significant relation between many of the parameters, particularly time to complete each task and hand-eye coordination at the different games. There was a weaker association between video game performance and both laparoscopic errors committed and hand-eye coordination. Group B subjects did not improve significantly over those in group A in any measure (P >0.05 for all). Video game aptitude appears to predict the level of laparoscopic skill in the novice surgeon. In this study, practicing video games did not improve one's laparoscopic skill significantly, but a larger study with more practice time could prove games to be helpful.

  17. 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.

  18. Improved predictions of nuclear reaction rates with the TALYS reaction code for astrophysical applications

    International Nuclear Information System (INIS)

    Goriely, S.; Hilaire, S.; Koning, A.J

    2008-01-01

    Context. Nuclear reaction rates of astrophysical applications are traditionally determined on the basis of Hauser-Feshbach reaction codes. These codes adopt a number of approximations that have never been tested, such as a simplified width fluctuation correction, the neglect of delayed or multiple-particle emission during the electromagnetic decay cascade, or the absence of the pre-equilibrium contribution at increasing incident energies. Aims. The reaction code TALYS has been recently updated to estimate the Maxwellian-averaged reaction rates that are of astrophysical relevance. These new developments enable the reaction rates to be calculated with increased accuracy and reliability and the approximations of previous codes to be investigated. Methods. The TALYS predictions for the thermonuclear rates of relevance to astrophysics are detailed and compared with those derived by widely-used codes for the same nuclear ingredients. Results. It is shown that TALYS predictions may differ significantly from those of previous codes, in particular for nuclei for which no or little nuclear data is available. The pre-equilibrium process is shown to influence the astrophysics rates of exotic neutron-rich nuclei significantly. For the first time, the Maxwellian- averaged (n, 2n) reaction rate is calculated for all nuclei and its competition with the radiative capture rate is discussed. Conclusions. The TALYS code provides a new tool to estimate all nuclear reaction rates of relevance to astrophysics with improved accuracy and reliability. (authors)

  19. Big Data, Predictive Analytics, and Quality Improvement in Kidney Transplantation: A Proof of Concept.

    Science.gov (United States)

    Srinivas, T R; Taber, D J; Su, Z; Zhang, J; Mour, G; Northrup, D; Tripathi, A; Marsden, J E; Moran, W P; Mauldin, P D

    2017-03-01

    We sought proof of concept of a Big Data Solution incorporating longitudinal structured and unstructured patient-level data from electronic health records (EHR) to predict graft loss (GL) and mortality. For a quality improvement initiative, GL and mortality prediction models were constructed using baseline and follow-up data (0-90 days posttransplant; structured and unstructured for 1-year models; data up to 1 year for 3-year models) on adult solitary kidney transplant recipients transplanted during 2007-2015 as follows: Model 1: United Network for Organ Sharing (UNOS) data; Model 2: UNOS & Transplant Database (Tx Database) data; Model 3: UNOS, Tx Database & EHR comorbidity data; and Model 4: UNOS, Tx Database, EHR data, Posttransplant trajectory data, and unstructured data. A 10% 3-year GL rate was observed among 891 patients (2007-2015). Layering of data sources improved model performance; Model 1: area under the curve (AUC), 0.66; (95% confidence interval [CI]: 0.60, 0.72); Model 2: AUC, 0.68; (95% CI: 0.61-0.74); Model 3: AUC, 0.72; (95% CI: 0.66-077); Model 4: AUC, 0.84, (95 % CI: 0.79-0.89). One-year GL (AUC, 0.87; Model 4) and 3-year mortality (AUC, 0.84; Model 4) models performed similarly. A Big Data approach significantly adds efficacy to GL and mortality prediction models and is EHR deployable to optimize outcomes. © 2016 The American Society of Transplantation and the American Society of Transplant Surgeons.

  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. Specific Components of Pediatricians' Medication-Related Care Predict Attention-Deficit/Hyperactivity Disorder Symptom Improvement.

    Science.gov (United States)

    Epstein, Jeffery N; Kelleher, Kelly J; Baum, Rebecca; Brinkman, William B; Peugh, James; Gardner, William; Lichtenstein, Phil; Langberg, Joshua M

    2017-06-01

    The development of attention-deficit/hyperactivity disorder (ADHD) care quality measurements is a prerequisite to improving the quality of community-based pediatric care of children with ADHD. Unfortunately, the evidence base for existing ADHD care quality metrics is poor. The objective of this study was to identify which components of ADHD care best predict patient outcomes. Parents of 372 medication-naïve children in grades 1 to 5 presenting to their community-based pediatrician (N = 195) for an ADHD-related concern and who were subsequently prescribed ADHD medication were identified. Parents completed the Vanderbilt ADHD Parent Rating Scale (VAPRS) at the time ADHD was raised as a concern and then approximately 12 months after starting ADHD medication. Each patient's chart was reviewed to measure 12 different components of ADHD care. Across all children, the mean decrease in VAPRS total symptom score during the first year of treatment was 11.6 (standard deviation 10.1). Of the 12 components of ADHD care, shorter times to first contact and more teacher ratings collected in the first year of treatment significantly predicted greater decreases in patient total symptom scores. Notably, it was timeliness of contacts, defined as office visits, phone calls, or email communication, that predicted more ADHD symptom decreases. Office visits alone, in terms of number or timeliness, did not predict patient outcomes. The magnitude of ADHD symptom decrease that can be achieved with the use of ADHD medications was associated with specific components of ADHD care. Future development and modifications of ADHD quality care metrics should include these ADHD care components. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  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. Mutations in gp41 are correlated with coreceptor tropism but do not improve prediction methods substantially.

    Science.gov (United States)

    Thielen, Alexander; Lengauer, Thomas; Swenson, Luke C; Dong, Winnie W Y; McGovern, Rachel A; Lewis, Marilyn; James, Ian; Heera, Jayvant; Valdez, Hernan; Harrigan, P Richard

    2011-01-01

    The main determinants of HIV-1 coreceptor usage are located in the V3-loop of gp120, although mutations in V2 and gp41 are also known. Incorporation of V2 is known to improve prediction algorithms; however, this has not been confirmed for gp41 mutations. Samples with V3 and gp41 genotypes and Trofile assay (Monogram Biosciences, South San Francisco, CA, USA) results were taken from the HOMER cohort (n=444) and from patients screened for the MOTIVATE studies (n=1,916; 859 with maraviroc outcome data). Correlations of mutations with tropism were assessed using Fisher's exact test and prediction models trained using support vector machines. Models were validated by cross-validation, by testing models from one dataset on the other, and by analysing virological outcome. Several mutations within gp41 were highly significant for CXCR4 usage; most strikingly an insertion occurring in 7.7% of HOMER-R5 and 46.3% of HOMER-X4 samples (MOTIVATE 5.7% and 25.2%, respectively). Models trained on gp41 sequence alone achieved relatively high areas under the receiver-operating characteristic curve (AUCs; HOMER 0.713 and MOTIVATE 0.736) that were almost as good as V3 models (0.773 and 0.884, respectively). However, combining the two regions improved predictions only marginally (0.813 and 0.902, respectively). Similar results were found when models were trained on HOMER and validated on MOTIVATE or vice versa. The difference in median log viral load decrease at week 24 between patients with R5 and X4 virus was 1.65 (HOMER 2.45 and MOTIVATE 0.79) for V3 models, 1.59 for gp41-models (2.42 and 0.83, respectively) and 1.58 for the combined predictor (2.44 and 0.86, respectively). Several mutations within gp41 showed strong correlation with tropism in two independent datasets. However, incorporating gp41 mutations into prediction models is not mandatory because they do not improve substantially on models trained on V3 sequences alone.

  5. Performance of the Sellick maneuver significantly improves when residents and trained nurses use a visually interactive guidance device in simulation

    International Nuclear Information System (INIS)

    Connor, Christopher W; Saffary, Roya; Feliz, Eddy

    2013-01-01

    We examined the proper performance of the Sellick maneuver, a maneuver used to reduce the risk of aspiration of stomach contents during induction of general anesthesia, using a novel device that measures and visualizes the force applied to the cricoid cartilage using thin-film force sensitive resistors in a form suitable for in vivo use. Performance was tested in three stages with twenty anaesthesiology residents and twenty trained operating room nurses. Firstly, subjects applied force to the cricoid cartilage as was customary to them. Secondly, subjects used the device to guide the application of that force. Thirdly, subjects were again asked to perform the manoeuvre without visual guidance. Each test lasted 1 min and the amount of force applied was measured throughout. Overall, the Sellick maneuver was often not applied properly, with large variance between individual subjects. Performance and inter-subject consistency improved to a very highly significant degree when subjects were able to use the device as a visual guide (p < 0.001). Subsequent significant improvements in performances during the last, unguided test demonstrated that the device initiated learning. (paper)

  6. Performance of the Sellick maneuver significantly improves when residents and trained nurses use a visually interactive guidance device in simulation

    Energy Technology Data Exchange (ETDEWEB)

    Connor, Christopher W; Saffary, Roya; Feliz, Eddy [Department of Anesthesiology Boston Medical Center, Boston, MA (United States)

    2013-12-15

    We examined the proper performance of the Sellick maneuver, a maneuver used to reduce the risk of aspiration of stomach contents during induction of general anesthesia, using a novel device that measures and visualizes the force applied to the cricoid cartilage using thin-film force sensitive resistors in a form suitable for in vivo use. Performance was tested in three stages with twenty anaesthesiology residents and twenty trained operating room nurses. Firstly, subjects applied force to the cricoid cartilage as was customary to them. Secondly, subjects used the device to guide the application of that force. Thirdly, subjects were again asked to perform the manoeuvre without visual guidance. Each test lasted 1 min and the amount of force applied was measured throughout. Overall, the Sellick maneuver was often not applied properly, with large variance between individual subjects. Performance and inter-subject consistency improved to a very highly significant degree when subjects were able to use the device as a visual guide (p < 0.001). Subsequent significant improvements in performances during the last, unguided test demonstrated that the device initiated learning. (paper)

  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 pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

    International Nuclear Information System (INIS)

    Manderla, M; Koutnik, J; Kiniger, K

    2014-01-01

    Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance

  9. Improved pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

    Science.gov (United States)

    Manderla, M.; Kiniger, K.; Koutnik, J.

    2014-03-01

    Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

  10. 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)

  11. A prediction score for significant coronary artery disease in Chinese patients ≥50 years old referred for rheumatic valvular heart disease surgery.

    Science.gov (United States)

    Xu, Zhenjun; Pan, Jun; Chen, Tao; Zhou, Qing; Wang, Qiang; Cao, Hailong; Fan, Fudong; Luo, Xuan; Ge, Min; Wang, Dongjin

    2018-04-01

    Our goal was to establish a prediction score and protocol for the preoperative prediction of significant coronary artery disease (CAD) in patients with rheumatic valvular heart disease. Using multivariate logistic regression analysis, we validated the model based on 490 patients without a history of myocardial infarction and who underwent preoperative screening coronary angiography. Significant CAD was defined as ≥50% narrowing of the diameter of the lumen of the left main coronary artery or ≥70% narrowing of the diameter of the lumen of the left anterior descending coronary artery, left circumflex artery or right coronary artery. Significant CAD was present in 9.8% of patients. Age, smoking, diabetes mellitus, diastolic blood pressure, low-density lipoprotein cholesterol and ischaemia evident on an electrocardiogram were independently associated with significant CAD and were entered into the multivariate model. According to the logistic regression predictive risk score, preoperative coronary angiography is recommended in (i) postmenopausal women between 50 and 59 years of age with ≥9.1% logistic regression predictive risk score; (ii) postmenopausal women who are ≥60 years old with a logistic regression predictive risk score ≥6.6% and (iii) men ≥50 years old whose logistic regression predictive risk score was ≥2.8%. Based on this predictive model, 246 (50.2%) preoperative coronary angiograms could be safely avoided. The negative predictive value of the model was 98.8% (246 of 249). This model was accurate for the preoperative prediction of significant CAD in patients with rheumatic valvular heart disease. This model must be validated in larger cohorts and various populations.

  12. 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.

  13. Pulmonary edema predictive scoring index (PEPSI), a new index to predict risk of reperfusion pulmonary edema and improvement of hemodynamics in percutaneous transluminal pulmonary angioplasty.

    Science.gov (United States)

    Inami, Takumi; Kataoka, Masaharu; Shimura, Nobuhiko; Ishiguro, Haruhisa; Yanagisawa, Ryoji; Taguchi, Hiroki; Fukuda, Keiichi; Yoshino, Hideaki; Satoh, Toru

    2013-07-01

    This study sought to identify useful predictors for hemodynamic improvement and risk of reperfusion pulmonary edema (RPE), a major complication of this procedure. Percutaneous transluminal pulmonary angioplasty (PTPA) has been reported to be effective for the treatment of chronic thromboembolic pulmonary hypertension (CTEPH). PTPA has not been widespread because RPE has not been well predicted. We included 140 consecutive procedures in 54 patients with CTEPH. The flow appearance of the target vessels was graded into 4 groups (Pulmonary Flow Grade), and we proposed PEPSI (Pulmonary Edema Predictive Scoring Index) = (sum total change of Pulmonary Flow Grade scores) × (baseline pulmonary vascular resistance). Correlations between occurrence of RPE and 11 variables, including hemodynamic parameters, number of target vessels, and PEPSI, were analyzed. Hemodynamic parameters significantly improved after median observation period of 6.4 months, and the sum total changes in Pulmonary Flow Grade scores were significantly correlated with the improvement in hemodynamics. Multivariate analysis revealed that PEPSI was the strongest factor correlated with the occurrence of RPE (p PEPSI to be a useful marker of the risk of RPE (cutoff value 35.4, negative predictive value 92.3%). Pulmonary Flow Grade score is useful in determining therapeutic efficacy, and PEPSI is highly supportive to reduce the risk of RPE after PTPA. Using these 2 indexes, PTPA could become a safe and common therapeutic strategy for CTEPH. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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

    DEFF Research Database (Denmark)

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

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

  15. Induction Based Training leads to Highly Significant Improvements of Objective and Subjective Suturing Ability in Junior Doctors

    Directory of Open Access Journals (Sweden)

    Kevin Garry

    2018-03-01

    Full Text Available Background: Simulation based training has shown to be of benefit in the education of medical students. However, the impact of induction based clinical simulation on surgical ability of qualified doctors remains unclear.The aim of this study was to establish if a 60 minute teaching session integrated into an Emergency Medicine speciality induction program produces statistically significant improvements in objective and subjective suturing abilities of junior doctors commencing an Emergency Medicine rotation.Methods: The objective suturing abilities of 16 Foundation Year Two doctors were analysed using a validated OSATs scale prior to a novel teaching intervention. The doctors then undertook an intensive hour long workshop receiving one to one feedback before undergoing repeat OSATs assessment.Subjective ability was measured using a 5 point likert scale and self-assessed competency reporting interrupted suturing before and after the intervention. Photographs of wound closure before and after the intervention were recorded for further blinded assessment of impact of intervention. A survey regarding continued ability was repeated at four months following the intervention. The study took place on 7/12/16 during the Belfast Health and Social Care Trust Emergency Medicine induction in the Royal Victoria Hospital Belfast. The hospital is a regional level 1 trauma centre that has annual departmental attendances in excess of 200,000.All new junior doctors commencing the Emergency Medicine rotation were invited to partake in the study. All 16 agreed. The group consisted of a mixture of undergraduate and postgraduate medicaldoctors who all had 16 months experience working in a variety of medical or surgical jobs previously.Results: Following the teaching intervention objective and subjective abilities in interrupted suturing showed statistically significant improvement (P>0.005. Self-reporting of competency of independently suturingwounds improved from 50

  16. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

    2016-07-30

    Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron

  17. 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)

  18. 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.

  19. 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.

  20. P-wave characteristics on routine preoperative electrocardiogram improve prediction of new-onset postoperative atrial fibrillation in cardiac surgery.

    Science.gov (United States)

    Wong, Jim K; Lobato, Robert L; Pinesett, Andre; Maxwell, Bryan G; Mora-Mangano, Christina T; Perez, Marco V

    2014-12-01

    To test the hypothesis that including preoperative electrocardiogram (ECG) characteristics with clinical variables significantly improves the new-onset postoperative atrial fibrillation prediction model. Retrospective analysis. Single-center university hospital. Five hundred twenty-six patients, ≥ 18 years of age, who underwent coronary artery bypass grafting, aortic valve replacement, mitral valve replacement/repair, or a combination of valve surgery and coronary artery bypass grafting requiring cardiopulmonary bypass. Retrospective review of medical records. Baseline characteristics and cardiopulmonary bypass times were collected. Digitally-measured timing and voltages from preoperative electrocardiograms were extracted. Postoperative atrial fibrillation was defined as atrial fibrillation requiring therapeutic intervention. Two hundred eight (39.5%) patients developed postoperative atrial fibrillation. Clinical predictors were age, ejection fractionelectrocardiogram variables to the prediction model with only clinical predictors significantly improved the area under the receiver operating characteristic curve, from 0.71 to 0.78 (p<0.01). Overall net reclassification improvement was 0.059 (p = 0.09). Among those who developed postoperative atrial fibrillation, the net reclassification improvement was 0.063 (p = 0.03). Several p-wave characteristics are independently associated with postoperative atrial fibrillation. Addition of these parameters improves the postoperative atrial fibrillation prediction model. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  1. The European Academy laparoscopic “Suturing Training and Testing’’ (SUTT) significantly improves surgeons’ performance

    Science.gov (United States)

    Sleiman, Z.; Tanos, V.; Van Belle, Y.; Carvalho, J.L.; Campo, R.

    2015-01-01

    The efficiency of suturing training and testing (SUTT) model by laparoscopy was evaluated, measuring the suturingskill acquisition of trainee gynecologists at the beginning and at the end of a teaching course. During a workshop organized by the European Academy of Gynecological Surgery (EAGS), 25 participants with three different experience levels in laparoscopy (minor, intermediate and major) performed the 4 exercises of the SUTT model (Ex 1: both hands stitching and continuous suturing, Ex 2: right hand stitching and intracorporeal knotting, Ex 3: left hand stitching and intracorporeal knotting, Ex 4: dominant hand stitching, tissue approximation and intracorporeal knotting). The time needed to perform the exercises is recorded for each trainee and group and statistical analysis used to note the differences. Overall, all trainees achieved significant improvement in suturing time (p psychomotor skills, surgery, teaching, training suturing model. PMID:26977264

  2. High-intensity interval training (swimming) significantly improves the adverse metabolism and comorbidities in diet-induced obese mice.

    Science.gov (United States)

    Motta, Victor F; Aguila, Marcia B; Mandarim-DE-Lacerda, Carlos A

    2016-05-01

    Controlling obesity and other comorbidities in the population is a challenge in modern society. High-intensity interval training (HIIT) combines short periods of high-intensity exercise with long recovery periods or a low-intensity exercise. The aim was to assess the impact of HIIT in the context of diet-induced obesity in the animal model. C57BL/6 mice were fed one of the two diets: standard chow (lean group [LE]) or a high-fat diet (obese group [OB]). After twelve weeks, the animals were divided into non-trained groups (LE-NT and OB-NT) and trained groups (LE-T and OB-T), and began an exercise protocol. For biochemical analysis of inflammatory and lipid profile, we used a colorimetric enzymatic method and an automatic spectrophotometer. One-way ANOVA was used for statistical analysis of the experimental groups with Holm-Sidak post-hoc Test. Two-way ANOVA analyzed the interactions between diet and HIIT protocol. HIIT leads to significant reductions in body mass, blood glucose, glucose tolerance and hepatic lipid profile in T-groups compared to NT-groups. HIIT was able to reduce plasma levels of inflammatory cytokines. Additionally, HIIT improves the insulin immunodensity in the islets, reduces the adiposity and the hepatic steatosis in the T-groups. HIIT improves beta-oxidation and peroxisome proliferator-activated receptor (PPAR)-alpha and reduces lipogenesis and PPAR-gamma levels in the liver. In skeletal muscle, HIIT improves PPAR-alpha and glucose transporter-4 and reduces PPAR-gamma levels. HIIT leads to attenuate the adverse effects caused by a chronic ingestion of a high-fat diet.

  3. Codon Optimization Significantly Improves the Expression Level of α-Amylase Gene from Bacillus licheniformis in Pichia pastoris

    Directory of Open Access Journals (Sweden)

    Jian-Rong Wang

    2015-01-01

    Full Text Available α-Amylase as an important industrial enzyme has been widely used in starch processing, detergent, and paper industries. To improve expression efficiency of recombinant α-amylase from Bacillus licheniformis (B. licheniformis, the α-amylase gene from B. licheniformis was optimized according to the codon usage of Pichia pastoris (P. pastoris and expressed in P. pastoris. Totally, the codons encoding 305 amino acids were optimized in which a total of 328 nucleotides were changed and the G+C content was increased from 47.6 to 49.2%. The recombinants were cultured in 96-deep-well microplates and screened by a new plate assay method. Compared with the wild-type gene, the optimized gene is expressed at a significantly higher level in P. pastoris after methanol induction for 168 h in 5- and 50-L bioreactor with the maximum activity of 8100 and 11000 U/mL, which was 2.31- and 2.62-fold higher than that by wild-type gene. The improved expression level makes the enzyme a good candidate for α-amylase production in industrial use.

  4. On the importance of paleoclimate modelling for improving predictions of future climate change

    Directory of Open Access Journals (Sweden)

    J. C. Hargreaves

    2009-12-01

    Full Text Available We use an ensemble of runs from the MIROC3.2 AGCM with slab-ocean to explore the extent to which mid-Holocene simulations are relevant to predictions of future climate change. The results are compared with similar analyses for the Last Glacial Maximum (LGM and pre-industrial control climate. We suggest that the paleoclimate epochs can provide some independent validation of the models that is also relevant for future predictions. Considering the paleoclimate epochs, we find that the stronger global forcing and hence larger climate change at the LGM makes this likely to be the more powerful one for estimating the large-scale changes that are anticipated due to anthropogenic forcing. The phenomena in the mid-Holocene simulations which are most strongly correlated with future changes (i.e., the mid to high northern latitude land temperature and monsoon precipitation do, however, coincide with areas where the LGM results are not correlated with future changes, and these are also areas where the paleodata indicate significant climate changes have occurred. Thus, these regions and phenomena for the mid-Holocene may be useful for model improvement and validation.

  5. Significant correlation between spleen volume and thrombocytopenia in liver transplant patients: a concept for predicting persistent thrombocytopenia.

    Science.gov (United States)

    Ohira, Masahiro; Ishifuro, Minoru; Ide, Kentaro; Irei, Toshimitsu; Tashiro, Hirotaka; Itamoto, Toshiyuki; Ito, Katsuhide; Chayama, Kazuaki; Asahara, Toshimasa; Ohdan, Hideki

    2009-02-01

    Interferon (IFN) therapy with or without ribavirin treatment is well established as a standard antiviral treatment for hepatitis C virus (HCV)-infected patients. However, susceptibility to thrombocytopenia is a major obstacle for initiating or continuing this therapy, particularly in liver transplant (LTx) recipients with HCV. Studies have reported that splenectomy performed concurrently with LTx is a feasible strategy for conditioning patients for anti-HCV IFN therapy. However, the relationship between the severity of splenomegaly and alterations in the blood cytopenia in LTx recipients remains to be clarified. Here, we analyzed the relationship between spleen volume (SV) and thrombocytopenia in 45 patients who underwent LTx at Hiroshima University Hospital. The extent of pre-LTx splenomegaly [the SV to body surface area (BSA) ratio in an individual] was inversely correlated with both the post-LTx white blood cell count and platelet (PLT) count (P or= 400), persistent thrombocytopenia is predictable after LTx. (c) 2009 AASLD.

  6. Changes in the Oswestry Disability Index that predict improvement after lumbar fusion.

    Science.gov (United States)

    Djurasovic, Mladen; Glassman, Steven D; Dimar, John R; Crawford, Charles H; Bratcher, Kelly R; Carreon, Leah Y

    2012-11-01

    Clinical studies use both disease-specific and generic health outcomes measures. Disease-specific measures focus on health domains most relevant to the clinical population, while generic measures assess overall health-related quality of life. There is little information about which domains of the Oswestry Disability Index (ODI) are most important in determining improvement in overall health-related quality of life, as measured by the 36-Item Short Form Health Survey (SF-36), after lumbar spinal fusion. The objective of the study is to determine which clinical elements assessed by the ODI most influence improvement of overall health-related quality of life. A single tertiary spine center database was used to identify patients undergoing lumbar fusion for standard degenerative indications. Patients with complete preoperative and 2-year outcomes measures were included. Pearson correlation was used to assess the relationship between improvement in each item of the ODI with improvement in the SF-36 physical component summary (PCS) score, as well as achievement of the SF-36 PCS minimum clinically important difference (MCID). Multivariate regression modeling was used to examine which items of the ODI best predicted achievement for the SF-36 PCS MCID. The effect size and standardized response mean were calculated for each of the items of the ODI. A total of 1104 patients met inclusion criteria (674 female and 430 male patients). The mean age at surgery was 57 years. All items of the ODI showed significant correlations with the change in SF-36 PCS score and achievement of MCID for the SF-36 PCS, but only pain intensity, walking, and social life had r values > 0.4 reflecting moderate correlation. These 3 variables were also the dimensions that were independent predictors of the SF-36 PCS, and they were the only dimensions that had effect sizes and standardized response means that were moderate to large. Of the health dimensions measured by the ODI, pain intensity, walking

  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. Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

    Directory of Open Access Journals (Sweden)

    Lees Jonathan G

    2008-01-01

    Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

  9. Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

    Science.gov (United States)

    Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

    2017-12-01

    Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.

  10. 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

  11. Linking precipitation, evapotranspiration and soil moisture content for the improvement of predictability over land

    Science.gov (United States)

    Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

    2013-04-01

    Climate change scenarios are expected to show an intensification of the hydrological cycle together with modifications of evapotranspiration and soil moisture content. Evapotranspiration changes have been already evidenced for the end of the 20th century. The variance of evapotranspiration has been shown to be strongly related to the variance of precipitation over land. Nevertheless, the feedbacks between evapotranspiration, soil moisture and precipitation have not yet been completely understood at present-day. Furthermore, soil moisture reservoirs are associated to a memory and thus their proper initialization may have a strong influence on predictability. In particular, the linkage between precipitation and soil moisture is modulated by the effects on evapotranspiration. Therefore, the investigation of the coupling between these variables appear to be of primary importance for the improvement of predictability over the continents. The coupled manifold (CM) technique (Navarra and Tribbia 2005) is a method designed to separate the effects of the variability of two variables which are connected. This method has proved to be successful for the analysis of different climate fields, like precipitation, vegetation and sea surface temperature. In particular, the coupled variables reveal patterns that may be connected with specific phenomena, thus providing hints regarding potential predictability. In this study we applied the CM to recent observational datasets of precipitation (from CRU), evapotranspiration (from GIMMS and MODIS satellite-based estimates) and soil moisture content (from ESA) spanning a time period of 23 years (1984-2006) with a monthly frequency. Different data stratification (monthly, seasonal, summer JJA) have been employed to analyze the persistence of the patterns and their characteristical time scales and seasonality. The three variables considered show a significant coupling among each other. Interestingly, most of the signal of the

  12. Complete Au@ZnO core-shell nanoparticles with enhanced plasmonic absorption enabling significantly improved photocatalysis

    Science.gov (United States)

    Sun, Yiqiang; Sun, Yugang; Zhang, Tao; Chen, Guozhu; Zhang, Fengshou; Liu, Dilong; Cai, Weiping; Li, Yue; Yang, Xianfeng; Li, Cuncheng

    2016-05-01

    Nanostructured ZnO exhibits high chemical stability and unique optical properties, representing a promising candidate among photocatalysts in the field of environmental remediation and solar energy conversion. However, ZnO only absorbs the UV light, which accounts for less than 5% of total solar irradiation, significantly limiting its applications. In this article, we report a facile and efficient approach to overcome the poor wettability between ZnO and Au by carefully modulating the surface charge density on Au nanoparticles (NPs), enabling rapid synthesis of Au@ZnO core-shell NPs at room temperature. The resulting Au@ZnO core-shell NPs exhibit a significantly enhanced plasmonic absorption in the visible range due to the Au NP cores. They also show a significantly improved photocatalytic performance in comparison with their single-component counterparts, i.e., the Au NPs and ZnO NPs. Moreover, the high catalytic activity of the as-synthesized Au@ZnO core-shell NPs can be maintained even after many cycles of photocatalytic reaction. Our results shed light on the fact that the Au@ZnO core-shell NPs represent a promising class of candidates for applications in plasmonics, surface-enhanced spectroscopy, light harvest devices, solar energy conversion, and degradation of organic pollutants.Nanostructured ZnO exhibits high chemical stability and unique optical properties, representing a promising candidate among photocatalysts in the field of environmental remediation and solar energy conversion. However, ZnO only absorbs the UV light, which accounts for less than 5% of total solar irradiation, significantly limiting its applications. In this article, we report a facile and efficient approach to overcome the poor wettability between ZnO and Au by carefully modulating the surface charge density on Au nanoparticles (NPs), enabling rapid synthesis of Au@ZnO core-shell NPs at room temperature. The resulting Au@ZnO core-shell NPs exhibit a significantly enhanced plasmonic

  13. Improved predictions of nuclear reaction rates for astrophysics applications with the TALYS reaction code

    International Nuclear Information System (INIS)

    Goriely, S.; Hilaire, S.; Koning, A.J.

    2008-01-01

    Nuclear reaction rates for astrophysics applications are traditionally determined on the basis of Hauser-Feshbach reaction codes, like MOST. These codes use simplified schemes to calculate the capture reaction cross section on a given target nucleus, not only in its ground state but also on the different thermally populated states of the stellar plasma at a given temperature. Such schemes include a number of approximations that have never been tested, such as an approximate width fluctuation correction, the neglect of delayed particle emission during the electromagnetic decay cascade or the absence of the pre-equilibrium contribution at increasing incident energies. New developments have been brought to the reaction code TALYS to estimate the Maxwellian-averaged reaction rates of astrophysics relevance. These new developments give us the possibility to calculate with an improved accuracy the reaction cross sections and the corresponding astrophysics rates. The TALYS predictions for the thermonuclear rates of astrophysics relevance are presented and compared with those obtained with the MOST code on the basis of the same nuclear ingredients for nuclear structure properties, optical model potential, nuclear level densities and γ-ray strength. It is shown that, in particular, the pre-equilibrium process significantly influences the astrophysics rates of exotic neutron-rich nuclei. The reciprocity theorem traditionally used in astrophysics to determine photo-rates is also shown no to be valid for exotic nuclei. The predictions obtained with different nuclear inputs are also analyzed to provide an estimate of the theoretical uncertainties still affecting the reaction rate prediction far away from the experimentally known regions. (authors)

  14. Combat-related intradural gunshot wound to the thoracic spine: significant improvement and neurologic recovery following bullet removal.

    Science.gov (United States)

    Louwes, Thijs M; Ward, William H; Lee, Kendall H; Freedman, Brett A

    2015-02-01

    The vast majority of combat-related penetrating spinal injuries from gunshot wounds result in severe or complete neurological deficit. Treatment is based on neurological status, the presence of cerebrospinal fluid (CSF) fistulas, and local effects of any retained fragment(s). We present a case of a 46-year-old male who sustained a spinal gunshot injury from a 7.62-mm AK-47 round that became lodged within the subarachnoid space at T9-T10. He immediately suffered complete motor and sensory loss. By 24-48 hours post-injury, he had recovered lower extremity motor function fully but continued to have severe sensory loss (posterior cord syndrome). On post-injury day 2, he was evacuated from the combat theater and underwent a T9 laminectomy, extraction of the bullet, and dural laceration repair. At surgery, the traumatic durotomy was widened and the bullet, which was laying on the dorsal surface of the spinal cord, was removed. The dura was closed in a water-tight fashion and fibrin glue was applied. Postoperatively, the patient made a significant but incomplete neurological recovery. His stocking-pattern numbness and sub-umbilical searing dysthesia improved. The spinal canal was clear of the foreign body and he had no persistent CSF leak. Postoperative magnetic resonance imaging of the spine revealed contusion of the spinal cord at the T9 level. Early removal of an intra-canicular bullet in the setting of an incomplete spinal cord injury can lead to significant neurological recovery following even high-velocity and/or high-caliber gunshot wounds. However, this case does not speak to, and prior experience does not demonstrate, significant neurological benefit in the setting of a complete injury.

  15. 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.

  16. Improve accuracy and sensibility in glycan structure prediction by matching glycan isotope abundance

    International Nuclear Information System (INIS)

    Xu Guang; Liu Xin; Liu Qingyan; Zhou Yanhong; Li Jianjun

    2012-01-01

    Highlights: ► A glycan isotope pattern recognition strategy for glycomics. ► A new data preprocessing procedure to detect ion peaks in a giving MS spectrum. ► A linear soft margin SVM classification for isotope pattern recognition. - Abstract: Mass Spectrometry (MS) is a powerful technique for the determination of glycan structures and is capable of providing qualitative and quantitative information. Recent development in computational method offers an opportunity to use glycan structure databases and de novo algorithms for extracting valuable information from MS or MS/MS data. However, detecting low-intensity peaks that are buried in noisy data sets is still a challenge and an algorithm for accurate prediction and annotation of glycan structures from MS data is highly desirable. The present study describes a novel algorithm for glycan structure prediction by matching glycan isotope abundance (mGIA), which takes isotope masses, abundances, and spacing into account. We constructed a comprehensive database containing 808 glycan compositions and their corresponding isotope abundance. Unlike most previously reported methods, not only did we take into count the m/z values of the peaks but also their corresponding logarithmic Euclidean distance of the calculated and detected isotope vectors. Evaluation against a linear classifier, obtained by training mGIA algorithm with datasets of three different human tissue samples from Consortium for Functional Glycomics (CFG) in association with Support Vector Machine (SVM), was proposed to improve the accuracy of automatic glycan structure annotation. In addition, an effective data preprocessing procedure, including baseline subtraction, smoothing, peak centroiding and composition matching for extracting correct isotope profiles from MS data was incorporated. The algorithm was validated by analyzing the mouse kidney MS data from CFG, resulting in the identification of 6 more glycan compositions than the previous annotation

  17. The significance and predictive value of free light chains in the urine of patients with chronic inflammatory rheumatic disease.

    Science.gov (United States)

    Bramlage, Carsten Paul; Froelich, Britta; Wallbach, Manuel; Minguet, Joan; Grupp, Clemens; Deutsch, Cornelia; Bramlage, Peter; Koziolek, Michael; Müller, Gerhard Anton

    2016-12-01

    In patients with rheumatic diseases, reliable markers for determining disease activity are scarce. One potential parameter is the level of immunoglobulin free light chains (FLCs), which is known to be elevated in the blood of patients with certain rheumatic diseases. Few studies have quantified FLCs in urine, a convenient source of test sample, in patients with different rheumatic diseases. We carried out a retrospective analysis of patients with rheumatic disease attending the University hospital of Goettingen, Germany. Subjects were included if they had urine levels of both κ and λ FLCs available and did not have myeloma. Data regarding systemic inflammation and kidney function were recorded, and FLC levels were correlated with inflammatory markers. Of the 382 patients with rheumatic disease, 40.1 % had chronic polyarthritis, 21.2 % connective tissue disease, 18.6 % spondyloarthritis and 15.7 % vasculitis. Elevated levels of κ FLCs were found for 84 % of patients and elevated λ for 52.7 %. For the patients with rheumatoid arthritis, FLCs correlated with C-reactive protein (κ, r = 0.368, p rheumatic disease, but not in κ/λ ratio. The correlation between FLCs and inflammatory markers in patients with rheumatoid arthritis demonstrates their potential for predicting disease activity.

  18. Lipid Replacement Therapy Drink Containing a Glycophospholipid Formulation Rapidly and Significantly Reduces Fatigue While Improving Energy and Mental Clarity

    Directory of Open Access Journals (Sweden)

    Robert Settineri

    2011-08-01

    Full Text Available Background: Fatigue is the most common complaint of patients seeking general medical care and is often treated with stimulants. It is also important in various physical activities of relatively healthy men and women, such as sports performance. Recent clinical trials using patients with chronic fatigue have shown the benefit of Lipid Replacement Therapy in restoring mitochondrial electron transport function and reducing moderate to severe chronic fatigue. Methods: Lipid Replacement Therapy was administered for the first time as an all-natural functional food drink (60 ml containing polyunsaturated glycophospholipids but devoid of stimulants or herbs to reduce fatigue. This preliminary study used the Piper Fatigue Survey instrument as well as a supplemental questionnaire to assess the effects of the glycophospholipid drink on fatigue and the acceptability of the test drink in adult men and women. A volunteer group of 29 subjects of mean age 56.2±4.5 years with various fatigue levels were randomly recruited in a clinical health fair setting to participate in an afternoon open label trial on the effects of the test drink. Results: Using the Piper Fatigue instrument overall fatigue among participants was reduced within the 3-hour seminar by a mean of 39.6% (p<0.0001. All of the subcategories of fatigue showed significant reductions. Some subjects responded within 15 minutes, and the majority responded within one hour with increased energy and activity and perceived improvements in cognitive function, mental clarity and focus. The test drink was determined to be quite acceptable in terms of taste and appearance. There were no adverse events from the energy drink during the study.Functional Foods in Health and Disease 2011; 8:245-254Conclusions: The Lipid Replacement Therapy functional food drink appeared to be a safe, acceptable and potentially useful new method to reduce fatigue, sustain energy and improve perceptions of mental function.

  19. A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

    Directory of Open Access Journals (Sweden)

    Simon D Angus

    -effecitive means of significantly improving clinical efficacy.

  20. A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

    Science.gov (United States)

    Angus, Simon D; Piotrowska, Monika Joanna

    2014-01-01

    of significantly improving clinical efficacy.

  1. Concurrent Modeling of Hydrodynamics and Interaction Forces Improves Particle Deposition Predictions.

    Science.gov (United States)

    Jin, Chao; Ren, Carolyn L; Emelko, Monica B

    2016-04-19

    It is widely believed that media surface roughness enhances particle deposition-numerous, but inconsistent, examples of this effect have been reported. Here, a new mathematical framework describing the effects of hydrodynamics and interaction forces on particle deposition on rough spherical collectors in absence of an energy barrier was developed and validated. In addition to quantifying DLVO force, the model includes improved descriptions of flow field profiles and hydrodynamic retardation functions. This work demonstrates that hydrodynamic effects can significantly alter particle deposition relative to expectations when only the DLVO force is considered. Moreover, the combined effects of hydrodynamics and interaction forces on particle deposition on rough, spherical media are not additive, but synergistic. Notably, the developed model's particle deposition predictions are in closer agreement with experimental observations than those from current models, demonstrating the importance of inclusion of roughness impacts in particle deposition description/simulation. Consideration of hydrodynamic contributions to particle deposition may help to explain discrepancies between model-based expectations and experimental outcomes and improve descriptions of particle deposition during physicochemical filtration in systems with nonsmooth collector surfaces.

  2. The Relationship between Obsessive Compulsive Personality and Obsessive Compulsive Disorder Treatment Outcomes: Predictive Utility and Clinically Significant Change.

    Science.gov (United States)

    Sadri, Shalane K; McEvoy, Peter M; Egan, Sarah J; Kane, Robert T; Rees, Clare S; Anderson, Rebecca A

    2017-09-01

    The evidence regarding whether co-morbid obsessive compulsive personality disorder (OCPD) is associated with treatment outcomes in obsessive compulsive disorder (OCD) is mixed, with some research indicating that OCPD is associated with poorer response, and some showing that it is associated with improved response. We sought to explore the role of OCPD diagnosis and the personality domain of conscientiousness on treatment outcomes for exposure and response prevention for OCD. The impact of co-morbid OCPD and conscientiousness on treatment outcomes was examined in a clinical sample of 46 participants with OCD. OCPD diagnosis and scores on conscientiousness were not associated with poorer post-treatment OCD severity, as indexed by Yale-Brown Obsessive Compulsive Scale (YBOCS) scores, although the relative sample size of OCPD was small and thus generalizability is limited. This study found no evidence that OCPD or conscientiousness were associated with treatment outcomes for OCD. Further research with larger clinical samples is required.

  3. Significance of cardiac sympathetic nervous system abnormality for predicting vascular events in patients with idiopathic paroxysmal atrial fibrillation

    International Nuclear Information System (INIS)

    Akutsu, Yasushi; Kaneko, Kyouichi; Kodama, Yusuke; Li, Hui-Ling; Kawamura, Mitsuharu; Asano, Taku; Hamazaki, Yuji; Tanno, Kaoru; Kobayashi, Youichi; Suyama, Jumpei; Shinozuka, Akira; Gokan, Takehiko

    2010-01-01

    Neuronal system activity plays an important role for the prognosis of patients with atrial fibrillation (AF). Using 123 I metaiodobenzylguanidine ( 123 I-MIBG) scintigraphy, we investigated whether a cardiac sympathetic nervous system (SNS) abnormality would be associated with an increased risk of vascular events in patients with paroxysmal AF. 123 I-MIBG scintigraphy was performed in 69 consecutive patients (67 ± 13 years, 62% men) with paroxysmal AF who did not have structural heart disease. SNS integrity was assessed from the heart to mediastinum (H/M) ratio on delayed imaging. Serum concentration of C-reactive protein (CRP) was measured before 123 I-MIBG study. During a mean of 4.5 ± 3.6 years follow-up, 19 patients had myocardial infarction, stroke or heart failure (range: 0.2-11.5 years). SNS abnormality (H/M ratio <2.7) and high CRP (≥0.3 mg/dl) were associated with the vascular events (58.3% in 14 of 24 patients with SNS abnormality vs 11.1% in 5 of 45 patients without SNS abnormality, p < 0.0001, 52.4% in 11 of 21 patients with high CRP vs 16.7% in 8 of 48 patients without high CRP, p < 0.0001). After adjustment for potential confounding variables such as age, left atrial dimension and left ventricular function, SNS abnormality was an independent predictor of vascular events with a hazard ratio of 4.1 [95% confidence interval (CI): 1.3-12.6, p = 0.014]. Further, SNS abnormality had an incremental and additive prognostic power in combination with high CRP with an adjusted hazard ratio of 4.1 (95% CI: 1.5-10.9, p = 0.006). SNS abnormality is predictive of vascular events in patients with idiopathic paroxysmal AF. (orig.)

  4. Significance of cardiac sympathetic nervous system abnormality for predicting vascular events in patients with idiopathic paroxysmal atrial fibrillation

    Energy Technology Data Exchange (ETDEWEB)

    Akutsu, Yasushi; Kaneko, Kyouichi; Kodama, Yusuke; Li, Hui-Ling; Kawamura, Mitsuharu; Asano, Taku; Hamazaki, Yuji; Tanno, Kaoru; Kobayashi, Youichi [Showa University School of Medicine, Division of Cardiology, Department of Medicine, Tokyo (Japan); Suyama, Jumpei; Shinozuka, Akira; Gokan, Takehiko [Showa University School of Medicine, Department of Radiology, Tokyo (Japan)

    2010-04-15

    Neuronal system activity plays an important role for the prognosis of patients with atrial fibrillation (AF). Using {sup 123}I metaiodobenzylguanidine ({sup 123}I-MIBG) scintigraphy, we investigated whether a cardiac sympathetic nervous system (SNS) abnormality would be associated with an increased risk of vascular events in patients with paroxysmal AF. {sup 123}I-MIBG scintigraphy was performed in 69 consecutive patients (67 {+-} 13 years, 62% men) with paroxysmal AF who did not have structural heart disease. SNS integrity was assessed from the heart to mediastinum (H/M) ratio on delayed imaging. Serum concentration of C-reactive protein (CRP) was measured before {sup 123}I-MIBG study. During a mean of 4.5 {+-} 3.6 years follow-up, 19 patients had myocardial infarction, stroke or heart failure (range: 0.2-11.5 years). SNS abnormality (H/M ratio <2.7) and high CRP ({>=}0.3 mg/dl) were associated with the vascular events (58.3% in 14 of 24 patients with SNS abnormality vs 11.1% in 5 of 45 patients without SNS abnormality, p < 0.0001, 52.4% in 11 of 21 patients with high CRP vs 16.7% in 8 of 48 patients without high CRP, p < 0.0001). After adjustment for potential confounding variables such as age, left atrial dimension and left ventricular function, SNS abnormality was an independent predictor of vascular events with a hazard ratio of 4.1 [95% confidence interval (CI): 1.3-12.6, p = 0.014]. Further, SNS abnormality had an incremental and additive prognostic power in combination with high CRP with an adjusted hazard ratio of 4.1 (95% CI: 1.5-10.9, p = 0.006). SNS abnormality is predictive of vascular events in patients with idiopathic paroxysmal AF. (orig.)

  5. Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

    Science.gov (United States)

    Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

    2018-03-01

    Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

  6. Flavonol-rich dark cocoa significantly decreases plasma endothelin-1 and improves cognitive responses in urban children.

    Directory of Open Access Journals (Sweden)

    Lilian eCalderon-Garciduenas

    2013-08-01

    Full Text Available Air pollution exposures are linked to systemic inflammation, cardiovascular and respiratory morbidity and mortality, neuroinflammation and neuropathology in young urbanites. In particular, most Mexico City Metropolitan Area (MCMA children exhibit subtle cognitive deficits, and neuropathology studies show 40% of them exhibiting frontal tau hyperphosphorylation and 51% amyloid-β diffuse plaques (compared to 0% in low pollution control children. We assessed whether a short cocoa intervention can be effective in decreasing plasma endothelin 1 (ET-1 and/or inflammatory mediators in MCMA children. Thirty g of dark cocoa with 680 mg of total flavonols were given daily for 10.11± 3.4 days (range 9 to 24 days to 18 children (10.55yrs, SD =1.45; 11F/7M. Key metabolite ratios in frontal white matter and in hippocampus pre and during cocoa intervention were quantified by magnetic resonance spectroscopy. ET-1 significantly decreased after cocoa treatment (p=0.0002. Fifteen children (83% showed a marginally significant individual improvement in one or both of the applied simple short memory tasks. Endothelial dysfunction is a key feature of exposure to particulate matter and decreased endothelin-1 bioavailability is likely useful for brain function in the context of air pollution. Our findings suggest that cocoa interventions may be critical for early implementation of neuroprotection of highly exposed urban children. Multi-domain nutraceutical interventions could limit the risk for endothelial dysfunction, cerebral hypoperfusion, neuroinflammation, cognitive deficits, structural volumetric detrimental brain effects, and the early development of the neuropathological hallmarks of Alzheimer’s and Parkinson’s diseases.

  7. Evaluation of ischemic corticospinal tract damage by diffusion tensor MRI. Its significance to predict functional outcome of corona radiata infarct

    International Nuclear Information System (INIS)

    Tanaka, Hideki

    2010-01-01

    Motor impairment is one of the most frequent symptoms among stroke patients and often leads to poststroke dependency. Recent advances of diffusion tensor MR imaging made it possible to identify corticospinal tract (CST) three-dimensionally and evaluate structural damage, so precise evaluation of the ischemic CST damage became feasible.Motor impairment, lesion size and location upon diffusion weighted MR image and clinical outcome were assessed in 23 acute to subacute capsular and corona radiata infarct patients. According to the lesion size, patients were grouped into A, maximal diameter below 15 mm and B, that above 15 mm. Motor impairment was graded severe: limb movement synergy level, moderate: selective muscle activity possible and mild: isolated movements well co-ordinated, each corresponding to Brunnstrom stage 1-3, 4-5, and 6, respectively. Outcome at the time of discharge was assessed by modified Rankin Scale (mRS), discharge destination and length of hospital stay were also registered. Diffusion tensor MR imaging was conducted in 15 corona radiata infarct patients at 2.3+-2.2 days from the onset of the clinical symptoms. CST was 3-dimensionally identified with dTV. II. SR and Volume-one 1.72 and CST-FA ratio (ipsi-/contralesional CST-FA) and CST-Area% (CST lesion free area/whole CST area) were obtained at the level where ischemic damage was most prominent and correlation of these parameters to motor impairment and clinical outcome was studied. CST-FA ratio and CST-Area% were in good correlation to motor impairment at presentation. Patients with severe motor impairment had lower CST-FA ratio and CSF-Area% than those with moderate or mild. CST-FA ratio was 0.73+-0.22 in patients with poor clinical outcome (mRS 3-6) and 0.93+-0.09 with good clinical outcome (mRS 0-2) (p=0.038). Diffusion tensor MR imaging is useful in evaluating motor impairment and predicting functional outcome of corona radiata infarct patient in the acute to subacute stage. (author)

  8. Sebum and Hydration Levels in Specific Regions of Human Face Significantly Predict the Nature and Diversity of Facial Skin Microbiome.

    Science.gov (United States)

    Mukherjee, Souvik; Mitra, Rupak; Maitra, Arindam; Gupta, Satyaranjan; Kumaran, Srikala; Chakrabortty, Amit; Majumder, Partha P

    2016-10-27

    The skin microbiome varies across individuals. The causes of these variations are inadequately understood. We tested the hypothesis that inter-individual variation in facial skin microbiome can be significantly explained by variation in sebum and hydration levels in specific facial regions of humans. We measured sebum and hydration from forehead and cheek regions of healthy female volunteers (n = 30). Metagenomic DNA from skin swabs were sequenced for V3-V5 regions of 16S rRNA gene. Altogether, 34 phyla were identified; predominantly Actinobacteria (66.3%), Firmicutes (17.7%), Proteobacteria (13.1%) and Bacteroidetes (1.4%). About 1000 genera were identified; predominantly Propionibacterium (58.6%), Staphylococcus (8.6%), Streptococcus (4.0%), Corynebacterium (3.6%) and Paracoccus (3.3%). A subset (n = 24) of individuals were sampled two months later. Stepwise multiple regression analysis showed that cheek sebum level was the most significant predictor of microbiome composition and diversity followed by forehead hydration level; forehead sebum and cheek hydration levels were not. With increase in cheek sebum, the prevalence of Actinobacteria (p = 0.001)/Propionibacterium (p = 0.002) increased, whereas microbiome diversity decreased (Shannon Index, p = 0.032); this was opposite for other phyla/genera. These trends were reversed for forehead hydration levels. Therefore, the nature and diversity of facial skin microbiome is jointly determined by site-specific lipid and water levels in the stratum corneum.

  9. Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods

    Directory of Open Access Journals (Sweden)

    Xiaodan Tan

    2017-12-01

    with variable weights in three templates. The significantly improved prediction accuracy of ASSR achieved by MSAD strongly supports the linear superposition mechanism of ASSR if an accurate template of transient AEPs can be reconstructed. The capacity in obtaining both ASSR and its underlying transient components accurately and simultaneously has the potential to contribute significantly to diagnosis of patients with neuropsychiatric disorders.

  10. Flexible deep-ultraviolet light-emitting diodes for significant improvement of quantum efficiencies by external bending

    KAUST Repository

    Shervin, Shahab; Oh, Seung Kyu; Park, Hyun Jung; Lee, Keon Hwa; Asadirad, Mojtaba; Kim, Seung Hwan; Kim, Jeomoh; Pouladi, Sara; Lee, Sung-Nam; Li, Xiaohang; Kwak, Joon-Seop; Ryou, Jae-Hyun

    2018-01-01

    Deep ultraviolet (DUV) light at the wavelength range of 250‒280 nm (UVC spectrum) is essential for numerous applications such as sterilization, purification, sensing, and communication. III-nitride-based DUV light-emitting diodes (DUV LEDs), like other solid-state lighting sources, offer a great potential to replace the conventional gas-discharged lamps with short lifetimes and toxic-element-bearing nature. However, unlike visible LEDs, the DUV LEDs are still suffering from low quantum efficiencies (QEs) and low optical output powers. In this work, reported is a new route to improve QEs of AlGaN-based DUV LEDs using mechanical flexibility of recently developed bendable thin-film structures. Numerical studies show that electronic band structures of AlGaN heterostructures and resulting optical and electrical characteristics of the devices can be significantly modified by external bending through active control of piezoelectric polarization. Internal quantum efficiency (IQE) is enhanced higher than three times, when the DUV LEDs are moderately bent to induce in-plane compressive strain in the heterostructure. Furthermore, efficiency droop at high injection currents is mitigated and turn-on voltage of diodes decreases with the same bending condition. The concept of bendable DUV LEDs with a controlled external strain can provide a new path for high-output-power and high-efficiency devices.

  11. Flexible deep-ultraviolet light-emitting diodes for significant improvement of quantum efficiencies by external bending

    KAUST Repository

    Shervin, Shahab

    2018-01-26

    Deep ultraviolet (DUV) light at the wavelength range of 250‒280 nm (UVC spectrum) is essential for numerous applications such as sterilization, purification, sensing, and communication. III-nitride-based DUV light-emitting diodes (DUV LEDs), like other solid-state lighting sources, offer a great potential to replace the conventional gas-discharged lamps with short lifetimes and toxic-element-bearing nature. However, unlike visible LEDs, the DUV LEDs are still suffering from low quantum efficiencies (QEs) and low optical output powers. In this work, reported is a new route to improve QEs of AlGaN-based DUV LEDs using mechanical flexibility of recently developed bendable thin-film structures. Numerical studies show that electronic band structures of AlGaN heterostructures and resulting optical and electrical characteristics of the devices can be significantly modified by external bending through active control of piezoelectric polarization. Internal quantum efficiency (IQE) is enhanced higher than three times, when the DUV LEDs are moderately bent to induce in-plane compressive strain in the heterostructure. Furthermore, efficiency droop at high injection currents is mitigated and turn-on voltage of diodes decreases with the same bending condition. The concept of bendable DUV LEDs with a controlled external strain can provide a new path for high-output-power and high-efficiency devices.

  12. Novel ventilation design of combining spacer and mesh structure in sports T-shirt significantly improves thermal comfort.

    Science.gov (United States)

    Sun, Chao; Au, Joe Sau-chuen; Fan, Jintu; Zheng, Rong

    2015-05-01

    This paper reports on novel ventilation design in sports T-shirt, which combines spacer and mesh structure, and experimental evidence on the advantages of design in improving thermal comfort. Evaporative resistance (Re) and thermal insulation (Rc) of T-shirts were measured using a sweating thermal manikin under three different air velocities. Moisture permeability index (i(m)) was calculated to compare the different designed T-shirts. The T-shirts of new and conventional designs were also compared by wearer trials, which were comprised of 30 min treadmill running followed by 10 min rest. Skin temperature, skin relative humidity, heart rate, oxygen inhalation and energy expenditure were monitored, and subjective sensations were asked. Results demonstrated that novel T-shirt has 11.1% significant lower im than control sample under windy condition. The novel T-shirt contributes to reduce the variation of skin temperature and relative humidity up to 37% and 32%, as well as decrease 3.3% energy consumption during exercise. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  13. Significant improvement of thermal stability of glucose 1-dehydrogenase by introducing disulfide bonds at the tetramer interface.

    Science.gov (United States)

    Ding, Haitao; Gao, Fen; Liu, Danfeng; Li, Zeli; Xu, Xiaohong; Wu, Min; Zhao, Yuhua

    2013-12-10

    Rational design was applied to glucose 1-dehydrogenase (LsGDH) from Lysinibacillus sphaericus G10 to improve its thermal stability by introduction of disulfide bridges between subunits. One out of the eleven mutants, designated as DS255, displayed significantly enhanced thermal stability with considerable soluble expression and high specific activity. It was extremely stable at pH ranging from 4.5 to 10.5, as it retained nearly 100% activity after incubating at different buffers for 1h. Mutant DS255 also exhibited high thermostability, having a half-life of 9900min at 50°C, which was 1868-fold as that of its wild type. Moreover, both of the increased free energy of denaturation and decreased entropy of denaturation of DS255 suggested that the enzyme structure was stabilized by the engineered disulfide bonds. On account of its robust stability, mutant DS255 would be a competitive candidate in practical applications of chiral chemicals synthesis, biofuel cells and glucose biosensors. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Imparting improvements in electrochemical sensors: evaluation of different carbon blacks that give rise to significant improvement in the performance of electroanalytical sensing platforms

    International Nuclear Information System (INIS)

    Vicentini, Fernando Campanhã; Ravanini, Amanda E.; Figueiredo-Filho, Luiz C.S.; Iniesta, Jesús; Banks, Craig E.; Fatibello-Filho, Orlando

    2015-01-01

    Three different carbon black materials have been evaluated as a potential modifier, however, only one demonstrated an improvement in the electrochemical properties. The carbon black structures were characterised with SEM, XPS and Raman spectroscopy and found to be very similar to that of amorphous graphitic materials. The modifications utilised were constructed by three different strategies (using ultrapure water, chitosan and dihexadecylphosphate). The fabricated sensors are electrochemically characterised using N,N,N',N'-tetramethyl-para-phenylenediamine and both inner-sphere and outer-sphere redox probes, namely potassium ferrocyanide(II) and hexaammineruthenium(III) chloride, in addition to the biologically relevant and electroactive analytes, dopamine (DA) and acetaminophen (AP). Comparisons are made with an edge-plane pyrolytic graphite and glassy-carbon electrode and the benefits of carbon black implemented as a modifier for sensors within electrochemistry are explored, as well as the characterisation of their electroanalytical performances. We reveal significant improvements in the electrochemical performance (excellent sensitivity, faster heterogeneous electron transfer rate (HET)) over that of a bare glassy-carbon and edge-plane pyrolytic graphite electrode and thus suggest that there are substantial advantages of using carbon black as modifier in the fabrication of electrochemical based sensors. Such work is highly important and informative for those working in the field of electroanalysis where electrochemistry can provide portable, rapid, reliable and accurate sensing protocols (bringing the laboratory into the field), with particular relevance to those searching for new electrode materials

  15. 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

  16. 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

  17. 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

  18. 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.

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

    Science.gov (United States)

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

    2014-12-01

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

  20. 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.

  1. CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.

    Science.gov (United States)

    van Dijk, Lisanne V; Brouwer, Charlotte L; van der Schaaf, Arjen; Burgerhof, Johannes G M; Beukinga, Roelof J; Langendijk, Johannes A; Sijtsema, Nanna M; Steenbakkers, Roel J H M

    2017-02-01

    Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER 12m ) and sticky saliva (STIC 12m ) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XER base ) or sticky saliva (STIC base ) scores. The purpose is to improve prediction of XER 12m and STIC 12m with patient-specific characteristics, based on CT image biomarkers (IBMs). Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping. The prediction of XER 12m could be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XER base . For STIC 12m , the IBM maximum CT intensity of the submandibular gland was selected in addition to STIC base and mean dose to submandibular glands. Prediction of XER 12m and STIC 12m was improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Cryptosporidium and other intestinal parasitic infections among HIV patients in southern Ethiopia: significance of improved HIV-related care.

    Science.gov (United States)

    Shimelis, Techalew; Tassachew, Yayehyirad; Lambiyo, Tariku

    2016-05-10

    Intestinal parasitic infections are known to cause gastroenteritis, leading to higher morbidity and mortality, particularly in people living with HIV/AIDS. This study aimed to determine the prevalence of Cryptosporidium and other intestinal parasitic infections among HIV patients receiving care at a hospital in Ethiopia where previous available baseline data helps assess if improved HIV-related care has reduced infection rates. A cross-sectional study was conducted at Hawassa University Hospital in southern Ethiopia from May, 2013 to March, 2014. A consecutive sample of 491 HIV- infected patients with diarrhea or a CD4 T cell count intestinal parasites. The study was approved by the Institutional Review Board of the College of Medicine and Health Sciences, Hawassa University. Physicians managed participants found to be infected with any pathogenic intestinal parasite. The overall prevalence of intestinal parasitic infections among the study population was 35.8 %. The most prevalent parasites were Cryptosporidium (13.2 %), followed by Entamoeba histolytica/dispar (10.2 %), and Giardia lamblia (7.9 %). The rate of single and multiple infections were 25.5 and 10.3 %, respectively. Patients with a CD4 T cell count intestinal parasitic infection or cryptosporidiosis compared to those with counts ≥ 200 cells/μl, but with some type of diarrhea. The study shows high prevalence of intestinal parasitic infections in the study population. However, the results in the current report are significantly lower compared to previous findings in the same hospital. The observed lower infection rate is encouraging and supports the need to strengthen and sustain the existing intervention measures in order to further reduce intestinal parasitic infections in people living with HIV/AIDS.

  3. Extended-release niacin/laropiprant significantly improves lipid levels in type 2 diabetes mellitus irrespective of baseline glycemic control

    Directory of Open Access Journals (Sweden)

    Bays HE

    2015-02-01

    Full Text Available Harold E Bays,1 Eliot A Brinton,2 Joseph Triscari,3 Erluo Chen,3 Darbie Maccubbin,3 Alexandra A MacLean,3 Kendra L Gibson,3 Rae Ann Ruck,3 Amy O Johnson-Levonas,3 Edward A O’Neill,3 Yale B Mitchel3 1Louisville Metabolic & Atherosclerosis Research Center (L-MARC, Louisville, KY, USA; 2Utah Foundation for Biomedical Research, Salt Lake City, UT, USA; 3Merck & Co, Inc., Whitehouse Station, NJ, USA Background: The degree of glycemic control in patients with type 2 diabetes mellitus (T2DM may alter lipid levels and may alter the efficacy of lipid-modifying agents. Objective: Evaluate the lipid-modifying efficacy of extended-release niacin/laropiprant (ERN/LRPT in subgroups of patients with T2DM with better or poorer glycemic control. Methods: Post hoc analysis of clinical trial data from patients with T2DM who were randomized 4:3 to double-blind ERN/LRPT or placebo (n=796, examining the lipid-modifying effects of ERN/LRPT in patients with glycosylated hemoglobin or fasting plasma glucose levels above and below median baseline levels. Results: At Week 12 of treatment, ERN/LRPT significantly improved low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C, non-high-density lipoprotein cholesterol, triglycerides, and lipoprotein (a, compared with placebo, with equal efficacy in patients above or below median baseline glycemic control. Compared with placebo, over 36 weeks of treatment more patients treated with ERN/LRPT had worsening of their diabetes and required intensification of antihyperglycemic medication, irrespective of baseline glycemic control. Incidences of other adverse experiences were generally low in all treatment groups. Conclusion: The lipid-modifying effects of ERN/LRPT are independent of the degree of baseline glycemic control in patients with T2DM (NCT00485758. Keywords: lipid-modifying agents, hyperglycemia, LDL, HDL, triglycerides

  4. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

    Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

    2017-12-01

    Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

  5. Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

    Science.gov (United States)

    Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

    2018-04-15

    Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen

  6. Improvement of NO and CO predictions for a homogeneous combustion SI engine using a novel emissions model

    International Nuclear Information System (INIS)

    Karvountzis-Kontakiotis, Apostolos; Ntziachristos, Leonidas

    2016-01-01

    Highlights: • Presentation of a novel emissions model to predict pollutants formation in engines. • Model based on detailed chemistry, requires no application-specific calibration. • Combined with 0D and 1D combustion models with low additional computational cost. • Demonstrates accurate prediction of cyclic variability of pollutants emissions. - Abstract: This study proposes a novel emissions model for the prediction of spark ignition (SI) engine emissions at homogeneous combustion conditions, using post combustion analysis and a detailed chemistry mechanism. The novel emissions model considers an unburned and a burned zone, where the latter is considered as a homogeneous reactor and is modeled using a detailed chemical kinetics mechanism. This allows detailed emission predictions at high speed practically based only on combustion pressure and temperature profiles, without the need for calibration of the model parameters. The predictability of the emissions model is compared against the extended Zeldovich mechanism for NO and a simplified two-step reaction kinetic model for CO, which both constitute the most widespread existing approaches in the literature. Under various engine load and speed conditions examined, the mean error in NO prediction was 28% for the existing models and less than 1.3% for the new model proposed. The novel emissions model was also used to predict emissions variation due to cyclic combustion variability and demonstrated mean prediction error of 6% and 3.6% for NO and CO respectively, compared to 36% (NO) and 67% (CO) for the simplified model. The results show that the emissions model proposed offers substantial improvements in the prediction of the results without significant increase in calculation time.

  7. 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).

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. 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...

  14. 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.

  15. 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 ...

  16. 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

  17. Interventions that effectively target Anopheles funestus mosquitoes could significantly improve control of persistent malaria transmission in south-eastern Tanzania.

    Science.gov (United States)

    Kaindoa, Emmanuel W; Matowo, Nancy S; Ngowo, Halfan S; Mkandawile, Gustav; Mmbando, Arnold; Finda, Marcelina; Okumu, Fredros O

    2017-01-01

    An. arabiensis (44.1%). Though An. arabiensis is still the most abundant vector species here, the remaining malaria transmission is predominantly mediated by An. funestus, possibly due to high insecticide resistance and high survival probabilities. Interventions that effectively target An. funestus mosquitoes could therefore significantly improve control of persistent malaria transmission in south-eastern Tanzania.

  18. Interventions that effectively target Anopheles funestus mosquitoes could significantly improve control of persistent malaria transmission in south–eastern Tanzania

    Science.gov (United States)

    Matowo, Nancy S.; Ngowo, Halfan S.; Mkandawile, Gustav; Mmbando, Arnold; Finda, Marcelina; Okumu, Fredros O.

    2017-01-01

    An. arabiensis (44.1%). Though An. arabiensis is still the most abundant vector species here, the remaining malaria transmission is predominantly mediated by An. funestus, possibly due to high insecticide resistance and high survival probabilities. Interventions that effectively target An. funestus mosquitoes could therefore significantly improve control of persistent malaria transmission in south–eastern Tanzania. PMID:28542335

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J. [Iowa State Univ., Ames, IA (United States)

    2017-12-28

    This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes

  7. Using Terrain Analysis and Remote Sensing to Improve Snow Mass Balance and Runoff Prediction

    Science.gov (United States)

    Venteris, E. R.; Coleman, A. M.; Wigmosta, M. S.

    2010-12-01

    Approximately 70-80% of the water in the international Columbia River basin is sourced from snowmelt. The demand for this water has competing needs, as it is used for agricultural irrigation, municipal, hydro and nuclear power generation, and environmental in-stream flow requirements. Accurate forecasting of water supply is essential for planning current needs and prediction of future demands due to growth and climate change. A significant limitation on current forecasting is spatial and temporal uncertainty in snowpack characteristics, particularly snow water equivalent. Currently, point measurements of snow mass balance are provided by the NRCS SNOTEL network. Each site consists of a snow mass sensor and meteorology station that monitors snow water equivalent, snow depth, precipitation, and temperature. There are currently 152 sites in the mountains of Oregon and Washington. An important step in improving forecasts is determining how representative each SNOTEL site is of the total mass balance of the watershed through a full accounting of the spatiotemporal variability in snowpack processes. This variation is driven by the interaction between meteorological processes, land cover, and landform. Statistical and geostatistical spatial models relate the state of the snowpack (characterized through SNOTEL, snow course measurements, and multispectral remote sensing) to terrain attributes derived from digital elevation models (elevation, aspect, slope, compound topographic index, topographic shading, etc.) and land cover. Time steps representing the progression of the snow season for several meteorologically distinct water years are investigated to identify and quantify dominant physical processes. The spatially distributed snow balance data can be used directly as model inputs to improve short- and long-range hydrologic forecasts.

  8. 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

  9. The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia.

    Science.gov (United States)

    Gougeon, R; Lamarche, M; Yale, J-F; Venuta, T

    2002-12-01

    Predictive equations have been reported to overestimate resting energy expenditure (REE) for obese persons. The presence of hyperglycemia results in elevated REE in obese persons with type 2 diabetes, and its effect on the validity of these equations is unknown. We tested whether (1) indicators of diabetes control were independent associates of REE in type 2 diabetes and (2) their inclusion would improve predictive equations. A cross-sectional study of 65 (25 men, 40 women) obese type 2 diabetic subjects. Variables measured were: REE by ventilated-hood indirect calorimetry, body composition by bioimpedance analysis, body circumferences, fasting plasma glucose (FPG) and hemoglobin A(1c). Data were analyzed using stepwise multiple linear regression. REE, corrected for weight, fat-free mass, age and gender, was significantly greater with FPG>10 mmol/l (P=0.017) and correlated with FPG (P=0.013) and hemoglobin A(1c) as percentage upper limit of normal (P=0.02). Weight was the main determinant of REE. Together with hip circumference and FPG, it explained 81% of the variation. FPG improved the predictability of the equation by >3%. With poor glycemic control, it can represent an increase in REE of up to 8%. Our data indicate that in a population of obese subjects with type 2 diabetes mellitus, REE is better predicted when fasting plasma glucose is included as a variable.

  10. 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.

  11. 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.

  12. 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.

  13. The macrophage activation marker sCD163 combined with markers of the Enhanced Liver Fibrosis (ELF) score predicts clinically significant portal hypertension in patients with cirrhosis

    DEFF Research Database (Denmark)

    Sandahl, T D; McGrail, R; Møller, H J

    2016-01-01

    BACKGROUND: Noninvasive identification of significant portal hypertension in patients with cirrhosis is needed in hepatology practice. AIM: To investigate whether the combination of sCD163 as a hepatic inflammation marker and the fibrosis markers of the Enhanced Liver Fibrosis score (ELF) can...... predict portal hypertension in patients with cirrhosis. METHODS: We measured sCD163 and the ELF components (hyaluronic acid, tissue inhibitor of metalloproteinase-1 and procollagen-III aminopeptide) in two separate cohorts of cirrhosis patients that underwent hepatic vein catheterisation. To test...... the predictive accuracy we developed a CD163-fibrosis portal hypertension score in an estimation cohort (n = 80) and validated the score in an independent cohort (n = 80). A HVPG ≥10 mmHg was considered clinically significant. RESULTS: Both sCD163 and the ELF components increased in a stepwise manner...

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

    Science.gov (United States)

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

    2016-10-01

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

  15. Prostate cancer volume adds significantly to prostate-specific antigen in the prediction of early biochemical failure after external beam radiation therapy

    International Nuclear Information System (INIS)

    D'Amico, Anthony V.; Propert, Kathleen J.

    1996-01-01

    Purpose: A new clinical pretreatment quantity that closely approximates the true prostate cancer volume is defined. Methods and Materials: The cancer-specific prostate-specific antigen (PSA), PSA density, prostate cancer volume (V Ca ), and the volume fraction of the gland involved with carcinoma (V Ca fx) were calculated for 227 prostate cancer patients managed definitively with external beam radiation therapy. 1. PSA density PSA/ultrasound prostate gland volume 2. Cancer-specific PSA = PSA - [PSA from benign epithelial tissue] 3. V Ca = Cancer-specific PSA/[PSA in serum per cm 3 of cancer] 4. V Ca fx = V Ca /ultrasound prostate gland volume A Cox multiple regression analysis was used to test whether any of these-clinical pretreatment parameters added significantly to PSA in predicting early postradiation PSA failure. Results: The prostate cancer volume (p = 0.039) and the volume fraction of the gland involved by carcinoma (p = 0.035) significantly added to the PSA in predicting postradiation PSA failure. Conversely, the PSA density and the cancer-specific PSA did not add significantly (p > 0.05) to PSA in predicting postradiation PSA failure. The 20-month actuarial PSA failure-free rates for patients with calculated tumor volumes of ≤0.5 cm 3 , 0.5-4.0 cm 3 , and >4.0 cm 3 were 92, 80, and 47%, respectively (p = 0.00004). Conclusion: The volume of prostate cancer (V Ca ) and the resulting volume fraction of cancer both added significantly to PSA in their ability to predict for early postradiation PSA failure. These new parameters may be used to select patients in prospective randomized trials that examine the efficacy of combining radiation and androgen ablative therapy in patients with clinically localized disease, who are at high risk for early postradiation PSA failure

  16. Improving the Accuracy of a Heliocentric Potential (HCP Prediction Model for the Aviation Radiation Dose

    Directory of Open Access Journals (Sweden)

    Junga Hwang

    2016-12-01

    Full Text Available The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs, flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA. However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015. In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1 real-time daily sunspot assessments, (2 predictions of the daily HCP by our prediction algorithm, and (3 calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

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

    DEFF Research Database (Denmark)

    Li, Xiujin

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

  18. Improved prediction of reservoir behavior through integration of quantitative geological and petrophysical data

    Energy Technology Data Exchange (ETDEWEB)

    Auman, J. B.; Davies, D. K.; Vessell, R. K.

    1997-08-01

    Methodology that promises improved reservoir characterization and prediction of permeability, production and injection behavior during primary and enhanced recovery operations was demonstrated. The method is based on identifying intervals of unique pore geometry by a combination of image analysis techniques and traditional petrophysical measurements to calculate rock type and estimate permeability and saturation. Results from a complex carbonate and sandstone reservoir were presented as illustrative examples of the versatility and high level of accuracy of this method in predicting reservoir quality. 16 refs., 5 tabs., 14 figs.

  19. Significant survival improvement of patients with recurrent breast cancer in the periods 2001-2008 vs. 1992-2000

    Directory of Open Access Journals (Sweden)

    Nishimura Sumiko

    2011-03-01

    Full Text Available Abstract Background It is unclear whether individualized treatments based on biological factors have improved the prognosis of recurrent breast cancer. The purpose of this study is to evaluate the survival improvement of patients with recurrent breast cancer after the introduction of third generation aromatase inhibitors (AIs and trastuzumab. Methods A total of 407 patients who received first diagnosis of recurrent breast cancer and treatment at National Kyushu Cancer Center between 1992 and 2008 were retrospectively evaluated. As AIs and trastuzumab were approved for clinical use in Japan in 2001, the patients were divided into two time cohorts depending on whether the cancer recurred before or after 2001. Cohort A: 170 patients who were diagnosed between 1992 and 2000. Cohort B: 237 patients who were diagnosed between 2001 and 2008. Tumor characteristics, treatments, and outcome were compared. Results Fourteen percent of cohort A and 76% of cohort B received AIs and/or trastuzumab (P Conclusions The prognosis of patients with recurrent breast cancer was improved over time following the introduction of AIs and trastuzumab and the survival improvement was apparent in HR- and/or HER-2-positive tumors.

  20. Significant Improvement in Sleep in People with Intellectual Disabilities Living in Residential Settings by Non-Pharmaceutical Interventions

    Science.gov (United States)

    Hylkema, T.; Vlaskamp, C.

    2009-01-01

    Background: Although about 15 to 50 percent of people with intellectual disabilities (ID) living in residential settings suffer from sleep problems, scant attention is paid to these problems. Most available studies focus on pharmaceutical solutions. In this study we focus on improving sleep in people with intellectual disabilities living in…

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

    Science.gov (United States)

    Ickes, Jacob C.

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

  2. Missing Value Imputation Improves Mortality Risk Prediction Following Cardiac Surgery: An Investigation of an Australian Patient Cohort.

    Science.gov (United States)

    Karim, Md Nazmul; Reid, Christopher M; Tran, Lavinia; Cochrane, Andrew; Billah, Baki

    2017-03-01

    The aim of this study was to evaluate the impact of missing values on the prediction performance of the model predicting 30-day mortality following cardiac surgery as an example. Information from 83,309 eligible patients, who underwent cardiac surgery, recorded in the Australia and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database registry between 2001 and 2014, was used. An existing 30-day mortality risk prediction model developed from ANZSCTS database was re-estimated using the complete cases (CC) analysis and using multiple imputation (MI) analysis. Agreement between the risks generated by the CC and MI analysis approaches was assessed by the Bland-Altman method. Performances of the two models were compared. One or more missing predictor variables were present in 15.8% of the patients in the dataset. The Bland-Altman plot demonstrated significant disagreement between the risk scores (prisk of mortality. Compared to CC analysis, MI analysis resulted in an average of 8.5% decrease in standard error, a measure of uncertainty. The MI model provided better prediction of mortality risk (observed: 2.69%; MI: 2.63% versus CC: 2.37%, Pvalues improved the 30-day mortality risk prediction following cardiac surgery. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  3. Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

    Science.gov (United States)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

    Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

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

    International Nuclear Information System (INIS)

    Lim, Jonh Seon

    2002-02-01

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

  5. SU-D-BRB-02: Combining a Commercial Autoplanning Engine with Database Dose Predictions to Further Improve Plan Quality

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, SP; Moore, JA; Hui, X; Cheng, Z; McNutt, TR [Johns Hopkins University, Baltimore, MD (United States); DeWeese, TL; Tran, P; Quon, H [John Hopkins Hospital, Baltimore, MD (United States); Bzdusek, K [Philips, Fitchburg, WI (United States); Kumar, P [Philips India Limited, Bangalore, Karnataka (India)

    2016-06-15

    Purpose: Database dose predictions and a commercial autoplanning engine both improve treatment plan quality in different but complimentary ways. The combination of these planning techniques is hypothesized to further improve plan quality. Methods: Four treatment plans were generated for each of 10 head and neck (HN) and 10 prostate cancer patients, including Plan-A: traditional IMRT optimization using clinically relevant default objectives; Plan-B: traditional IMRT optimization using database dose predictions; Plan-C: autoplanning using default objectives; and Plan-D: autoplanning using database dose predictions. One optimization was used for each planning method. Dose distributions were normalized to 95% of the planning target volume (prostate: 8000 cGy; HN: 7000 cGy). Objectives used in plan optimization and analysis were the larynx (25%, 50%, 90%), left and right parotid glands (50%, 85%), spinal cord (0%, 50%), rectum and bladder (0%, 20%, 50%, 80%), and left and right femoral heads (0%, 70%). Results: All objectives except larynx 25% and 50% resulted in statistically significant differences between plans (Friedman’s χ{sup 2} ≥ 11.2; p ≤ 0.011). Maximum dose to the rectum (Plans A-D: 8328, 8395, 8489, 8537 cGy) and bladder (Plans A-D: 8403, 8448, 8527, 8569 cGy) were significantly increased. All other significant differences reflected a decrease in dose. Plans B-D were significantly different from Plan-A for 3, 17, and 19 objectives, respectively. Plans C-D were also significantly different from Plan-B for 8 and 13 objectives, respectively. In one case (cord 50%), Plan-D provided significantly lower dose than plan C (p = 0.003). Conclusion: Combining database dose predictions with a commercial autoplanning engine resulted in significant plan quality differences for the greatest number of objectives. This translated to plan quality improvements in most cases, although special care may be needed for maximum dose constraints. Further evaluation is warranted

  6. Sub-seasonal prediction of significant wave heights over the Western Pacific and Indian Oceans, part II: The impact of ENSO and MJO

    Science.gov (United States)

    Shukla, Ravi P.; Kinter, James L.; Shin, Chul-Su

    2018-03-01

    This study evaluates the effect of El Niño and the Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) events on 14-day mean significant wave height (SWH) at 3 weeks lead time (Wk34) over the Western Pacific and Indian Oceans using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2). The WAVEWATCH-3 (WW3) model is forced with daily 10m-winds predicted by a modified version of CFSv2 that is initialized with multiple ocean analyses in both January and May for 1979-2008. A significant anomaly correlation of predicted and observed SWH anomalies (SWHA) at Wk34 lead-time is found over portions of the domain, including the central western Pacific, South China Sea (SCS), Bay of Bengal (BOB) and southern Indian Ocean (IO) in January cases, and over BOB, equatorial western Pacific, the Maritime Continent and southern IO in May cases. The model successfully predicts almost all the important features of the observed composite SWHA during El Niño events in January, including negative SWHA in the central IO where westerly wind anomalies act on an easterly mean state, and positive SWHA over the southern Ocean (SO) where westerly wind anomalies act on a westerly mean state. The model successfully predicts the sign and magnitude of SWHA at Wk34 lead-time in May over the BOB and SCS in composites of combined phases-2-3 and phases-6-7 of MJO. The observed leading mode of SWHA in May and the third mode of SWHA in January are influenced by the combined effects of ENSO and MJO. Based on spatial and temporal correlations, the spatial patterns of SWHA in the model at Wk34 in both January and May are in good agreement with the observations over the equatorial western Pacific, equatorial and southern IO, and SO.

  7. A genetic risk score combining ten psoriasis risk loci improves disease prediction.

    Directory of Open Access Journals (Sweden)

    Haoyan Chen

    2011-04-01

    Full Text Available Psoriasis is a chronic, immune-mediated skin disease affecting 2-3% of Caucasians. Recent genetic association studies have identified multiple psoriasis risk loci; however, most of these loci contribute only modestly to disease risk. In this study, we investigated whether a genetic risk score (GRS combining multiple loci could improve psoriasis prediction. Two approaches were used: a simple risk alleles count (cGRS and a weighted (wGRS approach. Ten psoriasis risk SNPs were genotyped in 2815 case-control samples and 858 family samples. We found that the total number of risk alleles in the cases was significantly higher than in controls, mean 13.16 (SD 1.7 versus 12.09 (SD 1.8, p = 4.577×10(-40. The wGRS captured considerably more risk than any SNP considered alone, with a psoriasis OR for high-low wGRS quartiles of 10.55 (95% CI 7.63-14.57, p = 2.010×10(-65. To compare the discriminatory ability of the GRS models, receiver operating characteristic curves were used to calculate the area under the curve (AUC. The AUC for wGRS was significantly greater than for cGRS (72.0% versus 66.5%, p = 2.13×10(-8. Additionally, the AUC for HLA-C alone (rs10484554 was equivalent to the AUC for all nine other risk loci combined (66.2% versus 63.8%, p = 0.18, highlighting the dominance of HLA-C as a risk locus. Logistic regression revealed that the wGRS was significantly associated with two subphenotypes of psoriasis, age of onset (p = 4.91×10(-6 and family history (p = 0.020. Using a liability threshold model, we estimated that the 10 risk loci account for only 11.6% of the genetic variance in psoriasis. In summary, we found that a GRS combining 10 psoriasis risk loci captured significantly more risk than any individual SNP and was associated with early onset of disease and a positive family history. Notably, only a small fraction of psoriasis heritability is captured by the common risk variants identified to date.

  8. Brief Communication: Upper Air Relaxation in RACMO2 Significantly Improves Modelled Interannual Surface Mass Balance Variability in Antarctica

    Science.gov (United States)

    van de Berg, W. J.; Medley, B.

    2016-01-01

    The Regional Atmospheric Climate Model (RACMO2) has been a powerful tool for improving surface mass balance (SMB) estimates from GCMs or reanalyses. However, new yearly SMB observations for West Antarctica show that the modelled interannual variability in SMB is poorly simulated by RACMO2, in contrast to ERA-Interim, which resolves this variability well. In an attempt to remedy RACMO2 performance, we included additional upper-air relaxation (UAR) in RACMO2. With UAR, the correlation to observations is similar for RACMO2 and ERA-Interim. The spatial SMB patterns and ice-sheet-integrated SMB modelled using UAR remain very similar to the estimates of RACMO2 without UAR. We only observe an upstream smoothing of precipitation in regions with very steep topography like the Antarctic Peninsula. We conclude that UAR is a useful improvement for regional climate model simulations, although results in regions with steep topography should be treated with care.

  9. Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    2017-03-01

    Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

  10. Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

    Science.gov (United States)

    Wang, R.; Chen, J. M.; Luo, X.

    2016-12-01

    Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

  11. Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2015-10-01

    Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.

  12. A New Approach to Improve Accuracy of Grey Model GMC(1,n in Time Series Prediction

    Directory of Open Access Journals (Sweden)

    Sompop Moonchai

    2015-01-01

    Full Text Available This paper presents a modified grey model GMC(1,n for use in systems that involve one dependent system behavior and n-1 relative factors. The proposed model was developed from the conventional GMC(1,n model in order to improve its prediction accuracy by modifying the formula for calculating the background value, the system of parameter estimation, and the model prediction equation. The modified GMC(1,n model was verified by two cases: the study of forecasting CO2 emission in Thailand and forecasting electricity consumption in Thailand. The results demonstrated that the modified GMC(1,n model was able to achieve higher fitting and prediction accuracy compared with the conventional GMC(1,n and D-GMC(1,n models.

  13. Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

    Science.gov (United States)

    Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

    2016-01-01

    Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

  14. Improved time series prediction with a new method for selection of model parameters

    International Nuclear Information System (INIS)

    Jade, A M; Jayaraman, V K; Kulkarni, B D

    2006-01-01

    A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

  15. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

    Science.gov (United States)

    Stegen, James C

    2018-01-01

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

  16. Validation of three noninvasive laboratory variables to predict significant fibrosis and cirrhosis in patients with chronic hepatitis C in Saudi Arabia

    International Nuclear Information System (INIS)

    Ado, Ayman A.; Al-Swat, Khalid; Azzam, N.; Al-Faleh, Faleh; Ahmed, S.

    2007-01-01

    We tested the clinical utility of the platelet count, aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio, and the AST to platelet ratio index (APRI) score in predicting the presence or absence of advanced fibrosis and cirrhosis in patients with chronic hepatitis C in Saudi Arabia. Liver biopsy procedures performed on chronic hepatitis C patients in our gastroenterology unit at King Khalid University Hospital were traced form records between 1998 to 2003. The hospital computer database was then accessed and detailed laboratory parameters obtained. By plotting receiver operating characteristic curves (ROC), three selected models (platelet count, AST/ALT ratio and the APRI score) were compared in terms of the best variable to predict significant fibrosis. Two hundred and forty-six patients with hepatitis C were included in this analysis. Overall, 26% of patients had advanced fibrosis. When comparing the three above mentioned prediction models, APRI score was the one associated with the highest area under the curve (AUC) = 0.812 (95%Cl, 0.756-0.868) on the ROC curves, compared to the platelet count and AST/ALT ratio, which yielded an AUC of 0.783 (0.711-0.855) and 0.716 (0.642-0.789), respectively. The APRI score seemed to be the best predictive variable for the presence or absence of advanced fibrosis in Saudi hepatitis C patients. (author)

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Improved Seasonal Prediction of European Summer Temperatures With New Five-Layer Soil-Hydrology Scheme

    Science.gov (United States)

    Bunzel, Felix; Müller, Wolfgang A.; Dobrynin, Mikhail; Fröhlich, Kristina; Hagemann, Stefan; Pohlmann, Holger; Stacke, Tobias; Baehr, Johanna

    2018-01-01

    We evaluate the impact of a new five-layer soil-hydrology scheme on seasonal hindcast skill of 2 m temperatures over Europe obtained with the Max Planck Institute Earth System Model (MPI-ESM). Assimilation experiments from 1981 to 2010 and 10-member seasonal hindcasts initialized on 1 May each year are performed with MPI-ESM in two soil configurations, one using a bucket scheme and one a new five-layer soil-hydrology scheme. We find the seasonal hindcast skill for European summer temperatures to improve with the five-layer scheme compared to the bucket scheme and investigate possible causes for these improvements. First, improved indirect soil moisture assimilation allows for enhanced soil moisture-temperature feedbacks in the hindcasts. Additionally, this leads to improved prediction of anomalies in the 500 hPa geopotential height surface, reflecting more realistic atmospheric circulation patterns over Europe.

  19. Breast calcifications. A standardized mammographic reporting and data system to improve positive predictive value

    International Nuclear Information System (INIS)

    Perugini, G.; Bonzanini, B.; Valentino, C.

    1999-01-01

    The purpose of this work is to investigate the usefulness of a standardized reporting and data system in improving the positive predictive value of mammography in breast calcifications. Using the Breast Imaging Reporting and Data System lexicon developed by the American College of Radiology, it is defined 5 descriptive categories of breast calcifications and classified diagnostic suspicion of malignancy on a 3-grade scale (low, intermediate and high). Two radiologists reviewed 117 mammographic studies selected from those of the patients submitted to surgical biopsy for mammographically detected calcifications from January 1993 to December 1997, and classified them according to the above criteria. The positive predictive value was calculated for all examinations and for the stratified groups. Defining a standardized system for assessing and describing breast calcifications helps improve the diagnostic accuracy of mammography in clinical practice [it

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

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2015-01-01

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

  1. A Model Predictive Control Approach for Fuel Economy Improvement of a Series Hydraulic Hybrid Vehicle

    Directory of Open Access Journals (Sweden)

    Tri-Vien Vu

    2014-10-01

    Full Text Available This study applied a model predictive control (MPC framework to solve the cruising control problem of a series hydraulic hybrid vehicle (SHHV. The controller not only regulates vehicle velocity, but also engine torque, engine speed, and accumulator pressure to their corresponding reference values. At each time step, a quadratic programming problem is solved within a predictive horizon to obtain the optimal control inputs. The objective is to minimize the output error. This approach ensures that the components operate at high efficiency thereby improving the total efficiency of the system. The proposed SHHV control system was evaluated under urban and highway driving conditions. By handling constraints and input-output interactions, the MPC-based control system ensures that the system operates safely and efficiently. The fuel economy of the proposed control scheme shows a noticeable improvement in comparison with the PID-based system, in which three Proportional-Integral-Derivative (PID controllers are used for cruising control.

  2. 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.

  3. Towards improved hydrologic predictions using data assimilation techniques for water resource management at the continental scale

    Science.gov (United States)

    Naz, Bibi; Kurtz, Wolfgang; Kollet, Stefan; Hendricks Franssen, Harrie-Jan; Sharples, Wendy; Görgen, Klaus; Keune, Jessica; Kulkarni, Ketan

    2017-04-01

    More accurate and reliable hydrologic simulations are important for many applications such as water resource management, future water availability projections and predictions of extreme events. However, simulation of spatial and temporal variations in the critical water budget components such as precipitation, snow, evaporation and runoff is highly uncertain, due to errors in e.g. model structure and inputs (hydrologic parameters and forcings). In this study, we use data assimilation techniques to improve the predictability of continental-scale water fluxes using in-situ measurements along with remotely sensed information to improve hydrologic predications for water resource systems. The Community Land Model, version 3.5 (CLM) integrated with the Parallel Data Assimilation Framework (PDAF) was implemented at spatial resolution of 1/36 degree (3 km) over the European CORDEX domain. The modeling system was forced with a high-resolution reanalysis system COSMO-REA6 from Hans-Ertel Centre for Weather Research (HErZ) and ERA-Interim datasets for time period of 1994-2014. A series of data assimilation experiments were conducted to assess the efficiency of assimilation of various observations, such as river discharge data, remotely sensed soil moisture, terrestrial water storage and snow measurements into the CLM-PDAF at regional to continental scales. This setup not only allows to quantify uncertainties, but also improves streamflow predictions by updating simultaneously model states and parameters utilizing observational information. The results from different regions, watershed sizes, spatial resolutions and timescales are compared and discussed in this study.

  4. Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

    Science.gov (United States)

    Katzner, Steffen; Treue, Stefan; Busse, Laura

    2012-09-04

    One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

  5. Clinical Significance of the Prognostic Nutritional Index for Predicting Short- and Long-Term Surgical Outcomes After Gastrectomy: A Retrospective Analysis of 7781 Gastric Cancer Patients.

    Science.gov (United States)

    Lee, Jee Youn; Kim, Hyoung-Il; Kim, You-Na; Hong, Jung Hwa; Alshomimi, Saeed; An, Ji Yeong; Cheong, Jae-Ho; Hyung, Woo Jin; Noh, Sung Hoon; Kim, Choong-Bai

    2016-05-01

    To evaluate the predictive and prognostic significance of the prognostic nutritional index (PNI) in a large cohort of gastric cancer patients who underwent gastrectomy.Assessing a patient's immune and nutritional status, PNI has been reported as a predictive marker for surgical outcomes in various types of cancer.We retrospectively reviewed data from a prospectively maintained database of 7781 gastric cancer patients who underwent gastrectomy from January 2001 to December 2010 at a single center. From this data, we analyzed clinicopathologic characteristics, PNI, and short- and long-term surgical outcomes for each patient. We used the PNI value for the 10th percentile (46.70) of the study cohort as a cut-off for dividing patients into low and high PNI groups.Regarding short-term outcomes, multivariate analysis showed a low PNI (odds ratio [OR] = 1.505, 95% CI = 1.212-1.869, P cancer recurrence.

  6. An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

    Science.gov (United States)

    Dash, Rajashree

    2017-11-01

    Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

  7. RAPID COMMUNICATION: Improving prediction accuracy of GPS satellite clocks with periodic variation behaviour

    Science.gov (United States)

    Heo, Youn Jeong; Cho, Jeongho; Heo, Moon Beom

    2010-07-01

    The broadcast ephemeris and IGS ultra-rapid predicted (IGU-P) products are primarily available for use in real-time GPS applications. The IGU orbit precision has been remarkably improved since late 2007, but its clock products have not shown acceptably high-quality prediction performance. One reason for this fact is that satellite atomic clocks in space can be easily influenced by various factors such as temperature and environment and this leads to complicated aspects like periodic variations, which are not sufficiently described by conventional models. A more reliable prediction model is thus proposed in this paper in order to be utilized particularly in describing the periodic variation behaviour satisfactorily. The proposed prediction model for satellite clocks adds cyclic terms to overcome the periodic effects and adopts delay coordinate embedding, which offers the possibility of accessing linear or nonlinear coupling characteristics like satellite behaviour. The simulation results have shown that the proposed prediction model outperforms the IGU-P solutions at least on a daily basis.

  8. 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.

  9. The Significance of the PD-L1 Expression in Non-Small-Cell Lung Cancer: Trenchant Double Swords as Predictive and Prognostic Markers.

    Science.gov (United States)

    Takada, Kazuki; Toyokawa, Gouji; Shoji, Fumihiro; Okamoto, Tatsuro; Maehara, Yoshihiko

    2018-03-01

    Lung cancer is the leading cause of death due to cancer worldwide. Surgery, chemotherapy, and radiotherapy have been the standard treatment for lung cancer, and targeted molecular therapy has greatly improved the clinical course of patients with non-small-cell lung cancer (NSCLC) harboring driver mutations, such as in epidermal growth factor receptor and anaplastic lymphoma kinase genes. Despite advances in such therapies, the prognosis of patients with NSCLC without driver oncogene mutations remains poor. Immunotherapy targeting programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) has recently been shown to improve the survival in advanced NSCLC. The PD-L1 expression on the surface of tumor cells has emerged as a potential biomarker for predicting responses to immunotherapy and prognosis after surgery in NSCLC. However, the utility of PD-L1 expression as a predictive and prognostic biomarker remains controversial because of the existence of various PD-L1 antibodies, scoring systems, and positivity cutoffs. In this review, we summarize the data from representative clinical trials of PD-1/PD-L1 immune checkpoint inhibitors in NSCLC and previous reports on the association between PD-L1 expression and clinical outcomes in patients with NSCLC. Furthermore, we discuss the future perspectives of immunotherapy and immune checkpoint factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Sobering stories: narratives of self-redemption predict behavioral change and improved health among recovering alcoholics.

    Science.gov (United States)

    Dunlop, William L; Tracy, Jessica L

    2013-03-01

    The present research examined whether the production of a narrative containing self-redemption (wherein the narrator describes a positive personality change following a negative experience) predicts positive behavioral change. In Study 1, we compared the narratives of alcoholics who had maintained their sobriety for over 4 years with those of alcoholics who had been sober 6 months or less. When describing their last drink, the former were significantly more likely to produce a narrative containing self-redemption than the latter. In Study 2, we examined the relation between the profession of self-redemption and behavioral change using a longitudinal design, by following the newly sober alcoholics from Study 1 over time. Although indistinguishable at initial assessment, newly sober alcoholics whose narratives included self-redemption were substantially more likely to maintain sobriety in the following months, compared to newly sober alcoholics who produced nonredemptive narratives; 83% of the redemptive group maintained sobriety between assessments, compared to 44% of nonredemptive participants. Redemptive participants in Study 2 also demonstrated improved health relative to the nonredemptive group. In both studies, the effects of self-redemption on sobriety and health held after controlling for relevant personality traits, alcohol dependence, recovery program involvement, initial physical and mental health, and additional narrative themes. Collectively, these results suggest that the production of a self-redemptive narrative may stimulate prolonged behavioral change and thus indicate a potentially modifiable psychological process that exhibits a major influence on recovery from addiction. PsycINFO Database Record (c) 2013 APA, all rights reserved

  11. Migration ability and Toll-like receptor expression of human mesenchymal stem cells improves significantly after three-dimensional culture.

    Science.gov (United States)

    Zhou, Panpan; Liu, Zilin; Li, Xue; Zhang, Bing; Wang, Xiaoyuan; Lan, Jing; Shi, Qing; Li, Dong; Ju, Xiuli

    2017-09-16

    While the conventional two-dimensional (2D) culture protocol is well accepted for the culture of mesenchymal stem cells (MSCs), this method fails to recapitulate the in vivo native three-dimensional (3D) cellular microenvironment, and may result in phenotypic changes, and homing and migration capacity impairments. MSC preparation in 3D culture systems has been considered an attractive preparatory and delivery method recently. We seeded human umbilical cord-derived MSCs (hUCMSCs) in a 3D culture system with porcine acellular dermal matrix (PADM), and investigated the phenotypic changes, the expression changes of some important receptors, including Toll-like receptors (TLRs) and C-X-C chemokine receptor type 4 (CXCR4) when hUCMSCs were transferred from 2D to 3D systems, as well as the alterations in in vivo homing and migration potential. It was found that the percentage of CD105-positive cells decreased significantly, whereas that of CD34- and CD271-positive cells increased significantly in 3D culture, compared to that in 2D culture. The mRNA and protein expression levels of TLR2, TLR3, TLR4, TLR6, and CXCR4 in hUCMSCs were increased significantly upon culturing with PADM for 3 days, compared to the levels in 2D culture. The numbers of migratory 3D hUCMSCs in the heart, liver, spleen, and bone marrow were significantly greater than the numbers of 2D hUCMSCs, and the worst migration occurred in 3D + AMD3100 (CXCR4 antagonist) hUCMSCs. These results suggested that 3D culture of hUCMSCs with PADM could alter the phenotypic characteristics of hUCMSCs, increase their TLR and CXCR4 expression levels, and promote their migratory and homing capacity in which CXCR4 plays an important role. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. The patient's safety - For a dynamics of improvement. Nr 3. How to analyze your significant radiation protection events?

    International Nuclear Information System (INIS)

    2012-07-01

    The objective of this publication is to present event analysis methods which are the most frequently used by radiotherapy departments. After an indication of key figures concerning radiotherapy patients, sessions and events, the document indicates the objectives and steps of an event analysis. It presents various analysis methods: Ishikawa diagram (or 5M method or causes-effects diagram), the cause tree, the ALARM method (association of litigation and risk management), the ORION method. It proposes a comparison between these five methods, their possibilities, their limits. Good practices are outlined in terms of data acquisition, method choice, event analysis, and improvement actions. The use of the cause tree analysis is commented by members of the Limoges hospital radiotherapy department, and that of the Ishikawa method by a member of the Beauvais hospital

  13. Different surgical strategies for chronic pancreatitis significantly improve long-term outcome: a comparative single center study

    Directory of Open Access Journals (Sweden)

    Hildebrand P

    2010-08-01

    Full Text Available Abstract Objective In general, chronic pancreatitis (CP primarily requires conservative treatment. The chronic pain syndrome and complications make patients seek surgical advice, frequently after years of progression. In the past, surgical procedures involving drainage as well as resection have been employed successfully. The present study compared the different surgical strategies. Patients and Methods From March 2000 until April 2005, a total of 51 patients underwent surgical treatment for CP at the Department of surgery, University of Schleswig-Holstein, Campus Lübeck. Out of those 51 patients, 39 (76.5% were operated according to the Frey procedure, and in 12 cases (23.5% the Whipple procedure was performed. Patient data were documented prospectively throughout the duration of the hospital stay. The evaluation of the postoperative pain score was carried out retrospectively with a validated questionnaire. Results Average operating time was 240 minutes for the Frey group and 411 minutes for the Whipple group. The medium number of blood transfusions was 1 in the Frey group and 4.5 in the Whipple group. Overall morbidity was 21% in the Frey group and 42% in the Whipple group. 30-day mortality was zero for all patients. During the median follow-up period of 50 months, an improvement in pain score was observed in 93% of the patients of the Frey group and 67% of the patients treated according to the Whipple procedure. Conclusion The results show that both the Frey procedure as well as partial pancreaticoduodenectomy are capable of improving chronic pain symptoms in CP. As far as later endocrine and exocrine pancreatic insufficiency is concerned, however, the extended drainage operation according to Frey proves to be advantageous compared to the traditional resection procedure by Whipple. Accordingly, the Frey procedure provides us with an organ-preserving surgical procedure which treats the complications of CP sufficiently, thus being an

  14. Significant improvement of bone mineral density by denosumab treatment in Japanese osteoporotic patients following breast cancer treatment

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    Nakamura Y

    2018-03-01

    Full Text Available Yukio Nakamura,1,2 Mikio Kamimura,3 Akio Morikawa,4 Akira Taguchi,5 Takako Suzuki,1 Hiroyuki Kato1 1Department of Orthopaedic Surgery, Shinshu University School of Medicine, Matsumoto, 2Department of Orthopedic Surgery, Showa-Inan General Hospital, Komagane, 3Center for Osteoporosis and Spinal Disorders, Kamimura Orthopaedic Clinic, Matsumoto, 4Department of Surgery, Showa-Inan General Hospital, Komagane, 5Department of Oral and Maxillofacial Radiology, School of Dentistry, Matsumoto Dental University, Shiojiri, Japan Background: The aim of this study was to evaluate the effects of denosumab in patients with osteoporosis (OP and non-metastatic breast cancer following treatment of 1 surgery, 2 surgery and aromatase inhibitors, and 3 surgery, aromatase inhibitors, and anti-cancer agents, compared with those in primary OP patients. Patients and methods: In this retrospective 24-month study, patients were divided into the primary OP group (34 cases or OP receiving breast cancer treatment group (breast cancer group; 17 cases. We measured serum calcium, whole parathyroid hormone (PTH, 1,25OH2D3, bone alkaline phosphatase (BAP, tartrate-resistant acid phosphatase-5b (TRACP-5b, and bone mineral density (BMD of the lumbar 1–4 vertebrae (L-BMD and bilateral total hips (H-BMD for 24 months. Results: The percent changes of serum calcium in the breast cancer group were significantly lower than those in the primary OP group at 1 week, 1 and 12 months. The percent changes of whole PTH in the primary OP group were significantly lower than those in the breast cancer group at 2 and 4 months. Significant differences were found between the groups at 18 months (-34.5% in the primary OP group and -52.6% in the breast cancer group, respectively for the percent changes of BAP. Significant differences were found between the groups at 12, 18, and 24 months (-39.7% in the primary OP group and -64.0% in the breast cancer group at 24 months, respectively for the percent

  15. Improved Prediction of Falls in Community-Dwelling Older Adults Through Phase-Dependent Entropy of Daily-Life Walking

    Directory of Open Access Journals (Sweden)

    Espen A. F. Ihlen

    2018-03-01

    Full Text Available Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME, and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016. The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME (p < 0.0001 of their trunk acceleration at 60% of their step cycle when compared with non-fallers. No significant differences were found between PGME of multiple-time fallers and non-fallers, but PGME was found to improve the prediction model of multiple-time fallers when combined with other gait features. These findings suggest that taking into account phase-dependent changes in the stability of the gait dynamics has additional value for predicting falls in older people, especially for single-time prospective fallers.

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

    Directory of Open Access Journals (Sweden)

    Evelyn Tai Li Min

    2017-08-01

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

  17. Significant Improvement Selected Mediators of Inflammation in Phenotypes of Women with PCOS after Reduction and Low GI Diet

    Directory of Open Access Journals (Sweden)

    Małgorzata Szczuko

    2017-01-01

    Full Text Available Many researchers suggest an increased risk of atherosclerosis in women with polycystic ovary syndrome. In the available literature, there are no studies on the mediators of inflammation in women with PCOS, especially after dietary intervention. Eicosanoids (HETE and HODE were compared between the biochemical phenotypes of women with PCOS (normal and high androgens and after the 3-month reduction diet. Eicosanoid profiles (9(S-HODE, 13(S-HODE, 5(S-HETE, 12(S-HETE, 15(S-HETE, 5(S-oxoETE, 16(R-HETE, 16(S-HETE and 5(S, 6(R-lipoxin A4, 5(S, 6(R, 15(R-lipoxin A4 were extracted from 0.5 ml of plasma using solid-phase extraction RP-18 SPE columns. The HPLC separations were performed on a 1260 liquid chromatograph. No significant differences were found in the concentration of analysed eicosanoids in phenotypes of women with PCOS. These women, however, have significantly lower concentration of inflammatory mediators than potentially healthy women from the control group. Dietary intervention leads to a significant (p<0.01 increase in the synthesis of proinflammatory mediators, reaching similar levels as in the control group. The development of inflammatory reaction in both phenotypes of women with PCOS is similar. The pathways for synthesis of proinflammatory mediators in women with PCOS are dormant, but can be stimulated through a reduction diet. Three-month period of lifestyle change may be too short to stimulate the pathways inhibiting inflammatory process.

  18. Rapid improvements in emotion regulation predict intensive treatment outcome for patients with bulimia nervosa and purging disorder.

    Science.gov (United States)

    MacDonald, Danielle E; Trottier, Kathryn; Olmsted, Marion P

    2017-10-01

    Rapid and substantial behavior change (RSBC) early in cognitive behavior therapy (CBT) for eating disorders is the strongest known predictor of treatment outcome. Rapid change in other clinically relevant variables may also be important. This study examined whether rapid change in emotion regulation predicted treatment outcomes, beyond the effects of RSBC. Participants were diagnosed with bulimia nervosa or purging disorder (N = 104) and completed ≥6 weeks of CBT-based intensive treatment. Hierarchical regression models were used to test whether rapid change in emotion regulation variables predicted posttreatment outcomes, defined in three ways: (a) binge/purge abstinence; (b) cognitive eating disorder psychopathology; and (c) depression symptoms. Baseline psychopathology and emotion regulation difficulties and RSBC were controlled for. After controlling for baseline variables and RSBC, rapid improvement in access to emotion regulation strategies made significant unique contributions to the prediction of posttreatment binge/purge abstinence, cognitive psychopathology of eating disorders, and depression symptoms. Individuals with eating disorders who rapidly improve their belief that they can effectively modulate negative emotions are more likely to achieve a variety of good treatment outcomes. This supports the formal inclusion of emotion regulation skills early in CBT, and encouraging patient beliefs that these strategies are helpful. © 2017 Wiley Periodicals, Inc.

  19. A study to determine whether targeted education significantly improves the perception of human torture in medical students in India.

    Science.gov (United States)

    Husain, Munawwar; Ghaffar, Usama B; Usmani, Jawed Ahmad; Rivzi, Shameem Jahan

    2010-08-01

    This study was undertaken to find out the knowledge of torture in MBBS students. A fair comparison was done by selecting two groups of medical students; one, to whom torture was not taught ie, pretaught group (PrTG, n = 125), and second, to whom torture was taught in classroom ie, post-taught group (PoTG, n = 110) in more than one sessions. The topic on torture was taught under many headings maximising the effort to cover as much as possible; namely, definition, geographical distribution, types of torture (physical, psychological and sexual), post-torture sequelae, sociopolitical environment prevailing in the country, doctors' involvement in torture, rehabilitation of torture victims and the UNO's role in containment of torture. In all a questionnaire was designed having MCQ types on these aspects. It was found that significant level of difference in perception and knowledge about torture existed amongst the groups, and this was further accentuated in medical and non-medical intratopics. 'P' value of each question was computed separately. It was found that the study was statistically significant and reestablished the need of fortifying the gossameric firmament of education specific to torture.

  20. Drilling for improvement : Statoil and Halliburton report significant cost savings and more accurate well placement at the Leismer demonstration project

    Energy Technology Data Exchange (ETDEWEB)

    Jaremko, D.

    2010-07-15

    This article discussed new improvements in steam assisted gravity drainage (SAGD) made by Statoil and Halliburton at the Leismer demonstration project. The Leismer project is Statoil's inaugural project in oil sands development, and will have a capacity to produce 10,000 barrels per day through 4 separate well pads with 23 well pairs. Challenges to the project included the long lateral sections required for the well pairs to remain parallel to each other while remaining within the target formation. An azimuthal deep resistivity (ADR) tool was used to detect the proximity of the wellbore to shale and water zones. Use of the tool allowed operators to modify the planned well trajectory in order to optimize placements within the reservoir. A rotary steerable system (RSS) was used increase injection times. The project was completed 6 to 8 weeks ahead of schedule. Applications have now been filed for a further 10 phases that will produce 240,000 barrels per day. 1 fig.

  1. Icariin combined with human umbilical cord mesenchymal stem cells significantly improve the impaired kidney function in chronic renal failure.

    Science.gov (United States)

    Li, Wen; Wang, Li; Chu, Xiaoqian; Cui, Huantian; Bian, Yuhong

    2017-04-01

    At present, the main therapy for chronic renal failure (CRF) is dialysis and renal transplantation, but neither obtains satisfactory results. Human umbilical cord mesenchymal stem cells (huMSCs) are isolated from the fetal umbilical cord which has a high self-renewal and multi-directional differentiation potential. Icariin (ICA), a kidney-tonifying Chinese Medicine can enhance the multipotency of huMSCs. Therefore, this work seeks to employ the use of ICA-treated huMSCs for the treatment of chronic renal failure. Blood urea nitrogen and creatinine (Cr) analyses showed amelioration of functional parameters in ICA-treated huMSCs for the treatment of CRF rats at 3, 7, and 14 days after transplantation. ICA-treated huMSCs can obviously increase the number of cells in injured renal tissues at 3, 7, and 14 days after transplantation by optical molecular imaging system. Hematoxylin-eosin staining demonstrated that ICA-treated huMSCs reduced the levels of fibrosis in CRF rats at 14 days after transplantation. Superoxide dismutase and Malondialdehyde analyses showed that ICA-treated huMSCs reduced the oxidative damage in CRF rats. Moreover, transplantation with ICA-treated huMSCs decreased inflammatory responses, promoted the expression of growth factors, and protected injured renal tissues. Taken together, our findings suggest that ICA-treated huMSCs could improve the kidney function in CRF rats.

  2. Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.

    Science.gov (United States)

    Li, Jing; Wang, Jing; Li, Jing

    2017-12-01

    As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .

  3. Improvement of Fabry Disease-Related Gastrointestinal Symptoms in a Significant Proportion of Female Patients Treated with Agalsidase Beta

    DEFF Research Database (Denmark)

    Wilcox, William R; Feldt-Rasmussen, Ulla; Martins, Ana Maria

    2018-01-01

    of organ involvement. Although variable, gastrointestinal symptoms are among the most common and significant early clinical manifestations; they tend to persist into adulthood if left untreated. To further understand the effects of sustained enzyme replacement therapy (ERT) with agalsidase beta......Fabry disease, an X-linked inherited lysosomal storage disorder, is caused by mutations in the gene encoding α-galactosidase, GLA. In patients with Fabry disease, glycosphingolipids accumulate in various cell types, triggering a range of cellular and tissue responses that result in a wide spectrum...... on gastrointestinal symptoms in heterozygotes, a data analysis of female patients enrolled in the Fabry Registry was conducted. To be included, females of any age must have received agalsidase beta (average dose 1.0 mg/kg every 2 weeks) for at least 2.5 years. Measured outcomes were self-reported gastrointestinal...

  4. Diagnostic value of thallium-201 myocardial perfusion IQ-SPECT without and with computed tomography-based attenuation correction to predict clinically significant and insignificant fractional flow reserve

    Science.gov (United States)

    Tanaka, Haruki; Takahashi, Teruyuki; Ohashi, Norihiko; Tanaka, Koichi; Okada, Takenori; Kihara, Yasuki

    2017-01-01

    Abstract The aim of this study was to clarify the predictive value of fractional flow reserve (FFR) determined by myocardial perfusion imaging (MPI) using thallium (Tl)-201 IQ-SPECT without and with computed tomography-based attenuation correction (CT-AC) for patients with stable coronary artery disease (CAD). We assessed 212 angiographically identified diseased vessels using adenosine-stress Tl-201 MPI-IQ-SPECT/CT in 84 consecutive, prospectively identified patients with stable CAD. We compared the FFR in 136 of the 212 diseased vessels using visual semiquantitative interpretations of corresponding territories on MPI-IQ-SPECT images without and with CT-AC. FFR inversely correlated most accurately with regional summed difference scores (rSDS) in images without and with CT-AC (r = −0.584 and r = −0.568, respectively, both P system can predict FFR at an optimal cut-off of <0.80, and we propose a novel application of CT-AC to MPI-IQ-SPECT for predicting clinically significant and insignificant FFR even in nonobese patients. PMID:29390486

  5. Pt-decorated GaN nanowires with significant improvement in H2 gas-sensing performance at room temperature.

    Science.gov (United States)

    Abdullah, Q N; Yam, F K; Hassan, Z; Bououdina, M

    2015-12-15

    Superior sensitivity towards H2 gas was successfully achieved with Pt-decorated GaN nanowires (NWs) gas sensor. GaN NWs were fabricated via chemical vapor deposition (CVD) route. Morphology (field emission scanning electron microscopy and transmission electron microscopy) and crystal structure (high resolution X-ray diffraction) characterizations of the as-synthesized nanostructures demonstrated the formation of GaN NWs having a wurtzite structure, zigzaged shape and an average diameter of 30-166nm. The Pt-decorated GaN NWs sensor shows a high response of 250-2650% upon exposure to H2 gas concentration from 7 to 1000ppm respectively at room temperature (RT), and then increases to about 650-4100% when increasing the operating temperature up to 75°C. The gas-sensing measurements indicated that the Pt-decorated GaN NWs based sensor exhibited efficient detection of H2 at low concentration with excellent sensitivity, repeatability, and free hysteresis phenomena over a period of time of 100min. The large surface-to-volume ratio of GaN NWs and the catalytic activity of Pt metal are the most influential factors leading to the enhancement of H2 gas-sensing performances through the improvement of the interaction between the target molecules (H2) and the sensing NWs surface. The attractive low-cost, low power consumption and high-performance of the resultant decorated GaN NWs gas sensor assure their uppermost potential for H2 gas sensor working at low operating temperature. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Noninvasive work of breathing improves prediction of post-extubation outcome.

    Science.gov (United States)

    Banner, Michael J; Euliano, Neil R; Martin, A Daniel; Al-Rawas, Nawar; Layon, A Joseph; Gabrielli, Andrea

    2012-02-01

    We hypothesized that non-invasively determined work of breathing per minute (WOB(N)/min) (esophageal balloon not required) may be useful for predicting extubation outcome, i.e., appropriate work of breathing values may be associated with extubation success, while inappropriately increased values may be associated with failure. Adult candidates for extubation were divided into a training set (n = 38) to determine threshold values of indices for assessing extubation and a prospective validation set (n = 59) to determine the predictive power of the threshold values for patients successfully extubated and those who failed extubation. All were evaluated for extubation during a spontaneous breathing trial (5 cmH(2)O pressure support ventilation, 5 cmH(2)O positive end expiratory pressure) using routine clinical practice standards. WOB(N)/min data were blinded to attending physicians. Area under the receiver operating characteristic curves (AUC), sensitivity, specificity, and positive and negative predictive values of all extubation indices were determined. AUC for WOB(N)/min was 0.96 and significantly greater (p indices. WOB(N)/min had a specificity of 0.83, the highest sensitivity at 0.96, positive predictive value at 0.84, and negative predictive value at 0.96 compared to all indices. For 95% of those successfully extubated, WOB(N)/min was ≤10 J/min. WOB(N)/min had the greatest overall predictive accuracy for extubation compared to traditional indices. WOB(N)/min warrants consideration for use in a complementary manner with spontaneous breathing pattern data for predicting extubation outcome.

  7. 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.

  8. Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

    Science.gov (United States)

    Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

    2018-02-19

    Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

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

    Science.gov (United States)

    Crawford, B. R.; Tsenn, M. C.; Homburg, J. M.; Stehle, R. C.; Freysteinso