An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Wang, Yunzhi; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

2016-03-01

In order to establish a new personalized breast cancer screening paradigm, it is critically important to accurately predict the short-term risk of a woman having image-detectable cancer after a negative mammographic screening. In this study, we developed and tested a novel short-term risk assessment model based on deep learning method. During the experiment, a number of 270 "prior" negative screening cases was assembled. In the next sequential ("current") screening mammography, 135 cases were positive and 135 cases remained negative. These cases were randomly divided into a training set with 200 cases and a testing set with 70 cases. A deep learning based computer-aided diagnosis (CAD) scheme was then developed for the risk assessment, which consists of two modules: adaptive feature identification module and risk prediction module. The adaptive feature identification module is composed of three pairs of convolution-max-pooling layers, which contains 20, 10, and 5 feature maps respectively. The risk prediction module is implemented by a multiple layer perception (MLP) classifier, which produces a risk score to predict the likelihood of the woman developing short-term mammography-detectable cancer. The result shows that the new CAD-based risk model yielded a positive predictive value of 69.2% and a negative predictive value of 74.2%, with a total prediction accuracy of 71.4%. This study demonstrated that applying a new deep learning technology may have significant potential to develop a new short-term risk predicting scheme with improved performance in detecting early abnormal symptom from the negative mammograms.

An exotic long-term pattern in stock price dynamics.

PubMed

Wei, Jianrong; Huang, Jiping

2012-01-01

To accurately predict the movement of stock prices is always of both academic importance and practical value. So far, a lot of research has been reported to help understand the behavior of stock prices. However, some of the existing theories tend to render us the belief that the time series of stock prices are unpredictable on a long-term timescale. The question arises whether the long-term predictability exists in stock price dynamics. In this work, we analyze the price reversals in the US stock market and the Chinese stock market on the basis of a renormalization method. The price reversals are divided into two types: retracements (the downward trends after upward trends) and rebounds (the upward trends after downward trends), of which the intensities are described by dimensionless quantities, R(t) and R(b), respectively. We reveal that for both mature and emerging markets, the distribution of either retracements R(t) or rebounds R(b) shows two characteristic values, 0.335 and 0.665, both of which are robust over the long term. The methodology presented here provides a way to quantify the stock price reversals. Our findings strongly support the existence of the long-term predictability in stock price dynamics, and may offer a hint on how to predict the long-term movement of stock prices.

The accuracy of new wheelchair users' predictions about their future wheelchair use.

PubMed

Hoenig, Helen; Griffiths, Patricia; Ganesh, Shanti; Caves, Kevin; Harris, Frances

2012-06-01

This study examined the accuracy of new wheelchair user predictions about their future wheelchair use. This was a prospective cohort study of 84 community-dwelling veterans provided a new manual wheelchair. The association between predicted and actual wheelchair use was strong at 3 mos (ϕ coefficient = 0.56), with 90% of those who anticipated using the wheelchair at 3 mos still using it (i.e., positive predictive value = 0.96) and 60% of those who anticipated not using it indeed no longer using the wheelchair (i.e., negative predictive value = 0.60, overall accuracy = 0.92). Predictive accuracy diminished over time, with overall accuracy declining from 0.92 at 3 mos to 0.66 at 6 mos. At all time points, and for all types of use, patients better predicted use as opposed to disuse, with correspondingly higher positive than negative predictive values. Accuracy of prediction of use in specific indoor and outdoor locations varied according to location. This study demonstrates the importance of better understanding the potential mismatch between the anticipated and actual patterns of wheelchair use. The findings suggest that users can be relied upon to accurately predict their basic wheelchair-related needs in the short-term. Further exploration is needed to identify characteristics that will aid users and their providers in more accurately predicting mobility needs for the long-term.

A Gaussian Processes Technique for Short-term Load Forecasting with Considerations of Uncertainty

NASA Astrophysics Data System (ADS)

Ohmi, Masataro; Mori, Hiroyuki

In this paper, an efficient method is proposed to deal with short-term load forecasting with the Gaussian Processes. Short-term load forecasting plays a key role to smooth power system operation such as economic load dispatching, unit commitment, etc. Recently, the deregulated and competitive power market increases the degree of uncertainty. As a result, it is more important to obtain better prediction results to save the cost. One of the most important aspects is that power system operator needs the upper and lower bounds of the predicted load to deal with the uncertainty while they require more accurate predicted values. The proposed method is based on the Bayes model in which output is expressed in a distribution rather than a point. To realize the model efficiently, this paper proposes the Gaussian Processes that consists of the Bayes linear model and kernel machine to obtain the distribution of the predicted value. The proposed method is successively applied to real data of daily maximum load forecasting.

Noninvasive Uterine Electromyography For Prediction of Preterm Delivery*

PubMed Central

UCOVNIK, Miha L; MANER, William L.; CHAMBLISS, Linda R.; BLUMRICK, Richard; BALDUCCI, James; NOVAK-ANTOLIC, Ziva; GARFIELD, Robert E.

2011-01-01

Objective Power spectrum (PS) of uterine electromyography (EMG) can identify true labor. EMG propagation velocity (PV) to diagnose labor has not been reported. The objective was to compare uterine EMG against current methods to predict preterm delivery. Study design EMG was recorded in 116 patients (preterm labor, n=20; preterm non-labor, n=68; term labor, n=22; term non-labor, n=6). Student’s t-test was used to compare EMG values for labor vs. non-labor (P<0.05 significant). Predictive values of EMG, Bishop-score, contractions on tocogram, and transvaginal cervical length were calculated using receiver-operator-characteristics analysis. Results PV was higher in preterm and term labor compared with non-labor (P<0.001). Combined PV and PS peak frequency predicted preterm delivery within 7 days with area-under-the-curve (AUC) = 0.96. Bishop score, contractions, and cervical length had AUC of 0.72, 0.67, and 0.54. Conclusions Uterine EMG PV and PS peak frequency more accurately identify true preterm labor than clinical methods. PMID:21145033

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

PubMed

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

Getting off on the right foot: subjective value versus economic value in predicting longitudinal job outcomes from job offer negotiations.

PubMed

Curhan, Jared R; Elfenbein, Hillary Anger; Kilduff, Gavin J

2009-03-01

Although negotiation experiences can affect a negotiator's ensuing attitudes and behavior, little is known about their long-term consequences. Using a longitudinal survey design, the authors tested the degree to which economic and subjective value achieved in job offer negotiations predicts employees' subsequent job attitudes and intentions concerning turnover. Results indicate that subjective value predicts greater compensation satisfaction and job satisfaction and lower turnover intention measured 1 year later. Surprisingly, the economic outcomes that negotiators achieved had no apparent effects on these factors. Implications, limitations, and future directions are discussed. (c) 2009 APA, all rights reserved.

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

PubMed

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

2013-01-01

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

Prediction of near-term breast cancer risk using a Bayesian belief network

NASA Astrophysics Data System (ADS)

Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

2013-03-01

Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.

A proteinuria cut-off level of 0.7 g/day after 12 months of treatment best predicts long-term renal outcome in lupus nephritis: data from the MAINTAIN Nephritis Trial

PubMed Central

Tamirou, Farah; Lauwerys, Bernard R; Dall'Era, Maria; Mackay, Meggan; Rovin, Brad; Cervera, Ricard; Houssiau, Frédéric A

2015-01-01

Background Although an early decrease in proteinuria has been correlated with good long-term renal outcome in lupus nephritis (LN), studies aimed at defining a cut-off proteinuria value are missing, except a recent analysis performed on patients randomised in the Euro-Lupus Nephritis Trial, demonstrating that a target value of 0.8 g/day at month 12 optimised sensitivity and specificity for the prediction of good renal outcome. The objective of the current work is to validate this target in another LN study, namely the MAINTAIN Nephritis Trial (MNT). Methods Long-term (at least 7 years) renal function data were available for 90 patients randomised in the MNT. Receiver operating characteristic curves were built to test the performance of proteinuria measured within the 1st year as short-term predictor of long-term renal outcome. We calculated the positive and negative predictive values (PPV, NPV). Results After 12 months of treatment, achievement of a proteinuria <0.7 g/day best predicted good renal outcome, with a sensitivity and a specificity of 71% and 75%, respectively. The PPV was high (94%) but the NPV low (29%). Addition of the requirement of urine red blood cells ≤5/hpf as response criteria at month 12 reduced sensitivity from 71% to 41%. Conclusions In this cohort of mainly Caucasian patients suffering from a first episode of LN in most cases, achievement of a proteinuria <0.7 g/day at month 12 best predicts good outcome at 7 years and inclusion of haematuria in the set of criteria at month 12 undermines the sensitivity of early proteinuria decrease for the prediction of good outcome. The robustness of these conclusions stems from the very similar results obtained in two distinct LN cohorts. Trial registration number: NCT00204022. PMID:26629352

Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China

NASA Astrophysics Data System (ADS)

Xu, Shiluo; Niu, Ruiqing

2018-02-01

Every year, landslides pose huge threats to thousands of people in China, especially those in the Three Gorges area. It is thus necessary to establish an early warning system to help prevent property damage and save peoples' lives. Most of the landslide displacement prediction models that have been proposed are static models. However, landslides are dynamic systems. In this paper, the total accumulative displacement of the Baijiabao landslide is divided into trend and periodic components using empirical mode decomposition. The trend component is predicted using an S-curve estimation, and the total periodic component is predicted using a long short-term memory neural network (LSTM). LSTM is a dynamic model that can remember historical information and apply it to the current output. Six triggering factors are chosen to predict the periodic term using the Pearson cross-correlation coefficient and mutual information. These factors include the cumulative precipitation during the previous month, the cumulative precipitation during a two-month period, the reservoir level during the current month, the change in the reservoir level during the previous month, the cumulative increment of the reservoir level during the current month, and the cumulative displacement during the previous month. When using one-step-ahead prediction, LSTM yields a root mean squared error (RMSE) value of 6.112 mm, while the support vector machine for regression (SVR) and the back-propagation neural network (BP) yield values of 10.686 mm and 8.237 mm, respectively. Meanwhile, the Elman network (Elman) yields an RMSE value of 6.579 mm. In addition, when using multi-step-ahead prediction, LSTM obtains an RMSE value of 8.648 mm, while SVR, BP and the Elman network obtains RSME values of 13.418 mm, 13.014 mm, and 13.370 mm. The predicted results indicate that, to some extent, the dynamic model (LSTM) achieves results that are more accurate than those of the static models (i.e., SVR and BP). LSTM even displays better performance than the Elman network, which is also a dynamic method.

Effects of historical and predictive information on ability of transport pilot to predict an alert

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.

1994-01-01

In the aviation community, the early detection of the development of a possible subsystem problem during a flight is potentially useful for increasing the safety of the flight. Commercial airlines are currently using twin-engine aircraft for extended transport operations over water, and the early detection of a possible problem might increase the flight crew's options for safely landing the aircraft. One method for decreasing the severity of a developing problem is to predict the behavior of the problem so that appropriate corrective actions can be taken. To investigate the pilots' ability to predict long-term events, a computer workstation experiment was conducted in which 18 airline pilots predicted the alert time (the time to an alert) using 3 different dial displays and 3 different parameter behavior complexity levels. The three dial displays were as follows: standard (resembling current aircraft round dial presentations); history (indicating the current value plus the value of the parameter 5 sec in the past); and predictive (indicating the current value plus the value of the parameter 5 sec into the future). The time profiles describing the behavior of the parameter consisted of constant rate-of-change profiles, decelerating profiles, and accelerating-then-decelerating profiles. Although the pilots indicated that they preferred the near term predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients

PubMed Central

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Background: Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. Materials and Methods: The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. Results: A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30–70% range, with no significant difference among models (P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others (P > 0.05). Conclusion: This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others. PMID:27904602

Usefulness of a 50-meter round walking test for fall prediction in the elderly requiring long-term care

PubMed Central

Hachiya, Mizuki; Murata, Shin; Otao, Hiroshi; Ihara, Takehiko; Mizota, Katsuhiko; Asami, Toyoko

2015-01-01

[Purpose] This study aimed to verify the usefulness of a 50-m round walking test developed as an assessment method for walking ability in the elderly. [Subjects] The subjects were 166 elderly requiring long-term care individuals (mean age, 80.5 years). [Methods] In order to evaluate the factors that had affected falls in the subjects in the previous year, we performed the 50-m round walking test, functional reach test, one-leg standing test, and 5-m walking test and measured grip strength and quadriceps strength. [Results] The 50-m round walking test was selected as a variable indicating fall risk based on the results of multiple logistic regression analysis. The cutoff value of the 50-m round walking test for determining fall risk was 0.66 m/sec. The area under the receiver operating characteristic curve was 0.64. The sensitivity of the cutoff value was 65.7%, the specificity was 63.6%, the positive predictive value was 55.0%, the negative predictive value was 73.3%, and the accuracy was 64.5%. [Conclusion] These results suggest that the 50-m round walking test is a potentially useful parameter for the determination of fall risk in the elderly requiring long-term care. PMID:26834327

Usefulness of a 50-meter round walking test for fall prediction in the elderly requiring long-term care.

PubMed

Hachiya, Mizuki; Murata, Shin; Otao, Hiroshi; Ihara, Takehiko; Mizota, Katsuhiko; Asami, Toyoko

2015-12-01

[Purpose] This study aimed to verify the usefulness of a 50-m round walking test developed as an assessment method for walking ability in the elderly. [Subjects] The subjects were 166 elderly requiring long-term care individuals (mean age, 80.5 years). [Methods] In order to evaluate the factors that had affected falls in the subjects in the previous year, we performed the 50-m round walking test, functional reach test, one-leg standing test, and 5-m walking test and measured grip strength and quadriceps strength. [Results] The 50-m round walking test was selected as a variable indicating fall risk based on the results of multiple logistic regression analysis. The cutoff value of the 50-m round walking test for determining fall risk was 0.66 m/sec. The area under the receiver operating characteristic curve was 0.64. The sensitivity of the cutoff value was 65.7%, the specificity was 63.6%, the positive predictive value was 55.0%, the negative predictive value was 73.3%, and the accuracy was 64.5%. [Conclusion] These results suggest that the 50-m round walking test is a potentially useful parameter for the determination of fall risk in the elderly requiring long-term care.

Positive predictive value of infective endocarditis in the Danish National Patient Registry: a validation study.

PubMed

Østergaard, Lauge; Adelborg, Kasper; Sundbøll, Jens; Pedersen, Lars; Loldrup Fosbøl, Emil; Schmidt, Morten

2018-05-30

The positive predictive value of an infective endocarditis diagnosis is approximately 80% in the Danish National Patient Registry. However, since infective endocarditis is a heterogeneous disease implying long-term intravenous treatment, we hypothesiszed that the positive predictive value varies by length of hospital stay. A total of 100 patients with first-time infective endocarditis in the Danish National Patient Registry were identified from January 2010 - December 2012 at the University hospital of Aarhus and regional hospitals of Herning and Randers. Medical records were reviewed. We calculated the positive predictive value according to admission length, and separately for patients with a cardiac implantable electronic device and a prosthetic heart valve using the Wilson score method. Among the 92 medical records available for review, the majority of the patients had admission length ⩾2 weeks. The positive predictive value increased with length of admission. In patients with admission length <2 weeks the positive predictive value was 65% while it was 90% for admission length ⩾2 weeks. The positive predictive value was 81% for patients with a cardiac implantable electronic device and 87% for patients with a prosthetic valve. The positive predictive value of the infective endocarditis diagnosis in the Danish National Patient Registry is high for patients with admission length ⩾2 weeks. Using this algorithm, the Danish National Patient Registry provides a valid source for identifying infective endocarditis for research.

Predictive Validity of a Cigarette Purchase Task in a Randomized Controlled Trial of Contingent Vouchers for Smoking in Individuals With Substance Use Disorders

PubMed Central

Mackillop, James; Murphy, Cara M.; Martin, Rosemarie A.; Stojek, Monika; Tidey, Jennifer W.; Colby, Suzanne M.

2016-01-01

Abstract Introduction: A cigarette purchase task (CPT) is a behavioral economic measure of the reinforcing value of smoking in monetary terms (ie, cigarette demand). This study investigated whether cigarette demand predicted response to contingent monetary rewards for abstinence among individuals with substance use disorders. It also sought to replicate evidence for greater price sensitivity at whole-dollar pack price transitions (ie, left-digit effects). Methods: Participants ( N = 338) were individuals in residential substance use disorder treatment who participated in a randomized controlled trial that compared contingent vouchers to noncontingent vouchers for smoking abstinence. Baseline demand indices were used to predict number of abstinent days during the 14-day voucher period (after the reduction lead-in) and at 1 and 3 months afterward. Results: Demand indices correlated with measures of smoking and nicotine dependence. As measured by elasticity, intensity and Omax , higher demand significantly predicted fewer abstinent exhaled carbon monoxide readings during voucher period for individuals in the noncontingent vouchers condition. Breakpoint exhibited a trend-level association with abstinent exhaled carbon monoxide readings. Demand indices did not predict abstinence in the contingent vouchers group, and did not predict abstinence at 1- and 3-month follow-ups. Left-digit price transitions were associated with significantly greater reductions in consumption. Conclusions: The association of cigarette demand with smoking behavior only in the group for whom abstinence was not incentivized indicates that CPT assesses the value of smoking more than the value of money per se and that vouchers counteract the effects of the intrinsic reinforcing value of cigarettes. Results provide initial short-term evidence of predictive validity for the CPT indices. Implications: This study provides the first evidence of the validity of the CPT for predicting early response to brief advice for smoking cessation plus nicotine replacement in smokers with substance dependence. However, demand for cigarettes did not predict voucher-based treatment response, indicating that incentives serve as a powerful motivator not to smoke that acts in opposition to the intrinsic reinforcing value of cigarettes and that the indices reflect the value of smoking more than the value of money per se. PMID:26498173

Predictive value of early changes in triglycerides and weight for longer-term changes in metabolic measures during olanzapine, ziprasidone or aripiprazole treatment for schizophrenia and schizoaffective disorder post hoc analyses of 3 randomized, controlled clinical trials.

PubMed

Hoffmann, Vicki P; Case, Michael; Stauffer, Virginia L; Jacobson, Jennie G; Conley, Robert R

2010-12-01

The objective of this study was to determine if early changes in triglycerides and weight may be useful in predicting longer-term changes in weight and other metabolic parameters. Data were from three 24- to 28-week randomized, controlled studies comparing olanzapine to ziprasidone or aripiprazole for treatment of schizophrenia. Analyses were restricted to completers with fasting laboratory data at all protocol specified time points. Analyses were primarily descriptive and included mean changes and categorical outcomes. In all treatment groups, participants who did not experience a 20 mg/dL or greater increase in triglycerides at early time points were unlikely to experience a change of 50 mg/dL or more in triglycerides after 6 months. Negative predictive values were 83% to 95%. However, early change in triglycerides was not useful for predicting later change in glucose, cholesterol, or weight. Similarly, early weight change gave robust negative predictive values for longer-term weight change (≥10 kg), but not for change in glucose or cholesterol. Lack of early elevation in triglyceride concentrations was predictive of later lack of substantial increase in triglycerides in olanzapine-, ziprasidone-, and aripiprazole-treated participants. Lack of early elevation in weight was predictive of later lack of substantial increase in weight in all 3 treatment groups. Early monitoring of triglyceride concentrations and weight may help clinicians assess risk that individuals will experience significant increase in triglycerides or weight gain, allowing assessments of potential risks and benefits earlier in treatment. Clinical monitoring is advised throughout treatment for all patients.

A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework

NASA Astrophysics Data System (ADS)

Liang, Zhongmin; Li, Yujie; Hu, Yiming; Li, Binquan; Wang, Jun

2017-06-01

Accurate and reliable long-term forecasting plays an important role in water resources management and utilization. In this paper, a hybrid model called SVR-HUP is presented to predict long-term runoff and quantify the prediction uncertainty. The model is created based on three steps. First, appropriate predictors are selected according to the correlations between meteorological factors and runoff. Second, a support vector regression (SVR) model is structured and optimized based on the LibSVM toolbox and a genetic algorithm. Finally, using forecasted and observed runoff, a hydrologic uncertainty processor (HUP) based on a Bayesian framework is used to estimate the posterior probability distribution of the simulated values, and the associated uncertainty of prediction was quantitatively analyzed. Six precision evaluation indexes, including the correlation coefficient (CC), relative root mean square error (RRMSE), relative error (RE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE), and qualification rate (QR), are used to measure the prediction accuracy. As a case study, the proposed approach is applied in the Han River basin, South Central China. Three types of SVR models are established to forecast the monthly, flood season and annual runoff volumes. The results indicate that SVR yields satisfactory accuracy and reliability at all three scales. In addition, the results suggest that the HUP cannot only quantify the uncertainty of prediction based on a confidence interval but also provide a more accurate single value prediction than the initial SVR forecasting result. Thus, the SVR-HUP model provides an alternative method for long-term runoff forecasting.

Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

PubMed

Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

2017-07-15

The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p < 0.0001). The alternative predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

Research on dynamic creep strain and settlement prediction under the subway vibration loading.

PubMed

Luo, Junhui; Miao, Linchang

2016-01-01

This research aims to explore the dynamic characteristics and settlement prediction of soft soil. Accordingly, the dynamic shear modulus formula considering the vibration frequency was utilized and the dynamic triaxial test conducted to verify the validity of the formula. Subsequently, the formula was applied to the dynamic creep strain function, with the factors influencing the improved dynamic creep strain curve of soft soil being analyzed. Meanwhile, the variation law of dynamic stress with sampling depth was obtained through the finite element simulation of subway foundation. Furthermore, the improved dynamic creep strain curve of soil layer was determined based on the dynamic stress. Thereafter, it could to estimate the long-term settlement under subway vibration loading by norms. The results revealed that the dynamic shear modulus formula is straightforward and practical in terms of its application to the vibration frequency. The values predicted using the improved dynamic creep strain formula closed to the experimental values, whilst the estimating settlement closed to the measured values obtained in the field test.

Technical Note: On the calculation of stopping-power ratio for stoichiometric calibration in proton therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ödén, Jakob; Zimmerman, Jens; Nowik, Patrik

2015-09-15

Purpose: The quantitative effects of assumptions made in the calculation of stopping-power ratios (SPRs) are investigated, for stoichiometric CT calibration in proton therapy. The assumptions investigated include the use of the Bethe formula without correction terms, Bragg additivity, the choice of I-value for water, and the data source for elemental I-values. Methods: The predictions of the Bethe formula for SPR (no correction terms) were validated against more sophisticated calculations using the SRIM software package for 72 human tissues. A stoichiometric calibration was then performed at our hospital. SPR was calculated for the human tissues using either the assumption of simplemore » Bragg additivity or the Seltzer-Berger rule (as used in ICRU Reports 37 and 49). In each case, the calculation was performed twice: First, by assuming the I-value of water was an experimentally based value of 78 eV (value proposed in Errata and Addenda for ICRU Report 73) and second, by recalculating the I-value theoretically. The discrepancy between predictions using ICRU elemental I-values and the commonly used tables of Janni was also investigated. Results: Errors due to neglecting the correction terms to the Bethe formula were calculated at less than 0.1% for biological tissues. Discrepancies greater than 1%, however, were estimated due to departures from simple Bragg additivity when a fixed I-value for water was imposed. When the I-value for water was calculated in a consistent manner to that for tissue, this disagreement was substantially reduced. The difference between SPR predictions when using Janni’s or ICRU tables for I-values was up to 1.6%. Experimental data used for materials of relevance to proton therapy suggest that the ICRU-derived values provide somewhat more accurate results (root-mean-square-error: 0.8% versus 1.6%). Conclusions: The conclusions from this study are that (1) the Bethe formula can be safely used for SPR calculations without correction terms; (2) simple Bragg additivity can be reasonably assumed for compound materials; (3) if simple Bragg additivity is assumed, then the I-value for water should be calculated in a consistent manner to that of the tissue of interest (rather than using an experimentally derived value); (4) the ICRU Report 37 I-values may provide a better agreement with experiment than Janni’s tables.« less

The role of HATCH score in predicting the success rate of sinus rhythm following electrical cardioversion of atrial fibrillation.

PubMed

Emren, Sadık Volkan; Kocabaş, Uğur; Duygu, Hamza; Levent, Fatih; Şimşek, Ersin Çağrı; Yapan Emren, Zeynep; Tülüce, Selcen

2016-01-01

The HATCH score predicts the development of persistent and permanent atrial fibrillation (AF) one year after spontaneous or pharmacological conversion to sinus rhythm in patients with AF. However, it remains unknown whether HATCH score predicts short-term success of the procedure at early stages for patients who have undergone electrical cardioversion (EC) for AF. The present study evaluated whether HATCH score predicts short-term success of EC in patients with AF. The study included patients aged 18 years and over, who had undergone EC due to AF lasting less than 12 months, between December 2011 and October 2013. HATCH score was calculated for all patients. The acronym HATCH stands for Hypertension, Age (above 75 years), Transient ischaemic attack or stroke, Chronic obstructive pulmonary disease, and Heart failure. This scoring system awards two points for heart failure and transient ischaemic attack or stroke and one point for the remaining items. The study included 227 patients and short-term EC was successful in 163 of the cases. The mean HATCH scores of the patients who had undergone successful or unsuccessful EC were 1.3 ± 1.4 and 2.9 ± 1.4, respectively (p < 0.001). The area of the HATCH score under the curve in receiver operating characteristics analysis was (AUC) 0.792 (95% CI 0.727-0.857, p < 0.001). A HATCH score of two and above yielded 77% sensitivity, 62% specificity, 56% positive predictive value, and 87% negative predictive value in predicting unsuccessful cardioversion. HATCH score is useful in predicting short-term success of EC at early stages for patients with AF, for whom the use of a rhythm-control strategy is planned.

Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study

NASA Technical Reports Server (NTRS)

Johannsen, G.; Govindaraj, T.

1980-01-01

The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.

Predictive Value of the Sequential Organ Failure Assessment Score for Mortality in a Contemporary Cardiac Intensive Care Unit Population.

PubMed

Jentzer, Jacob C; Bennett, Courtney; Wiley, Brandon M; Murphree, Dennis H; Keegan, Mark T; Gajic, Ognjen; Wright, R Scott; Barsness, Gregory W

2018-03-10

Optimal methods of mortality risk stratification in patients in the cardiac intensive care unit (CICU) remain uncertain. We evaluated the ability of the Sequential Organ Failure Assessment (SOFA) score to predict mortality in a large cohort of unselected patients in the CICU. Adult patients admitted to the CICU from January 1, 2007, to December 31, 2015, at a single tertiary care hospital were retrospectively reviewed. SOFA scores were calculated daily, and Acute Physiology and Chronic Health Evaluation (APACHE)-III and APACHE-IV scores were calculated on CICU day 1. Discrimination of hospital mortality was assessed using area under the receiver-operator characteristic curve values. We included 9961 patients, with a mean age of 67.5±15.2 years; all-cause hospital mortality was 9.0%. Day 1 SOFA score predicted hospital mortality, with an area under the receiver-operator characteristic curve value of 0.83; area under the receiver-operator characteristic curve values were similar for the APACHE-III score, and APACHE-IV predicted mortality ( P >0.05). Mean and maximum SOFA scores over multiple CICU days had greater discrimination for hospital mortality ( P <0.01). Patients with an increasing SOFA score from day 1 and day 2 had higher mortality. Patients with day 1 SOFA score <2 were at low risk of mortality. Increasing tertiles of day 1 SOFA score predicted higher long-term mortality ( P <0.001 by log-rank test). The day 1 SOFA score has good discrimination for short-term mortality in unselected patients in the CICU, which is comparable to APACHE-III and APACHE-IV. Advantages of the SOFA score over APACHE include simplicity, improved discrimination using serial scores, and prediction of long-term mortality. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

NASA Astrophysics Data System (ADS)

Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

2018-04-01

In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

Prediction of long-term disability in multiple sclerosis.

PubMed

Schlaeger, R; D'Souza, M; Schindler, C; Grize, L; Dellas, S; Radue, E W; Kappos, L; Fuhr, P

2012-01-01

Little is known about the predictive value of neurophysiological measures for the long-term course of multiple sclerosis (MS). To prospectively investigate whether combined visual (VEP) and motor evoked potentials (MEP) allow prediction of disability over 14 years. A total of 30 patients with relapsing-remitting and secondary progressive MS were prospectively investigated with VEPs, MEPs and the Expanded Disability Status Scale (EDSS) at entry (T0) and after 6, 12 and 24 months, and with cranial MRI scans at entry (T2-weighted and gadolinium-enhanced T1-weighted images). EDSS was again assessed at year 14 (T4). The association between evoked potential (EP), magnetic resonance (MR) data and EDSS was measured using Spearman's rank correlation. Multivariable linear regression was performed to predict EDSS(T4) as a function of z-transformed EP-latencies(T0). The model was validated using a jack-knife procedure and the potential for improving it by inclusion of additional baseline variables was examined. EDSS values(T4) correlated with the sum of z-transformed EP-latencies(T0) (rho = 0.68, p < 0.0001), but not with MR-parameters(T0). EDSS(T4) as predicted by the formula EDSS(T4) = 4.194 + 0.088 * z-score P100(T0) + 0.071 * z-score CMCT(UE, T0) correlated with the observed values (rho = 0.69, p < 0.0001). Combined EPs allow prediction of long-term disability in small groups of patients with MS. This may have implications for the choice of monitoring methods in clinical trials and for daily practice decisions.

Longer-Term Investigation of the Value of 18F-FDG-PET and Magnetic Resonance Imaging for Predicting the Conversion of Mild Cognitive Impairment to Alzheimer's Disease: A Multicenter Study.

PubMed

Inui, Yoshitaka; Ito, Kengo; Kato, Takashi

2017-01-01

The value of fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) and magnetic resonance imaging (MRI) for predicting conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD) in longer-term is unclear. To evaluate longer-term prediction of MCI to AD conversion using 18F-FDG-PET and MRI in a multicenter study. One-hundred and fourteen patients with MCI were followed for 5 years. They underwent clinical and neuropsychological examinations, 18F-FDG-PET, and MRI at baseline. PET images were visually classified into predefined dementia patterns. PET scores were calculated as a semi quantitative index. For structural MRI, z-scores in medial temporal area were calculated by automated volume-based morphometry (VBM). Overall, 72% patients with amnestic MCI progressed to AD during the 5-year follow-up. The diagnostic accuracy of PET scores over 5 years was 60% with 53% sensitivity and 84% specificity. Visual interpretation of PET images predicted conversion to AD with an overall 82% diagnostic accuracy, 94% sensitivity, and 53% specificity. The accuracy of VBM analysis presented little fluctuation through 5 years and it was highest (73%) at the 5-year follow-up, with 79% sensitivity and 63% specificity. The best performance (87.9% diagnostic accuracy, 89.8% sensitivity, and 82.4% specificity) was with a combination identified using multivariate logistic regression analysis that included PET visual interpretation, educational level, and neuropsychological tests as predictors. 18F-FDG-PET visual assessment showed high performance for predicting conversion to AD from MCI, particularly in combination with neuropsychological tests. PET scores showed high diagnostic specificity. Structural MRI focused on the medial temporal area showed stable predictive value throughout the 5-year course.

Diagnostic Performance 1 H after Simulation Training Predicts Learning

ERIC Educational Resources Information Center

Consoli, Anna; Fraser, Kristin; Ma, Irene; Sobczak, Matthew; Wright, Bruce; McLaughlin, Kevin

2013-01-01

Although simulation training improves post-training performance, it is unclear how well performance soon after simulation training predicts longer term outcomes (i.e., learning). Here our objective was to assess the predictive value of performance 1 h post-training of performance 6 weeks later. We trained 84 first year medical students a simulated…

Assessment of PDF Micromixing Models Using DNS Data for a Two-Step Reaction

NASA Astrophysics Data System (ADS)

Tsai, Kuochen; Chakrabarti, Mitali; Fox, Rodney O.; Hill, James C.

1996-11-01

Although the probability density function (PDF) method is known to treat the chemical reaction terms exactly, its application to turbulent reacting flows have been overshadowed by the ability to model the molecular mixing terms satisfactorily. In this study, two PDF molecular mixing models, the linear-mean-square-estimation (LMSE or IEM) model and the generalized interaction-by-exchange-with-the-mean (GIEM) model, are compared with the DNS data in decaying turbulence with a two-step parallel-consecutive reaction and two segregated initial conditions: ``slabs" and ``blobs". Since the molecular mixing model is expected to have a strong effect on the mean values of chemical species under such initial conditions, the model evaluation is intended to answer the following questions: Can the PDF models predict the mean values of chemical species correctly with completely segregated initial conditions? (2) Is a single molecular mixing timescale sufficient for the PDF models to predict the mean values with different initial conditions? (3) Will the chemical reactions change the molecular mixing timescales of the reacting species enough to affect the accuracy of the model's prediction for the mean values of chemical species?

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

FEV1/FVC and FEV1 for the assessment of chronic airflow obstruction in prevalence studies: do prediction equations need revision?

PubMed

Roche, Nicolas; Dalmay, François; Perez, Thierry; Kuntz, Claude; Vergnenègre, Alain; Neukirch, Françoise; Giordanella, Jean-Pierre; Huchon, Gérard

2008-11-01

Little is known on the long-term validity of reference equations used in the calculation of FEV(1) and FEV(1)/FVC predicted values. This survey assessed the prevalence of chronic airflow obstruction in a population-based sample and how it is influenced by: (i) the definition of airflow obstruction; and (ii) equations used to calculate predicted values. Subjects aged 45 or more were recruited in health prevention centers, performed spirometry and fulfilled a standardized ECRHS-derived questionnaire. Previously diagnosed cases and risk factors were identified. Prevalence of airflow obstruction was calculated using: (i) ATS-GOLD definition (FEV(1)/FVC<0.70); and (ii) ERS definition (FEV(1)/FVC

Assessment of the Effects of Entrainment and Wind Shear on Nuclear Cloud Rise Modeling

NASA Astrophysics Data System (ADS)

Zalewski, Daniel; Jodoin, Vincent

2001-04-01

Accurate modeling of nuclear cloud rise is critical in hazard prediction following a nuclear detonation. This thesis recommends improvements to the model currently used by DOD. It considers a single-term versus a three-term entrainment equation, the value of the entrainment and eddy viscous drag parameters, as well as the effect of wind shear in the cloud rise following a nuclear detonation. It examines departures from the 1979 version of the Department of Defense Land Fallout Interpretive Code (DELFIC) with the current code used in the Hazard Prediction and Assessment Capability (HPAC) code version 3.2. The recommendation for a single-term entrainment equation, with constant value parameters, without wind shear corrections, and without cloud oscillations is based on both a statistical analysis using 67 U.S. nuclear atmospheric test shots and the physical representation of the modeling. The statistical analysis optimized the parameter values of interest for four cases: the three-term entrainment equation with wind shear and without wind shear as well as the single-term entrainment equation with and without wind shear. The thesis then examines the effect of cloud oscillations as a significant departure in the code. Modifications to user input atmospheric tables are identified as a potential problem in the calculation of stabilized cloud dimensions in HPAC.

Dynamic value assessments in oncology supported by the PACE Continuous Innovation Indicators.

PubMed

Paddock, Silvia; Goodman, Clifford; Shortenhaus, Scott; Grainger, David; Zummo, Jacqueline; Thomas, Samuel

2017-10-01

Several recently developed frameworks aim to assess the value of cancer treatments, but the most appropriate metrics remain uncertain. We use data from the Patient Access to Cancer care Excellence Continuous Innovation Indicators to examine the relationship between hazard ratios (HRs) from clinical trials and dynamic therapeutic value accumulating over time. Our analysis shows that HRs from initial clinical trials poorly predict the eventual therapeutic value of cancer treatments. Relying strongly on HRs from registration trials to predict the long-term success of treatments leaves a lot of the variance unexplained. The Continuous Innovation Indicators offer a complementing, dynamic method to track the therapeutic value of cancer treatments and continuously update value assessments as additional evidence accumulates.

Predictive and prognostic value of PET/CT imaging post-chemoradiotherapy and clinical decision-making consequences in locally advanced head & neck squamous cell carcinoma: a retrospective study.

PubMed

Kim, Ryul; Ock, Chan-Young; Keam, Bhumsuk; Kim, Tae Min; Kim, Jin Ho; Paeng, Jin Chul; Kwon, Seong Keun; Hah, J Hun; Kwon, Tack-Kyun; Kim, Dong-Wan; Wu, Hong-Gyun; Sung, Myung-Whun; Heo, Dae Seog

2016-02-17

The accuracy of (18)F-fluorodeoxygluocose positron emission tomography/computed tomography (PET/CT) in predicting immediate failure after radical chemoradiotherapy (CRT) for HNSCC is poorly characterized at present. The purpose of this study was to examine PET/CT as a predictive and prognostic gauge of immediate failure after CRT and determine the impact of these studies on clinical decision making in terms of salvage surgery. Medical records of 78 consecutive patients receiving radical CRT for locally advanced HNSCC were reviewed, analyzing PET/CTs done before and 3 months after CRT. Immediate failure was defined as residual disease or locoregional and/or systemic relapse within 6 months after CRT. Maximum standard uptake value (SUV) of post CRT PET/CT (postSUVmax) was found optimal for predicting immediate failure at a cutpoint of 4.4. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were 90.0%, 83.8%, 98.3%, and 45.0%, respectively. Of 78 patients studied, postSUVmax ≥ 4.4 prevailed in 20 (25.6%), with postSUVmax <4.4 in 58 (74.4%). At postSUVmax ≥ 4.4 (vs. postSUVmax <4.4) OS was poorer by comparison (3-year OS: 56.9 vs. 87.7%; P = 0.005), as was progression-free survival (3-year PFS: 42.9 vs. 81.1%; P < 0.001). At postSUVmax ≥ 4.4, OS with and without immediate salvage surgery did not differ significantly (3-year OS: 60.0 vs. 55.6%; Log-rank P = 0.913). Post CRT PET/CT imaging has prognostic value in terms of OS and PFS and is useful in predicting immediate therapeutic failure, given its high NPV. However, OS was not significantly altered by early salvage surgery done on the basis of post CRT PET/CT findings.

A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and Kappa

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen

2008-01-01

Modelling techniques used in binary classification problems often result in a predicted probability surface, which is then translated into a presence - absence classification map. However, this translation requires a (possibly subjective) choice of threshold above which the variable of interest is predicted to be present. The selection of this threshold value can have...

The Relationship between Adolescents' Levels of Hopelessness and Cyberbullying: The Role of Values

ERIC Educational Resources Information Center

Dilmaç, Bülent

2017-01-01

The purpose of this research is to present the relationship of teenagers' values with their levels of cyberbullying and hopelessness, as well as to test the created model in terms of these relations. This research analyzes the predictive relationships among adolescents' values, cyberbullying, and hopelessness through the program AMOS 19 in…

Personal values, subjective well-being and destination-loyalty intention of international students.

PubMed

Jamaludin, N L; Sam, D L; Sandal, G M; Adam, A A

2016-01-01

What are the factors that predict international students' destination-loyalty intention? This is the main question this paper addresses, using an online survey among 396 (short-term, N = 182) and (long-term, N = 214) international students at a Norwegian university. Structural equation model-AMOS was conducted to examine relationships among personal values, subjective well-being and destination-loyalty intentions. The results showed that: (1) universalism was positively related to subjective well-being for short-term students; and (2) subjective well-being was positively related to destination-loyalty intention for all groups. We found that relatively stable and happy individuals might be important for ensuring destination-loyalty intentions. Results also indicated that personal values that emphasize justice and equity are also important for short-term international students' well-being.

Long-Term Post-CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions.

PubMed

Carr, Brendan M; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C; Zhu, Wei; Shroyer, A Laurie

2016-01-01

Clinical risk models are commonly used to predict short-term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long-term mortality. The added value of long-term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long-term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Long-term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c-index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Mortality rates were 3%, 9%, and 17% at one-, three-, and five years, respectively (median follow-up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long-term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Long-term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long-term mortality risk can be accurately assessed and subgroups of higher-risk patients can be identified for enhanced follow-up care. More research appears warranted to refine long-term CABG clinical risk models. © 2015 The Authors. Journal of Cardiac Surgery Published by Wiley Periodicals, Inc.

Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

PubMed Central

Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

2015-01-01

Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

The comparison of umbilical cord arterial blood lactate and pH values for predicting short-term neonatal outcomes.

PubMed

Einikyte, Ruta; Snieckuviene, Vilija; Ramasauskaite, Diana; Panaviene, Jurate; Paliulyte, Virginija; Opolskiene, Gina; Kazenaite, Edita

2017-12-01

Current clinical practice of assessing neonatal condition is based on evaluation of umbilical cord arterial blood pH value rather than lactate. However, evidence shows that lactate is direct and more predictive measurement than pH or at least of equal importance. This study is to assess and compare umbilical cord arterial lactate and pH values for predicting short-term neonatal outcomes. A retrospective cohort study was conducted at the tertiary level hospital, were arterial umbilical cord blood sampling was collected according to the standard procedures. Neonatal morbidity was registered if at least one of the following conditions was noted: Apgar score at 1 min after delivery was 6 or lower, resuscitation performed, including assisted ventilation and requirement of admission to neonatal intensive care unit. Mothers-newborns pairs were allocated into two groups: newborns exposed to perinatal hypoxia (group 1) and observed as healthy newborns (group 2). Receiver operating characteristics curves (ROC) were generated to assess the predictive ability of pH and lactate for the short-term neonatal outcomes. 901 neonates born at ≥37 weeks of gestation were included. Newborns exposed to perinatal hypoxia (group 1) encompassed 39 (4.3%) patients, and observed as healthy (group 2) - 862 (95.7%). Arterial umbilical cord blood pH in group 1 was 7.160 ± 0.126 as compared to 7.314 ± 0.083 in group 2; p < 0.001. Mean arterial lactate was significantly higher in group 1 than group 2 (6.423 ± 2.335 as compared to 3.600 ± 1.833; p < 0.001). The difference between areas under ROC curves representing pH and lactate was not significant (0.848 and 0.831 respectively; p = 0.6132). Umbilical cord arterial lactate and pH predicted short-term neonatal outcomes with similar efficacies. Copyright © 2017. Published by Elsevier B.V.

The effect of individual differences and manipulated life expectancies on the willingness to engage in sexual coercion.

PubMed

Dunkel, Curtis S; Mathes, Eugene

2011-12-16

The role of the individual difference variables of mate value, short-term and long-term mating preferences, and life history strategy along with the manipulated variable of life expectancy were used to predict differences in the willingness to engage in sexually coercive behaviors. Short-term preferences and long-term preferences were correlated with the willingness to engage in sexual coercion at all life expectancies. Life history strategy was correlated with the willingness to engage in sexual coercion at only the shortest and longest life expectancies. Most importantly short-term and long-term mating preferences interacted with life expectancy to predict the willingness to engage in sexually coercive behaviors. Short life expectancies increased willingness in individuals with high short-term and low long-term preferences. The results are discussed in terms of the varying theories of sexual coercion with emphasis put on a life history approach.

Higgs and superparticle mass predictions from the landscape

NASA Astrophysics Data System (ADS)

Baer, Howard; Barger, Vernon; Serce, Hasan; Sinha, Kuver

2018-03-01

Predictions for the scale of SUSY breaking from the string landscape go back at least a decade to the work of Denef and Douglas on the statistics of flux vacua. The assumption that an assortment of SUSY breaking F and D terms are present in the hidden sector, and their values are uniformly distributed in the landscape of D = 4, N = 1 effective supergravity models, leads to the expectation that the landscape pulls towards large values of soft terms favored by a power law behavior P( m soft) ˜ m soft n . On the other hand, similar to Weinberg's prediction of the cosmological constant, one can assume an anthropic selection of weak scales not too far from the measured value characterized by m W,Z,h ˜ 100 GeV. Working within a fertile patch of gravity-mediated low energy effective theories where the superpotential μ term is ≪ m 3/2, as occurs in models such as radiative breaking of Peccei-Quinn symmetry, this biases statistical distributions on the landscape by a cutoff on the parameter ΔEW, which measures fine-tuning in the m Z - μ mass relation. The combined effect of statistical and anthropic pulls turns out to favor low energy phenomenology that is more or less agnostic to UV physics. While a uniform selection n = 0 of soft terms produces too low a value for m h , taking n = 1 and 2 produce most probabilistically m h ˜ 125 GeV for negative trilinear terms. For n ≥ 1, there is a pull towards split generations with {m}_{\\tilde{q},\\tilde{ℓ}}(1,2)˜ 10-30 TeV whilst {m}_{{\\tilde{t}}_1}˜ 1-2 TeV . The most probable gluino mass comes in at ˜ 3 - 4 TeV — apparently beyond the reach of HL-LHC (although the required quasi-degenerate higgsinos should still be within reach). We comment on consequences for SUSY collider and dark matter searches.

Validity of pre and post-term birth rates based on the date of last menstrual period compared to early obstetric ultrasonography.

PubMed

Medeiros, Maria Nilza Lima; Cavalcante, Nádia Carenina Nunes; Mesquita, Fabrício José Alencar; Batista, Rosângela Lucena Fernandes; Simões, Vanda Maria Ferreira; Cavalli, Ricardo de Carvalho; Cardoso, Viviane Cunha; Bettiol, Heloisa; Barbieri, Marco Antonio; Silva, Antônio Augusto Moura da

2015-04-01

The aim of this study was to assess the validity of the last menstrual period (LMP) estimate in determining pre and post-term birth rates, in a prenatal cohort from two Brazilian cities, São Luís and Ribeirão Preto. Pregnant women with a single fetus and less than 20 weeks' gestation by obstetric ultrasonography who received prenatal care in 2010 and 2011 were included. The LMP was obtained on two occasions (at 22-25 weeks gestation and after birth). The sensitivity of LMP obtained prenatally to estimate the preterm birth rate was 65.6% in São Luís and 78.7% in Ribeirão Preto and the positive predictive value was 57.3% in São Luís and 73.3% in Ribeirão Preto. LMP errors in identifying preterm birth were lower in the more developed city, Ribeirão Preto. The sensitivity and positive predictive value of LMP for the estimate of the post-term birth rate was very low and tended to overestimate it. LMP can be used with some errors to identify the preterm birth rate when obstetric ultrasonography is not available, but is not suitable for predicting post-term birth.

Predictive Utility of Personality Disorder in Depression: Comparison of Outcomes and Taxonomic Approach.

PubMed

Newton-Howes, Giles; Mulder, Roger; Ellis, Pete M; Boden, Joseph M; Joyce, Peter

2017-09-19

There is debate around the best model for diagnosing personality disorder, both in terms of its relationship to the empirical data and clinical utility. Four randomized controlled trials examining various treatments for depression were analyzed at an individual patient level. Three different approaches to the diagnosis of personality disorder were analyzed in these patients. A total of 578 depressed patients were included in the analysis. Personality disorder, however measured, was of little predictive utility in the short term but added significantly to predictive modelling of medium-term outcomes, accounting for more than twice as much of the variance in social functioning outcome as depression psychopathology. Personality disorder assessment is of predictive utility with longer timeframes and when considering social outcomes as opposed to symptom counts. This utility is sufficiently great that there appears to be value in assessing personality; however, no particular approach outperforms any other.

High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer

PubMed Central

Lluch, Ana; Ribelles, Nuria; Anton-Torres, Antonio; Sanchez-Rovira, Pedro; Albanell, Joan; Calvo, Lourdes; García-Asenjo, Jose Antonio Lopez; Palacios, Jose; Chacon, Jose Ignacio; Ruiz, Amparo; De la Haba-Rodriguez, Juan; Segui-Palmer, Miguel A.; Cirauqui, Beatriz; Margeli, Mireia; Plazaola, Arrate; Barnadas, Agusti; Casas, Maribel; Caballero, Rosalia; Carrasco, Eva; Rojo, Federico

2016-01-01

Background. In the neoadjuvant setting, changes in the proliferation marker Ki67 are associated with primary endocrine treatment efficacy, but its value as a predictor of response to chemotherapy is still controversial. Patients and Methods. We analyzed 262 patients with centralized basal Ki67 immunohistochemical evaluation derived from 4 GEICAM (Spanish Breast Cancer Group) clinical trials of neoadjuvant chemotherapy for breast cancer. The objective was to identify the optimal threshold for Ki67 using the receiver-operating characteristic curve method to maximize its predictive value for chemotherapy benefit. We also evaluated the predictive role of the defined Ki67 cutoffs for molecular subtypes defined by estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2). Results. A basal Ki67 cutpoint of 50% predicted pathological complete response (pCR). Patients with Ki67 >50% achieved a pCR rate of 40% (36 of 91) versus a pCR rate of 19% in patients with Ki67 ≤50% (33 of 171) (p = .0004). Ki67 predictive value was especially relevant in ER-HER2− and ER-HER2+ patients (pCR rates of 42% and 64%, respectively, in patients with Ki67 >50% versus 15% and 45%, respectively, in patients with Ki67 ≤50%; p = .0337 and .3238, respectively). Both multivariate analyses confirmed the independent predictive value of the Ki67 cutpoint of 50%. Conclusion. Basal Ki67 proliferation index >50% should be considered an independent predictive factor for pCR reached after neoadjuvant chemotherapy, suggesting that cell proliferation is a phenomenon closely related to chemosensitivity. These findings could help to identify a group of patients with a potentially favorable long-term prognosis. Implications for Practice: The use of basal Ki67 status as a predictive factor of chemotherapy benefit could facilitate the identification of a patient subpopulation with high probability of achieving pathological complete response when treated with primary chemotherapy, and thus with a potentially favorable long-term prognosis. PMID:26786263

Heat Capacity Anomaly Near the Lower Critical Consolute Point of Triethylamine-Water

NASA Technical Reports Server (NTRS)

Flewelling, Anne C.; DeFonseka, Rohan J.; Khaleeli, Nikfar; Partee, J.; Jacobs, D. T.

1996-01-01

The heat capacity of the binary liquid mixture triethylamine-water has been measured near its lower critical consolute point using a scanning, adiabatic calorimeter. Two data runs are analyzed to provide heat capacity and enthalpy data that are fitted by equations with background terms and a critical term that includes correction to scaling. The critical exponent a was determined to be 0.107 +/- 0.006, consistent with theoretical predictions. When alpha was fixed at 0.11 to determine various amplitudes consistently, our values of A(+) and A(-) agreed with a previous heat capacity measurement, but the value of A(-) was inconsistent with values determined by density or refractive index measurements. While our value for the amplitude ratio A(+)/ A(-) = 0.56 +/- 0.02 was consistent with other recent experimental determinations in binary liquid mixtures, it was slightly larger than either theoretical predictions or recent experimental values in liquid-vapor systems. The correction to scaling amplitude ratio D(+)/D(-) = 0.5 +/- 0.1 was half of that predicted. As a result of several more precise theoretical calculations and experimental determinations, the two-scale-factor universality ratio X, which we found to be 0.019 +/- 0.003, now is consistent among experiments and theories. A new 'universal' amplitude ratio R(sup +/-)(sub Bcr) involving the amplitudes for the specific heat was tested. Our determination of R(sup +/-)(sub Bcr) = -0.5 +/- 0.1 and R(sup -)(sub Bcr) = 1.1 +/- 0.1 is smaller in magnitude than predicted and is the first such determination in a binary fluid mixture.

Quantitative analysis of ventricular ectopic beats in short-term RR interval recordings to predict imminent ventricular tachyarrhythmia.

PubMed

Martínez-Alanis, Marisol; Ruiz-Velasco, Silvia; Lerma, Claudia

2016-12-15

Most approaches to predict ventricular tachyarrhythmias which are based on RR intervals consider only sinus beats, excluding premature ventricular complexes (PVCs). The method known as heartprint, which analyses PVCs and their characteristics, has prognostic value for fatal arrhythmias on long recordings of RR intervals (>70,000 beats). To evaluate characteristics of PVCs from short term recordings (around 1000 beats) and their prognostic value for imminent sustained tachyarrhythmia. We analyzed 132 pairs of short term RR interval recordings (one before tachyarrhythmia and one control) obtained from 78 patients. Patients were classified into two groups based on the history of accelerated heart rate (HR) (HR>90bpm) before a tachyarrhythmia episode. Heartprint indexes, such as mean coupling interval (meanCI) and the number of occurrences of the most prevalent form of PVCs (SNIB) were calculated. The predictive value of all the indexes and of the combination of different indexes was calculated. MeanCI shorter than 482ms and the occurrence of more repetitive arrhythmias (sNIB≥2.5), had a significant prognostic value for patients with accelerated heart rate: adjusted odds ratio of 2.63 (1.33-5.17) for meanCI and 2.28 (1.20-4.33) for sNIB. Combining these indexes increases the adjusted odds ratio: 10.94 (3.89-30.80). High prevalence of repeating forms of PVCs and shorter CI are potentially useful risk markers of imminent ventricular tachyarrhythmia. Knowing if a patient has history of VT/VF preceded by accelerated HR, improves the prognostic value of these risk markers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.

PubMed

Chi, Sang-Mun; Nam, Dougu

2012-04-01

We present an accurate and fast web server, WegoLoc for predicting subcellular localization of proteins based on sequence similarity and weighted Gene Ontology (GO) information. A term weighting method in the text categorization process is applied to GO terms for a support vector machine classifier. As a result, WegoLoc surpasses the state-of-the-art methods for previously used test datasets. WegoLoc supports three eukaryotic kingdoms (animals, fungi and plants) and provides human-specific analysis, and covers several sets of cellular locations. In addition, WegoLoc provides (i) multiple possible localizations of input protein(s) as well as their corresponding probability scores, (ii) weights of GO terms representing the contribution of each GO term in the prediction, and (iii) a BLAST E-value for the best hit with GO terms. If the similarity score does not meet a given threshold, an amino acid composition-based prediction is applied as a backup method. WegoLoc and User's guide are freely available at the website http://www.btool.org/WegoLoc smchiks@ks.ac.kr; dougnam@unist.ac.kr Supplementary data is available at http://www.btool.org/WegoLoc.

Short Term Rain Prediction For Sustainability of Tanks in the Tropic Influenced by Shadow Rains

NASA Astrophysics Data System (ADS)

Suresh, S.

2007-07-01

Rainfall and flow prediction, adapting the Venkataraman single time series approach and Wiener multiple time series approach were conducted for Aralikottai tank system, and Kothamangalam tank system, Tamilnadu, India. The results indicated that the raw prediction of daily values is closer to actual values than trend identified predictions. The sister seasonal time series were more amenable for prediction than whole parent time series. Venkataraman single time approach was more suited for rainfall prediction. Wiener approach proved better for daily prediction of flow based on rainfall. The major conclusion is that the sister seasonal time series of rain and flow have their own identities even though they form part of the whole parent time series. Further studies with other tropical small watersheds are necessary to establish this unique characteristic of independent but not exclusive behavior of seasonal stationary stochastic processes as compared to parent non stationary stochastic processes.

Validation of transcutaneous bilirubin nomogram for identifying neonatal hyperbilirubinemia in healthy Chinese term and late-preterm infants: a multicenter study.

PubMed

Yu, Zhangbin; Han, Shuping; Wu, Jinxia; Li, Mingxia; Wang, Huaiyan; Wang, Jimei; Liu, Jiebo; Pan, Xinnian; Yang, Jie; Chen, Chao

2014-01-01

to prospectively validate a previously constructed transcutaneous bilirubin (TcB) nomogram for identifying severe hyperbilirubinemia in healthy Chinese term and late-preterm infants. this was a multicenter study that included 9,174 healthy term and late-preterm infants in eight hospitals of China. TcB measurements were performed using a JM-103 bilirubinometer. TcB values were plotted on a previously developed TcB nomogram, to identify the predictive ability for subsequent significant hyperbilirubinemia. in the present study, 972 neonates (10.6%) developed significant hyperbilirubinemia. The 40(th) percentile of the nomogram could identify all neonates who were at risk of significant hyperbilirubinemia, but with a low positive predictive value (PPV) (18.9%). Of the 453 neonates above the 95(th) percentile, 275 subsequently developed significant hyperbilirubinemia, with a high PPV (60.7%), but with low sensitivity (28.3%). The 75(th) percentile was highly specific (81.9%) and moderately sensitive (79.8%). The area under the curve (AUC) for the TcB nomogram was 0.875. this study validated the previously developed TcB nomogram, which could be used to predict subsequent significant hyperbilirubinemia in healthy Chinese term and late-preterm infants. However, combining TcB nomogram and clinical risk factors could improve the predictive accuracy for severe hyperbilirubinemia, which was not assessed in the study. Further studies are necessary to confirm this combination. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Can a Resident's Publication Record Predict Fellowship Publications?

PubMed Central

Prasad, Vinay; Rho, Jason; Selvaraj, Senthil; Cheung, Mike; Vandross, Andrae; Ho, Nancy

2014-01-01

Background Internal medicine fellowship programs have an incentive to select fellows who will ultimately publish. Whether an applicant's publication record predicts long term publishing remains unknown. Methods Using records of fellowship bound internal medicine residents, we analyzed whether publications at time of fellowship application predict publications more than 3 years (2 years into fellowship) and up to 7 years after fellowship match. We calculate the sensitivity, specificity, positive and negative predictive values and likelihood ratios for every cutoff number of application publications, and plot a receiver operator characteristic curve of this test. Results Of 307 fellowship bound residents, 126 (41%) published at least one article 3 to 7 years after matching, and 181 (59%) of residents do not publish in this time period. The area under the receiver operator characteristic curve is 0.59. No cutoff value for application publications possessed adequate test characteristics. Conclusion The number of publications an applicant has at time of fellowship application is a poor predictor of who publishes in the long term. These findings do not validate the practice of using application publications as a tool for selecting fellows. PMID:24658088

Can a resident's publication record predict fellowship publications?

PubMed

Prasad, Vinay; Rho, Jason; Selvaraj, Senthil; Cheung, Mike; Vandross, Andrae; Ho, Nancy

2014-01-01

Internal medicine fellowship programs have an incentive to select fellows who will ultimately publish. Whether an applicant's publication record predicts long term publishing remains unknown. Using records of fellowship bound internal medicine residents, we analyzed whether publications at time of fellowship application predict publications more than 3 years (2 years into fellowship) and up to 7 years after fellowship match. We calculate the sensitivity, specificity, positive and negative predictive values and likelihood ratios for every cutoff number of application publications, and plot a receiver operator characteristic curve of this test. Of 307 fellowship bound residents, 126 (41%) published at least one article 3 to 7 years after matching, and 181 (59%) of residents do not publish in this time period. The area under the receiver operator characteristic curve is 0.59. No cutoff value for application publications possessed adequate test characteristics. The number of publications an applicant has at time of fellowship application is a poor predictor of who publishes in the long term. These findings do not validate the practice of using application publications as a tool for selecting fellows.

Analysis on Experimental Investigation and Mathematical Modeling of Incompressible Flow Through Ceramic Foam Filters

NASA Astrophysics Data System (ADS)

Akbarnejad, Shahin; Jonsson, Lage Tord Ingemar; Kennedy, Mark William; Aune, Ragnhild Elizabeth; Jönsson, Pӓr Göran

2016-08-01

This paper presents experimental results of pressure drop measurements on 30, 50, and 80 pores per inch (PPI) commercial alumina ceramic foam filters (CFF) and compares the obtained pressure drop profiles to numerically modeled values. In addition, it is aimed at investigating the adequacy of the mathematical correlations used in the analytical and the computational fluid dynamics (CFD) simulations. It is shown that the widely used correlations for predicting pressure drop in porous media continuously under-predict the experimentally obtained pressure drop profiles. For analytical predictions, the negative deviations from the experimentally obtained pressure drop using the unmodified Ergun and Dietrich equations could be as high as 95 and 74 pct, respectively. For the CFD predictions, the deviation to experimental results is in the range of 84.3 to 88.5 pct depending on filter PPI. Better results can be achieved by applying the Forchheimer second-order drag term instead of the Brinkman-Forchheimer drag term. Thus, the final deviation of the CFD model estimates lie in the range of 0.3 to 5.5 pct compared to the measured values.

Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

NASA Astrophysics Data System (ADS)

Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

2018-03-01

In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

NASA Astrophysics Data System (ADS)

ElSaid, AbdElRahman Ahmed

This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

The essential value of long-term experimental data for hydrology and water management

NASA Astrophysics Data System (ADS)

Tetzlaff, Doerthe; Carey, Sean K.; McNamara, James P.; Laudon, Hjalmar; Soulsby, Chris

2017-04-01

Observations and data from long-term experimental watersheds are the foundation of hydrology as a geoscience. They allow us to benchmark process understanding, observe trends and natural cycles, and are prerequisites for testing predictive models. Long-term experimental watersheds also are places where new measurement technologies are developed. These studies offer a crucial evidence base for understanding and managing the provision of clean water supplies, predicting and mitigating the effects of floods, and protecting ecosystem services provided by rivers and wetlands. They also show how to manage land and water in an integrated, sustainable way that reduces environmental and economic costs.

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

PubMed

Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

2018-05-08

Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

Novel and conventional serum biomarkers predicting acute kidney injury in adult cardiac surgery--a prospective cohort study.

PubMed

Haase-Fielitz, Anja; Bellomo, Rinaldo; Devarajan, Prasad; Story, David; Matalanis, George; Dragun, Duska; Haase, Michael

2009-02-01

To compare the value of novel with conventional serum biomarkers in the prediction of acute kidney injury (AKI) in adult cardiac surgical patients according to preoperative renal function. Single-center, prospective observational study. Tertiary hospital. One hundred adult cardiac surgical patients. We measured concentrations of plasma neutrophil gelatinase-associated lipocalin (NGAL), and serum cystatin C, and creatinine and urea at baseline, on arrival in the intensive care unit (ICU) and at 24 hours postoperatively. We assessed such biomarkers in relation to the development of AKI (>50% increase in creatinine from baseline) and to a composite end point (need for renal replacement therapy and in-hospital mortality). We defined an area under the receiver operating characteristic curve of 0.60-0.69 as poor, 0.70-0.79 as fair, 0.80-0.89 as good, and 0.90-1.00 as excellent in terms of predictive value. On arrival in ICU, plasma NGAL and serum cystatin C were of good predictive value, but creatinine and urea were of poor predictive value. After exclusion of patients with preoperative renal impairment (estimated glomerular filtration rate <60 mL/min), the predictive performance for AKI of all renal biomarkers on arrival in ICU remained unchanged except for cystatin C, which was of fair value in such patients. At 24 hours postoperatively, all renal biomarkers were of good predictive value. On arrival in ICU, novel biomarkers were superior to conventional biomarkers (p < 0.05). Plasma NGAL (p = 0.015) and serum cystatin C (p = 0.007) were independent predictors of AKI and of excellent value in the prediction of the composite end point. Early postoperative measurement of plasma NGAL was of good value in identifying patients who developed AKI after adult cardiac surgery. Plasma NGAL and serum cystatin C were superior to conventional biomarkers in the prediction of AKI and were also of prognostic value in this setting.

A New Interpretation of Augmented Subscores and Their Added Value in Terms of Parallel Forms

ERIC Educational Resources Information Center

Sinharay, Sandip

2018-01-01

The value-added method of Haberman is arguably one of the most popular methods to evaluate the quality of subscores. The method is based on the classical test theory and deems a subscore to be of added value if the subscore predicts the corresponding true subscore better than does the total score. Sinharay provided an interpretation of the added…

The Application of Function Points to Predict Source Lines of Code for Software Development

DTIC Science & Technology

1992-09-01

there are some disadvantages. Software estimating tools are expensive. A single tool may cost more than $15,000 due to the high market value of the...term and Lang variables simultaneously onlN added marginal improvements over models with these terms included singularly. Using all the available

Predicting Hydrologic Function With Aquatic Gene Fragments

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with stage III and IV colorectal cancer

PubMed Central

Kim, Jae Hyun; Lee, Jun Yeop; Kim, Hae Koo; Lee, Jin Wook; Jung, Sung Gyu; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-01-01

AIM To evaluate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in patients with colorectal cancer (CRC). METHODS Between April 1996 and December 2010, medical records from a total of 1868 patients with CRC were retrospectively reviewed. The values of simple inflammatory markers including NLR and PLR in predicting the long-term outcomes of these patients were evaluated using Kaplan-Meier curves and Cox regression models. RESULTS The median follow-up duration was 46 mo (interquartile range, 22-73). The estimation of NLR and PLR was based on the time of diagnosis. In multivariate Cox regression analysis, high NLR (≥ 3.0) and high PLR (≥ 160) were independent risk factors predicting poor long-term outcomes in patients with stage III and IV CRC. However, high NLR and high PLR were not prognostic factors in patients with stage I and II CRC. CONCLUSION In this study, we identified that high NLR (≥ 3.0) and high PLR (≥ 160) are useful prognostic factors to predict long-term outcomes in patients with stage III and IV CRC. PMID:28210087

Rural Adolescents' Reading Motivation, Achievement and Behavior across Transition to High School

ERIC Educational Resources Information Center

Cantrell, Susan Chambers; Rintamaa, Margaret; Anderman, Eric M.; Anderman, Lynley H.

2018-01-01

The authors examined 1,781 rural students' reading motivation and behavior across the transition from middle to high school. Using expectancy-value theory, they investigated how motivational variables predicted changes in reading behavior and achievement across the transition in terms of their expectancies, values, and out-of-school reading…

Predictors of long-term renal outcome in lupus nephritis trials: lessons learned from the Euro-Lupus Nephritis cohort.

PubMed

Dall'Era, Maria; Cisternas, Miriam G; Smilek, Dawn E; Straub, Laura; Houssiau, Frédéric A; Cervera, Ricard; Rovin, Brad H; Mackay, Meggan

2015-05-01

There is a need to determine which response measures in lupus nephritis trials are most predictive of good long-term renal function. We used data from the Euro-Lupus Nephritis Trial to evaluate the performance of proteinuria, serum creatinine (Cr), and urinary red blood cells (RBCs) as predictors of good long-term renal outcome. Patients from the Euro-Lupus Nephritis Trial with proteinuria, serum Cr, and urinary RBC measurements at 3, 6, or 12 months and with a minimum of 7 years of followup were included (n = 76). We assessed the ability of these clinical biomarkers at 3, 6, and 12 months after randomization to predict good long-term renal outcome (defined as a serum Cr value ≤1.0 mg/dl) at 7 years. Receiver operating characteristic curves were generated to assess parameter performance at these time points and to select the best cutoff for individual parameters. Sensitivity and specificity were calculated for the parameters alone and in combination. A proteinuria value of <0.8 gm/day at 12 months after randomization was the single best predictor of good long-term renal function (sensitivity 81% and specificity 78%). The addition of serum Cr to proteinuria as a composite predictor did not improve the performance of the outcome measure; addition of urinary RBCs as a predictor significantly decreased the sensitivity to 47%. This study demonstrates that the level of proteinuria at 12 months is the individual best predictor of long-term renal outcome in patients with lupus nephritis. Inclusion of urinary RBCs as part of a composite outcome measure actually undermined the predictive value of the trial data. We therefore suggest that urinary RBCs should not be included as a component of clinical trial response criteria in lupus nephritis. © 2015, American College of Rheumatology.

Long-term prognostic value of a comprehensive assessment of cardiac magnetic resonance indexes after an ST-segment elevation myocardial infarction.

PubMed

Merlos, Pilar; López-Lereu, Maria P; Monmeneu, Jose V; Sanchis, Juan; Núñez, Julio; Bonanad, Clara; Valero, Ernesto; Miñana, Gema; Chaustre, Fabián; Gómez, Cristina; Oltra, Ricardo; Palacios, Lorena; Bosch, Maria J; Navarro, Vicente; Llácer, Angel; Chorro, Francisco J; Bodí, Vicente

2013-08-01

A variety of cardiac magnetic resonance indexes predict mid-term prognosis in ST-segment elevation myocardial infarction patients. The extent of transmural necrosis permits simple and accurate prediction of systolic recovery. However, its long-term prognostic value beyond a comprehensive clinical and cardiac magnetic resonance evaluation is unknown. We hypothesized that a simple semiquantitative assessment of the extent of transmural necrosis is the best resonance index to predict long-term outcome soon after a first ST-segment elevation myocardial infarction. One week after a first ST-segment elevation myocardial infarction we carried out a comprehensive quantification of several resonance parameters in 206 consecutive patients. A semiquantitative assessment (altered number of segments in the 17-segment model) of edema, baseline and post-dobutamine wall motion abnormalities, first pass perfusion, microvascular obstruction, and the extent of transmural necrosis was also performed. During follow-up (median 51 months), 29 patients suffered a major adverse cardiac event (8 cardiac deaths, 11 nonfatal myocardial infarctions, and 10 readmissions for heart failure). Major cardiac events were associated with more severely altered quantitative and semiquantitative resonance indexes. After a comprehensive multivariate adjustment, the extent of transmural necrosis was the only resonance index independently related to the major cardiac event rate (hazard ratio=1.34 [1.19-1.51] per each additional segment displaying>50% transmural necrosis, P<.001). A simple and non-time consuming semiquantitative analysis of the extent of transmural necrosis is the most powerful cardiac magnetic resonance index to predict long-term outcome soon after a first ST-segment elevation myocardial infarction. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

Probabilistic Reasoning and Prediction with Young Children

ERIC Educational Resources Information Center

Kinnear, Virginia; Clark, Julie

2014-01-01

This paper reports findings from a classroom based study with 5 year old children in their first term of school. A data modelling activity contextualised by a picture story book was used to present a prediction problem. A data table with numerical data values provided for three consecutive days of rubbish collection was provided, with a fourth day…

Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states.

PubMed

Kloog, Itai; Nordio, Francesco; Coull, Brent A; Schwartz, Joel

2012-11-06

Satellite-derived aerosol optical depth (AOD) measurements have the potential to provide spatiotemporally resolved predictions of both long and short-term exposures, but previous studies have generally shown moderate predictive power and lacked detailed high spatio- temporal resolution predictions across large domains. We aimed at extending our previous work by validating our model in another region with different geographical and metrological characteristics, and incorporating fine scale land use regression and nonrandom missingness to better predict PM(2.5) concentrations for days with or without satellite AOD measures. We start by calibrating AOD data for 2000-2008 across the Mid-Atlantic. We used mixed models regressing PM(2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We used inverse probability weighting to account for nonrandom missingness of AOD, nested regions within days to capture spatial variation in the daily calibration, and introduced a penalization method that reduces the dimensionality of the large number of spatial and temporal predictors without selecting different predictors in different locations. We then take advantage of the association between grid-cell specific AOD values and PM(2.5) monitoring data, together with associations between AOD values in neighboring grid cells to develop grid cell predictions when AOD is missing. Finally to get local predictions (at the resolution of 50 m), we regressed the residuals from the predictions for each monitor from these previous steps against the local land use variables specific for each monitor. "Out-of-sample" 10-fold cross-validation was used to quantify the accuracy of our predictions at each step. For all days without AOD values, model performance was excellent (mean "out-of-sample" R(2) = 0.81, year-to-year variation 0.79-0.84). Upon removal of outliers in the PM(2.5) monitoring data, the results of the cross validation procedure was even better (overall mean "out of sample"R(2) of 0.85). Further, cross validation results revealed no bias in the predicted concentrations (Slope of observed vs predicted = 0.97-1.01). Our model allows one to reliably assess short-term and long-term human exposures in order to investigate both the acute and effects of ambient particles, respectively.

Hemoglobin levels above anemia thresholds are maximally predictive for long-term survival in COPD with chronic respiratory failure.

PubMed

Kollert, Florian; Tippelt, Andrea; Müller, Carolin; Jörres, Rudolf A; Porzelius, Christine; Pfeifer, Michael; Budweiser, Stephan

2013-07-01

In patients with COPD, chronic anemia is known as an unfavorable prognostic factor. Whether the association between hemoglobin (Hb) levels and long-term survival is restricted to anemia or extends to higher Hb levels has not yet been systematically assessed. We determined Hb levels in 309 subjects with COPD and chronic respiratory failure prior to initiation of noninvasive ventilation, accounting for confounders that might affect Hb. Subjects were categorized as anemic (Hb < 12 g/dL in females, Hb < 13 g/dL in males), polycythemic (Hb ≥ 15 g/dL in females, Hb ≥ 17 g/dL in males), or normocythemic. In addition, percentiles of Hb values were analyzed with regard to mortality from any cause. Two-hundred seven subjects (67.0%) showed normal Hb levels, 46 (14.9%) had anemia, and 56 (18.1%) had polycythemia. Polycythemic subjects showed a higher survival rate than anemic (P = .01) and normocythemic subjects (P = .043). In a univariate Cox hazards model, Hb was associated with long-term survival (hazard ratio 0.855; 95% CI 0.783-0.934, P < .001). The 58th percentiles of Hb (14.3 g/dL in females, 15.1 g/dL in males) yielded the highest discriminative value for predicting survival (hazard ratio 0.463, 95% CI 0.324-0.660, P < .001). In the multivariate analysis this cutoff was an independent predictor for survival (hazard ratio 0.627, 95% CI 0.414-0.949, P = .03), in addition to age and body mass index. In subjects with COPD and chronic respiratory failure undergoing treatment with noninvasive ventilation and LTOT, high Hb levels are associated with better long-term survival. The optimal cutoff level for prediction was above the established threshold defining anemia. Thus, predicting survival only on the basis of anemia does not fully utilize the prognostic potential of Hb values in COPD.

Decisions in Motion: Decision Dynamics during Intertemporal Choice reflect Subjective Evaluation of Delayed Rewards

NASA Astrophysics Data System (ADS)

O'Hora, Denis; Carey, Rachel; Kervick, Aoife; Crowley, David; Dabrowski, Maciej

2016-02-01

People tend to discount rewards or losses that occur in the future. Such delay discounting has been linked to many behavioral and health problems, since people choose smaller short-term gains over greater long-term gains. We investigated whether the effect of delays on the subjective value of rewards is expressed in how people move when they make choices. Over 600 patrons of the RISK LAB exhibition hosted by the Science Gallery DublinTM played a short computer game in which they used a computer mouse to choose between amounts of money at various delays. Typical discounting effects were observed and decision dynamics indicated that choosing smaller short-term rewards became easier (i.e., shorter response times, tighter trajectories, less vacillation) as the delays until later rewards increased. Based on a sequence of choices, subjective values of delayed outcomes were estimated and decision dynamics during initial choices predicted these values. Decision dynamics are affected by subjective values of available options and thus provide a means to estimate such values.

Time series and recurrence interval models to predict the vulnerability of streams to episodic acidification in Shenandoah National Park, Virginia

USGS Publications Warehouse

Deviney, Frank A.; Rice, Karen C.; Hornberger, George M.

2006-01-01

Acid rain affects headwater streams by temporarily reducing the acid‐neutralizing capacity (ANC) of the water, a process termed episodic acidification. The increase in acidic components in stream water can have deleterious effects on the aquatic biota. Although acidic deposition is uniform across Shenandoah National Park (SNP) in north central Virginia, the stream water quality response during rain events varies substantially. This response is a function of the catchment's underlying geology and topography. Geologic and topographic data for SNP's 231 catchments are readily available; however, long‐term measurements (tens of years) of ANC and accompanying discharge are not and would be prohibitively expensive to collect. Transfer function time series models were developed to predict hourly ANC from discharge for five SNP catchments with long‐term water‐quality and discharge records. Hourly ANC predictions over short time periods (≤1 week) were averaged, and distributions of the recurrence intervals of annual water‐year minimum ANC values were model‐simulated for periods of 6, 24, 72, and 168 hours. The distributions were extrapolated to the rest of the SNP catchments on the basis of catchment geology and topography. On the basis of the models, large numbers of SNP streams have 6‐ to 168‐hour periods of low‐ANC values, which may stress resident fish populations. Smaller catchments are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic/carbonate bedrock. Many catchments are predicted to have successive years of low‐ANC values potentially sufficient to extirpate some species.

Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

USGS Publications Warehouse

Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

2012-01-01

The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

Pentraxin-3 Predicts Short- and Mid-term Mortality in Patients with Sepsis and Septic Shock During Intensive Care Treatment.

PubMed

Hamed, Sonja; Behnes, Michael; Pauly, Dominic; Lepiorz, Dominic; Barre, Max; Becher, Tobias; Lang, Siegfried; Akin, Ibrahim; Borggrefe, Martin; Bertsch, Thomas; Hoffmann, Ursula

2018-06-01

The prognostic value of the acute phase protein Pentraxin 3 (PTX-3) is not well evaluated in patients with septic shock, which reveal an unacceptably high short- and long-term mortality. New Sepsis-3 definitions are not yet implemented in most biomarker studies. Therefore, this study assesses the prognostic value of PTX-3 for short- and mid-term mortality in patients with sepsis or septic shock, as defined by the latest definitions, treated at a medical intensive care unit (ICU). The study includes 213 ICU patients with clinical criteria of sepsis and septic shock. Plasma levels of PTX-3, procalcitonin (PCT) and interleukin-6 were measured on day 1, 3, and 8. All-cause mortality was followed up to 30 days and at 6 months. On all three days, PTX-3 levels were able to discriminate non-survivors from survivors at 30 days and 6 months (AUC range: 0.59 - 0.70; 95% CI: 0.52 - 0.79; p ≤ 0.02). Highest PTX-3 levels within the fourth quartiles during the first week of ICU treatment were associated with an increased mortality rate at 30 days (OR = 7; 95% CI: 2.0 - 23.5; p ≤ 0.002) and at 6 months (OR = 5; 95% CI: 2.1 - 11.4; p ≤ 0.006). Additionally, the prognostic value of PTX-3 was proven for all patients as well as in subcohorts of patients with sepsis and septic shock, according to Sepsis-3 criteria, both in univariate and multivariate analyses for 30-day and 6-months all-cause mortality, especially predicting all-cause mortality in septic shock (HRs range: 1.0 - 2.9; 95% CI: 0.3 - 5.1; p ≤ 0.03). PTX-3 offers prognostic value for the prediction of short- and mid-term all-cause mortality in patients suffering from sepsis and septic shock according to the latest Sepsis-3 criteria.

Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning.

PubMed

Månsson, K N T; Frick, A; Boraxbekk, C-J; Marquand, A F; Williams, S C R; Carlbring, P; Andersson, G; Furmark, T

2015-03-17

Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a substantial proportion relapse after treatment has ended. Predicting an individual's long-term clinical response therefore remains an important challenge. This study aimed at assessing neural predictors of long-term treatment outcome in participants with SAD 1 year after completion of Internet-delivered CBT (iCBT). Twenty-six participants diagnosed with SAD underwent iCBT including attention bias modification for a total of 13 weeks. Support vector machines (SVMs), a supervised pattern recognition method allowing predictions at the individual level, were trained to separate long-term treatment responders from nonresponders based on blood oxygen level-dependent (BOLD) responses to self-referential criticism. The Clinical Global Impression-Improvement scale was the main instrument to determine treatment response at the 1-year follow-up. Results showed that the proportion of long-term responders was 52% (12/23). From multivariate BOLD responses in the dorsal anterior cingulate cortex (dACC) together with the amygdala, we were able to predict long-term response rate of iCBT with an accuracy of 92% (confidence interval 95% 73.2-97.6). This activation pattern was, however, not predictive of improvement in the continuous Liebowitz Social Anxiety Scale-Self-report version. Follow-up psychophysiological interaction analyses revealed that lower dACC-amygdala coupling was associated with better long-term treatment response. Thus, BOLD response patterns in the fear-expressing dACC-amygdala regions were highly predictive of long-term treatment outcome of iCBT, and the initial coupling between these regions differentiated long-term responders from nonresponders. The SVM-neuroimaging approach could be of particular clinical value as it allows for accurate prediction of treatment outcome at the level of the individual.

Determination of the acid value of instant noodles: interlaboratory study.

PubMed

Hakoda, Akiko; Sakaida, Kenichi; Suzuki, Tadanao; Yasui, Akemi

2006-01-01

An interlaboratory study was performed to evaluate the method for determining the acid value of instant noodles, based on the Japanese Agricultural Standard (JAS), with extraction of lipid using petroleum ether at a volume of 100 mL to the test portion of 25 g. Thirteen laboratories participated and analyzed 5 test samples as blind duplicates. Statistical treatment revealed that the repeatability (RSDr) of acid value was <6.5%, and the reproducibility (RSDR) of acid value was <9.6%. The HorRat values (RSDR/predicted RSDR) were 1.2-1.8, where the RSDR and the predicted RSDR were obtained in terms of free fatty acids in the noodles per unit weight, using the equation [acid value = percent free fatty acids (as oleic) x 1.99] and the extracted lipid contents. This method was shown to have acceptable precision by the present study.

Re-evaluation of lung to thorax transverse area ratio immediately before birth in predicting postnatal short-term outcomes of fetuses with isolated left-sided congenital diaphragmatic hernia: A single center analysis.

PubMed

Kido, Saki; Hidaka, Nobuhiro; Sato, Yuka; Fujita, Yasuyuki; Miyoshi, Kina; Nagata, Kouji; Taguchi, Tomoaki; Kato, Kiyoko

2018-05-01

We aimed to investigate whether the lung-to-thorax transverse area ratio (LTR) immediately before birth is of diagnostic value for the prediction of postnatal short-term outcomes in cases of isolated left-sided congenital diaphragmatic hernia (CDH). We retrospectively reviewed the cases of fetal isolated left-sided CDH managed at our institution between April 2008 and July 2016. We divided the patients into two groups based on LTR immediately before birth, using a cut-off value of 0.08. We compared the proportions of subjects within the two groups who survived until discharge using Fisher's exact test. Further, using Spearman's rank correlation, we assessed whether LTR was correlated with length of stay, duration of mechanical ventilation, and supplemental oxygen. Twenty-nine subjects were included (five with LTR < 0.08, and 24 with LTR ≥ 0.08). The proportion of subjects surviving until discharge was 40% (2/5) for patients with LTR < 0.08, as compared with 96% (23/24) for those with LTR ≥ 0.08. LTR measured immediately before birth was negatively correlated with the postnatal length of stay (Spearman's rank correlation coefficient, rs = -0.486), and the duration of supplemental oxygen (rs = -0.537). Further, the duration of mechanical ventilation was longer in patients with a lower LTR value. LTR immediately before birth is useful for the prediction of postnatal short-term outcomes in fetuses with isolated left-sided CDH. In particular, patients with prenatal LTR value less than 0.08 are at increased risk of postnatal death. © 2017 Japanese Teratology Society.

[Evaluation of performance of five bioinformatics software for the prediction of missense mutations].

PubMed

Chen, Qianting; Dai, Congling; Zhang, Qianjun; Du, Juan; Li, Wen

2016-10-01

To study the prediction performance evaluation with five kinds of bioinformatics software (SIFT, PolyPhen2, MutationTaster, Provean, MutationAssessor). From own database for genetic mutations collected over the past five years, Chinese literature database, Human Gene Mutation Database, and dbSNP, 121 missense mutations confirmed by functional studies, and 121 missense mutations suspected to be pathogenic by pedigree analysis were used as positive gold standard, while 242 missense mutations with minor allele frequency (MAF)>5% in dominant hereditary diseases were used as negative gold standard. The selected mutations were predicted with the five software. Based on the results, the performance of the five software was evaluated for their sensitivity, specificity, positive predict value, false positive rate, negative predict value, false negative rate, false discovery rate, accuracy, and receiver operating characteristic curve (ROC). In terms of sensitivity, negative predictive value and false negative rate, the rank was MutationTaster, PolyPhen2, Provean, SIFT, and MutationAssessor. For specificity and false positive rate, the rank was MutationTaster, Provean, MutationAssessor, SIFT, and PolyPhen2. For positive predict value and false discovery rate, the rank was MutationTaster, Provean, MutationAssessor, PolyPhen2, and SIFT. For area under the ROC curve (AUC) and accuracy, the rank was MutationTaster, Provean, PolyPhen2, MutationAssessor, and SIFT. The prediction performance of software may be different when using different parameters. Among the five software, MutationTaster has the best prediction performance.

The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

PubMed

O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

2016-04-01

The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.

A behavioral economic reward index predicts drinking resolutions: moderation revisited and compared with other outcomes.

PubMed

Tucker, Jalie A; Roth, David L; Vignolo, Mary J; Westfall, Andrew O

2009-04-01

Data were pooled from 3 studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1- to 2-year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes than abstinence or relapse and to be predicted by more balanced preresolution monetary allocations between short-term and longer term objectives (i.e., drinking and saving for the future). Standardized odds ratios (ORs) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this "Alcohol-Savings Discretionary Expenditure" index predicted higher rates of abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p < .0001) compared with moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of preresolution spending patterns aids in predicting moderation.

Procedures for adjusting regional regression models of urban-runoff quality using local data

USGS Publications Warehouse

Hoos, A.B.; Sisolak, J.K.

1993-01-01

Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP?s as it was for the local regression models.

Predicting the losses in sawtimber volume and quality from fires in oak-hickory forests.

Treesearch

Robert M. Loomis

1974-01-01

Presents a method for predicting future sawtimber losses due to fire-caused wounds. Losses are in terms of: (1) lumber value in dollars, (2) volume in board feet, (3) length of defect in feet, and (4) cross sectional area of defect in square inches. The methods apply to northern red, black, scarlet, white and chestnut oaks.

Scenic beauty estimation model: predicting perceived beauty of forest landscapes

Treesearch

Terry C. Daniel; Herbert Schroeder

1979-01-01

An important activity in any land-use planning process is prediction of the consequences of alternative management approaches. Alternative plans must be com-pared in terms of their respective costs (economic and environmental) and benefits (in market and non-market values) if rational choice among them is to be made. The purpose of this paper is to describe a model for...

Inflection point in running kinetic term inflation

NASA Astrophysics Data System (ADS)

Gao, Tie-Jun; Xiu, Wu-Tao; Yang, Xiu-Yi

2017-04-01

In this work, we calculate the general form of the scalar potential with polynomial superpotential in the framework of running kinetic term inflation, then focus on a polynomial superpotential with two terms and obtain the inflection point inflationary model. We study the inflationary dynamics and show that the predicted value of the scalar spectral index and tensor-to-scalar ratio can lie within the 1σ confidence region allowed by the result of Planck 2015.

Escherichia coli bacteria density in relation to turbidity, streamflow characteristics, and season in the Chattahoochee River near Atlanta, Georgia, October 2000 through September 2008—Description, statistical analysis, and predictive modeling

USGS Publications Warehouse

Lawrence, Stephen J.

2012-01-01

Regression analyses show that E. coli density in samples was strongly related to turbidity, streamflow characteristics, and season at both sites. The regression equation chosen for the Norcross data showed that 78 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), streamflow event (dry-weather flow or stormflow), season (cool or warm), and an interaction term that is the cross product of streamflow event and turbidity. The regression equation chosen for the Atlanta data showed that 76 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), water temperature, streamflow event, and an interaction term that is the cross product of streamflow event and turbidity. Residual analysis and model confirmation using new data indicated the regression equations selected at both sites predicted E. coli density within the 90 percent prediction intervals of the equations and could be used to predict E. coli density in real time at both sites.

Data Analysis and Its Impact on Predicting Schedule & Cost Risk

DTIC Science & Technology

2006-03-01

variance of the error term by performing a Breusch - Pagan test for constant variance (Neter et al., 1996:239). In order to test the normality of...is constant variance. Using Microsoft Excel®, we calculate a p- 68 value of 0.225678 for the Breusch - Pagan test . We again compare this p-value to...calculate a p-value of 0.121211092 Breusch - Pagan test . We again compare this p-value to an alpha of 0.05 indicating our assumption of constant variance

Simulating boundary layer transition with low-Reynolds-number k-epsilon turbulence models. I - An evaluation of prediction characteristics. II - An approach to improving the predictions

NASA Technical Reports Server (NTRS)

Schmidt, R. C.; Patankar, S. V.

1991-01-01

The capability of two k-epsilon low-Reynolds number (LRN) turbulence models, those of Jones and Launder (1972) and Lam and Bremhorst (1981), to predict transition in external boundary-layer flows subject to free-stream turbulence is analyzed. Both models correctly predict the basic qualitative aspects of boundary-layer transition with free stream turbulence, but for calculations started at low values of certain defined Reynolds numbers, the transition is generally predicted at unrealistically early locations. Also, the methods predict transition lengths significantly shorter than those found experimentally. An approach to overcoming these deficiencies without abandoning the basic LRN k-epsilon framework is developed. This approach limits the production term in the turbulent kinetic energy equation and is based on a simple stability criterion. It is correlated to the free-stream turbulence value. The modification is shown to improve the qualitative and quantitative characteristics of the transition predictions.

Prediction of Mechanical Properties of Polymers With Various Force Fields

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Optimization of Regression Models of Experimental Data Using Confirmation Points

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2010-01-01

A new search metric is discussed that may be used to better assess the predictive capability of different math term combinations during the optimization of a regression model of experimental data. The new search metric can be determined for each tested math term combination if the given experimental data set is split into two subsets. The first subset consists of data points that are only used to determine the coefficients of the regression model. The second subset consists of confirmation points that are exclusively used to test the regression model. The new search metric value is assigned after comparing two values that describe the quality of the fit of each subset. The first value is the standard deviation of the PRESS residuals of the data points. The second value is the standard deviation of the response residuals of the confirmation points. The greater of the two values is used as the new search metric value. This choice guarantees that both standard deviations are always less or equal to the value that is used during the optimization. Experimental data from the calibration of a wind tunnel strain-gage balance is used to illustrate the application of the new search metric. The new search metric ultimately generates an optimized regression model that was already tested at regression model independent confirmation points before it is ever used to predict an unknown response from a set of regressors.

Longitudinal association of short-term, metronome-paced heart rate variability and echocardiographically assessed cardiac structure at a 4-year follow-up: results from the prospective, population-based CARLA cohort.

PubMed

Medenwald, Daniel; Swenne, Cees A; Frantz, Stefan; Nuding, Sebastian; Kors, Jan A; Pietzner, Diana; Tiller, Daniel; Greiser, Karin H; Kluttig, Alexander; Haerting, Johannes

2017-12-01

To assess the value of cardiac structure/function in predicting heart rate variability (HRV) and the possibly predictive value of HRV on cardiac parameters. Baseline and 4-year follow-up data from the population-based CARLA cohort were used (790 men, 646 women, aged 45-83 years at baseline and 50-87 years at follow-up). Echocardiographic and HRV recordings were performed at baseline and at follow-up. Linear regression models with a quadratic term were used. Crude and covariate adjusted estimates were calculated. Missing values were imputed by means of multiple imputation. Heart rate variability measures taken into account consisted of linear time and frequency domain [standard deviation of normal-to-normal intervals (SDNN), high-frequency power (HF), low-frequency power (LF), LF/HF ratio] and non-linear measures [detrended fluctuation analysis (DFA1), SD1, SD2, SD1/SD2 ratio]. Echocardiographic parameters considered were ventricular mass index, diastolic interventricular septum thickness, left ventricular diastolic dimension, left atrial dimension systolic (LADS), and ejection fraction (Teichholz). A negative quadratic relation between baseline LADS and change in SDNN and HF was observed. The maximum HF and SDNN change (an increase of roughly 0.02%) was predicted at LADS of 3.72 and 3.57 cm, respectively, while the majority of subjects experienced a decrease in HRV. There was no association between further echocardiographic parameters and change in HRV, and there was no evidence of a predictive value of HRV in the prediction of changes in cardiac structure. In the general population, LADS predicts 4-year alteration in SDNN and HF non-linearly. Because of the novelty of the result, analyses should be replicated in other populations. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions please email: journals.permissions@oup.com.

Prediction of resilient modulus from soil index properties.

DOT National Transportation Integrated Search

2004-11-01

Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new : design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical : speci...

Prediction of resilient modulus from soil index properties

DOT National Transportation Integrated Search

2004-11-01

Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical specimens...

Accuracy test for link prediction in terms of similarity index: The case of WS and BA models

NASA Astrophysics Data System (ADS)

Ahn, Min-Woo; Jung, Woo-Sung

2015-07-01

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barabási-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

USGS Publications Warehouse

Tangborn, Wendell V.

1980-01-01

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction (Cp) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

CaPTHUS scoring model in primary hyperparathyroidism: can it eliminate the need for ioPTH testing?

PubMed

Elfenbein, Dawn M; Weber, Sara; Schneider, David F; Sippel, Rebecca S; Chen, Herbert

2015-04-01

The CaPTHUS model was reported to have a positive predictive value of 100 % to correctly predict single-gland disease in patients with primary hyperparathyroidism, thus obviating the need for intraoperative parathyroid hormone (ioPTH) testing. We sought to apply the CaPTHUS scoring model in our patient population and assess its utility in predicting long-term biochemical cure. We retrospective reviewed all parathyroidectomies for primary hyperparathyroidism performed at our university hospital from 2003 to 2012. We routinely perform ioPTH testing. Biochemical cure was defined as a normal calcium level at 6 months. A total of 1,421 patients met the inclusion criteria: 78 % of patients had a single adenoma at the time of surgery, 98 % had a normal serum calcium at 1 week postoperatively, and 96 % had a normal serum calcium level 6 months postoperatively. Using the CaPTHUS scoring model, 307 patients (22.5 %) had a score of ≥ 3, with a positive predictive value of 91 % for single adenoma. A CaPTHUS score of ≥ 3 had a positive predictive value of 98 % for biochemical cure at 1 week as well as at 6 months. In our population, where ioPTH testing is used routinely to guide use of bilateral exploration, patients with a preoperative CaPTHUS score of ≥ 3 had good long-term biochemical cure rates. However, the model only predicted adenoma in 91 % of cases. If minimally invasive parathyroidectomy without ioPTH testing had been done for these patients, the cure rate would have dropped from 98 % to an unacceptable 89 %. Even in these patients with high CaPTHUS scores, multigland disease is present in almost 10 %, and ioPTH testing is necessary.

Mathematical models of human paralyzed muscle after long-term training.

PubMed

Law, L A Frey; Shields, R K

2007-01-01

Spinal cord injury (SCI) results in major musculoskeletal adaptations, including muscle atrophy, faster contractile properties, increased fatigability, and bone loss. The use of functional electrical stimulation (FES) provides a method to prevent paralyzed muscle adaptations in order to sustain force-generating capacity. Mathematical muscle models may be able to predict optimal activation strategies during FES, however muscle properties further adapt with long-term training. The purpose of this study was to compare the accuracy of three muscle models, one linear and two nonlinear, for predicting paralyzed soleus muscle force after exposure to long-term FES training. Further, we contrasted the findings between the trained and untrained limbs. The three models' parameters were best fit to a single force train in the trained soleus muscle (N=4). Nine additional force trains (test trains) were predicted for each subject using the developed models. Model errors between predicted and experimental force trains were determined, including specific muscle force properties. The mean overall error was greatest for the linear model (15.8%) and least for the nonlinear Hill Huxley type model (7.8%). No significant error differences were observed between the trained versus untrained limbs, although model parameter values were significantly altered with training. This study confirmed that nonlinear models most accurately predict both trained and untrained paralyzed muscle force properties. Moreover, the optimized model parameter values were responsive to the relative physiological state of the paralyzed muscle (trained versus untrained). These findings are relevant for the design and control of neuro-prosthetic devices for those with SCI.

Earthquake prediction in Japan and natural time analysis of seismicity

NASA Astrophysics Data System (ADS)

Uyeda, S.; Varotsos, P.

2011-12-01

M9 super-giant earthquake with huge tsunami devastated East Japan on 11 March, causing more than 20,000 casualties and serious damage of Fukushima nuclear plant. This earthquake was predicted neither short-term nor long-term. Seismologists were shocked because it was not even considered possible to happen at the East Japan subduction zone. However, it was not the only un-predicted earthquake. In fact, throughout several decades of the National Earthquake Prediction Project, not even a single earthquake was predicted. In reality, practically no effective research has been conducted for the most important short-term prediction. This happened because the Japanese National Project was devoted for construction of elaborate seismic networks, which was not the best way for short-term prediction. After the Kobe disaster, in order to parry the mounting criticism on their no success history, they defiantly changed their policy to "stop aiming at short-term prediction because it is impossible and concentrate resources on fundamental research", that meant to obtain "more funding for no prediction research". The public were and are not informed about this change. Obviously earthquake prediction would be possible only when reliable precursory phenomena are caught and we have insisted this would be done most likely through non-seismic means such as geochemical/hydrological and electromagnetic monitoring. Admittedly, the lack of convincing precursors for the M9 super-giant earthquake has adverse effect for us, although its epicenter was far out off shore of the range of operating monitoring systems. In this presentation, we show a new possibility of finding remarkable precursory signals, ironically, from ordinary seismological catalogs. In the frame of the new time domain termed natural time, an order parameter of seismicity, κ1, has been introduced. This is the variance of natural time kai weighted by normalised energy release at χ. In the case that Seismic Electric Signals' (SES) data are available as in Greece, the natural time analysis of the seismicity after the initiation of the SES allows the determination of the time window of the impending mainshock through the evolution of the value of κ1 itself. It was found to work also for the 1989 M7.1 Loma Prieta earthquake. If SES data are not available, we solely rely on the evolution of the fluctuations of κ1 obtained by computing κ1 values using a natural time window of certain length sliding through the earthquake catalog. The fluctuations of the order parameter, in terms of variability, i. e., standard deviation divided by average, was found to increase dramatically when approaching the 11 March M9 super- giant earthquake. In fact, such increase was also found for M7.1 Kobe in 1995, M8.0 Tokachi-oki in 2003 and Landers and Hector-Mines earthquakes in Southern California. It is worth mentioning that such increase is obtained straghtforwardly from ordinary earthquake catalogs without any adjustable parameters.

Predictive value of T2 relative signal intensity for response to somatostatin analogs in newly diagnosed acromegaly.

PubMed

Shen, Ming; Zhang, Qilin; Liu, Wenjuan; Wang, Meng; Zhu, Jingjing; Ma, Zengyi; He, Wenqiang; Li, Shiqi; Shou, Xuefei; Li, Yiming; Zhang, Zhaoyun; Ye, Hongying; He, Min; Lu, Bin; Yao, Zhenwei; Lu, Yun; Qiao, Nidan; Ye, Zhao; Zhang, Yichao; Yang, Yeping; Zhao, Yao; Wang, Yongfei

2016-11-01

The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the correlation between MRI rSI and expression of somatostatin receptors (SSTR). This was a retrospective review of prospectively recorded data. Ninety-two newly diagnosed patients (37 males and 55 females) with active acromegaly were recruited. All patients were treated with pre-surgical SSA, followed by reassessment and transspenoidal surgery. rSI values were generated by calculating the ratio of SI in the tumor to the SI of normal frontal white matter. The Youden indices were calculated to determine the optimal cutoff of rSI to determine the efficacy of SSA. The correlation between rSI and expression of SSTR2/5 was analyzed by the Spearman rank correlation coefficient. T2 rSI was strongly correlated with biochemical sensitivity to SSA. The cutoff value of T2 rSI to distinguish biochemical sensitivity was 1.205, with a positive predictive value (PPV) of 81.5 % and a negative predictive value (NPV) of 77.3 %. No correlation was found between MRI and tumor size sensitivity. Moreover, T2 rSI was negatively correlated with the expression of SSTR5. T2 rSI correlates with the expression of SSTR5 and quantitatively predicts the biochemical efficacy of SSA in acromegaly.

Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function.

PubMed

Perco, Paul; Heinzel, Andreas; Leierer, Johannes; Schneeberger, Stefan; Bösmüller, Claudia; Oberhuber, Rupert; Wagner, Silvia; Engler, Franziska; Mayer, Gert

2018-05-03

Donor organ quality affects long term outcome after renal transplantation. A variety of prognostic molecular markers is available, yet their validity often remains undetermined. A network-based molecular model reflecting donor kidney status based on transcriptomics data and molecular features reported in scientific literature to be associated with chronic allograft nephropathy was created. Significantly enriched biological processes were identified and representative markers were selected. An independent kidney pre-implantation transcriptomics dataset of 76 organs was used to predict estimated glomerular filtration rate (eGFR) values twelve months after transplantation using available clinical data and marker expression values. The best-performing regression model solely based on the clinical parameters donor age, donor gender, and recipient gender explained 17% of variance in post-transplant eGFR values. The five molecular markers EGF, CD2BP2, RALBP1, SF3B1, and DDX19B representing key molecular processes of the constructed renal donor organ status molecular model in addition to the clinical parameters significantly improved model performance (p-value = 0.0007) explaining around 33% of the variability of eGFR values twelve months after transplantation. Collectively, molecular markers reflecting donor organ status significantly add to prediction of post-transplant renal function when added to the clinical parameters donor age and gender.

Ab initio estimates of the size of the observable universe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Page, Don N., E-mail: profdonpage@gmail.com

2011-09-01

When one combines multiverse predictions by Bousso, Hall, and Nomura for the observed age and size of the universe in terms of the proton and electron charge and masses with anthropic predictions of Carter, Carr, and Rees for these masses in terms of the charge, one gets that the age of the universe should be roughly the inverse 64th power, and the cosmological constant should be around the 128th power, of the proton charge. Combining these with a further renormalization group argument gives a single approximate equation for the proton charge, with no continuous adjustable or observed parameters, and withmore » a solution that is within 8% of the observed value. Using this solution gives large logarithms for the age and size of the universe and for the cosmological constant that agree with the observed values within 17%.« less

Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI.

PubMed

Colas, Jaron T; Pauli, Wolfgang M; Larsen, Tobias; Tyszka, J Michael; O'Doherty, John P

2017-10-01

Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.

Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI

PubMed Central

Pauli, Wolfgang M.; Larsen, Tobias; Tyszka, J. Michael; O’Doherty, John P.

2017-01-01

Prediction-error signals consistent with formal models of “reinforcement learning” (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models—namely, “actor/critic” models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning. PMID:29049406

Analytical performance evaluation of SAR ATR with inaccurate or estimated models

NASA Astrophysics Data System (ADS)

DeVore, Michael D.

2004-09-01

Hypothesis testing algorithms for automatic target recognition (ATR) are often formulated in terms of some assumed distribution family. The parameter values corresponding to a particular target class together with the distribution family constitute a model for the target's signature. In practice such models exhibit inaccuracy because of incorrect assumptions about the distribution family and/or because of errors in the assumed parameter values, which are often determined experimentally. Model inaccuracy can have a significant impact on performance predictions for target recognition systems. Such inaccuracy often causes model-based predictions that ignore the difference between assumed and actual distributions to be overly optimistic. This paper reports on research to quantify the effect of inaccurate models on performance prediction and to estimate the effect using only trained parameters. We demonstrate that for large observation vectors the class-conditional probabilities of error can be expressed as a simple function of the difference between two relative entropies. These relative entropies quantify the discrepancies between the actual and assumed distributions and can be used to express the difference between actual and predicted error rates. Focusing on the problem of ATR from synthetic aperture radar (SAR) imagery, we present estimators of the probabilities of error in both ideal and plug-in tests expressed in terms of the trained model parameters. These estimators are defined in terms of unbiased estimates for the first two moments of the sample statistic. We present an analytical treatment of these results and include demonstrations from simulated radar data.

Proposal for a New Predictive Model of Short-Term Mortality After Living Donor Liver Transplantation due to Acute Liver Failure.

PubMed

Chung, Hyun Sik; Lee, Yu Jung; Jo, Yun Sung

2017-02-21

BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after LDLT due to ALF. The recommended cut-off value of MELD-p is 3.98.

Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Li, Yane; Fan, Ming; Cheng, Hu; Zhang, Peng; Zheng, Bin; Li, Lihua

2018-01-01

This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All ‘prior’ images acquired in the two screening series were negative, while in the ‘current’ screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the ‘prior’ negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863  ±  0.0237 to 0.6870  ±  0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p  =  0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p  =  0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555  ±  0.0437, 0.6958  ±  0.0290, and 0.7054  ±  0.0529 for the three age groups of 37-49, 50-65, and 66-87 years old, respectively. AUC values of 0.6529  ±  0.1100, 0.6820  ±  0.0353, 0.6836  ±  0.0302 and 0.8043  ±  0.1067 were yielded for the four mammography density sub-groups (BIRADS from 1-4), respectively. This study demonstrated that bilateral asymmetry features extracted from local regions combined with the global region in bilateral negative mammograms could be used as a new imaging marker to assist in the prediction of short-term breast cancer risk.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1988-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 to + or - 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was developed to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Strengths of specimens containing crack-like slits were calculated from predicted failing strains using uniaxial stress-strain curves. Predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only + or - 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Evaluation and interpretation of Thematic Mapper ratios in equations for estimating corn growth parameters

NASA Technical Reports Server (NTRS)

Dardner, B. R.; Blad, B. L.; Thompson, D. R.; Henderson, K. E.

1985-01-01

Reflectance and agronomic Thematic Mapper (TM) data were analyzed to determine possible data transformations for evaluating several plant parameters of corn. Three transformation forms were used: the ratio of two TM bands, logarithms of two-band ratios, and normalized differences of two bands. Normalized differences and logarithms of two-band ratios responsed similarly in the equations for estimating the plant growth parameters evaluated in this study. Two-term equations were required to obtain the maximum predictability of percent ground cover, canopy moisture content, and total wet phytomass. Standard error of estimate values were 15-26 percent lower for two-term estimates of these parameters than for one-term estimates. The terms log(TM4/TM2) and (TM4/TM5) produced the maximum predictability for leaf area and dry green leaf weight, respectively. The middle infrared bands TM5 and TM7 are essential for maximizing predictability for all measured plant parameters except leaf area index. The estimating models were evaluated over bare soil to discriminate between equations which are statistically similar. Qualitative interpretations of the resulting prediction equations are consistent with general agronomic and remote sensing theory.

[Early prediction of the neurological result at 12 months in newborns at neurological risk].

PubMed

Herbón, F; Garibotti, G; Moguilevsky, J

2015-08-01

The aim of this study was to evaluate the Amiel-Tison neurological examination (AT) and cranial ultrasound at term for predicting the neurological result at 12 months in newborns with neurological risk. The study included 89 newborns with high risk of neurological damage, who were discharged from the Neonatal Intensive Care of the Hospital Zonal Bariloche, Argentina. The assessment consisted of a neurological examination and cranial ultrasound at term, and neurological examination and evaluation of development at 12 months. The sensitivity, specificity, positive and negative predictor value was calculated. The relationship between perinatal factors and neurodevelopment at 12 month of age was also calculated using logistic regression models. Seventy children completed the follow-up. At 12 months of age, 14% had an abnormal neurological examination, and 17% abnormal development. The neurological examination and the cranial ultrasound at term had low sensitivity to predict abnormal neurodevelopment. At 12 months, 93% of newborns with normal AT showed normal neurological results, and 86% normal development. Among newborns with normal cranial ultrasound the percentages were 90 and 81%, respectively. Among children with three or more perinatal risk factors, the frequency of abnormalities in the neurological response was 5.4 times higher than among those with fewer risk factors, and abnormal development was 3.5 times more frequent. The neurological examination and cranial ultrasound at term had low sensitivity but high negative predictive value for the neurodevelopment at 12 months. Three or more perinatal risk factors were associated with neurodevelopment abnormalities at 12 months of age. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

DIVERGT screening procedure predicts general cognitive functioning in adult long-term survivors of pediatric acute lymphoblastic leukemia: A PETALE study.

PubMed

Boulet-Craig, Aubree; Robaey, Philippe; Laniel, Julie; Bertout, Laurence; Drouin, Simon; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Sultan, Serge; Lippé, Sarah

2018-05-24

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Because of major improvements in treatment protocols, the survival rate now exceeds 80%. However, ALL treatments can cause long-term neurocognitive sequelae, which negatively impact academic achievement and quality of life. Therefore, cognitive sequelae need to be carefully evaluated. The DIVERGT is a battery of tests proposed as a screening tool, sensitive to executive function impairments in children and adolescent cancer survivors. Our study aimed at verifying the predictive value of the DIVERGT on general cognitive functioning in adult long-term survivors of ALL. ALL survivors completed the DIVERGT 13.4 years, on average, after remission (N = 247). In addition, 49 of these survivors (equally selected amongst those with low, average, and high DIVERGT scores) as well as 29 controls completed a more comprehensive neuropsychological evaluation within a 3-year period from DIVERGT administration. Multivariate regression analysis was used to assess the predictive value of the DIVERGT on general intelligence, mathematics, verbal memory, and working memory. As a follow-up analysis, three performance groups were created based on the DIVERGT results. Multivariate analysis of variance (MANOVA) assessed neuropsychological differences between groups. The DIVERGT accurately predicted General Ability Index (GAI) (P < 0.0001), mathematics (P < 0.0001) and verbal memory (P = 0.045). Moreover, the low-performance group consistently had poorer performance than the high-performance and control groups on the neuropsychological tests. The DIVERGT is a useful, time-effective screening battery for broader neurocognitive impairments identification in long-term adult ALL survivors. It could be implemented as routine examination in cancer follow-up clinics. © 2018 Wiley Periodicals, Inc.

Long-term disability progression in primary progressive multiple sclerosis: a 15-year study.

PubMed

Rocca, Maria A; Sormani, Maria Pia; Rovaris, Marco; Caputo, Domenico; Ghezzi, Angelo; Montanari, Enrico; Bertolotto, Antonio; Laroni, Alice; Bergamaschi, Roberto; Martinelli, Vittorio; Comi, Giancarlo; Filippi, Massimo

2017-11-01

Prognostic markers of primary progressive multiple sclerosis evolution are needed. We investigated the added value of magnetic resonance imaging measures of brain and cervical cord damage in predicting long-term clinical worsening of primary progressive multiple sclerosis compared to simple clinical assessment. In 54 patients, conventional and diffusion tensor brain scans and cervical cord T1-weighted scans were acquired at baseline and after 15 months. Clinical evaluation was performed after 5 and 15 years in 49 patients. Lesion load, brain and cord atrophy, mean diffusivity and fractional anisotropy values from the brain normal-appearing white matter and grey matter were obtained. Using linear regression models, we screened the clinical and imaging variables as independent predictors of 15-year disability change (measured on the expanded disability status scale). At 15 years, 90% of the patients had disability progression. Integrating clinical and imaging variables at 15 months predicted disability changes at 15 years better than clinical factors at 5 years (R2 = 61% versus R2 = 57%). The model predicted long-term disability change with a precision within one point in 38 of 49 patients (77.6%). Integration of clinical and imaging measures allows identification of primary progressive multiple sclerosis patients at risk of long-term disease progression 4 years earlier than when using clinical assessment alone. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Estimation of Filling and Afterload Conditions by Pump Intrinsic Parameters in a Pulsatile Total Artificial Heart.

PubMed

Cuenca-Navalon, Elena; Laumen, Marco; Finocchiaro, Thomas; Steinseifer, Ulrich

2016-07-01

A physiological control algorithm is being developed to ensure an optimal physiological interaction between the ReinHeart total artificial heart (TAH) and the circulatory system. A key factor for that is the long-term, accurate determination of the hemodynamic state of the cardiovascular system. This study presents a method to determine estimation models for predicting hemodynamic parameters (pump chamber filling and afterload) from both left and right cardiovascular circulations. The estimation models are based on linear regression models that correlate filling and afterload values with pump intrinsic parameters derived from measured values of motor current and piston position. Predictions for filling lie in average within 5% from actual values, predictions for systemic afterload (AoPmean , AoPsys ) and mean pulmonary afterload (PAPmean ) lie in average within 9% from actual values. Predictions for systolic pulmonary afterload (PAPsys ) present an average deviation of 14%. The estimation models show satisfactory prediction and confidence intervals and are thus suitable to estimate hemodynamic parameters. This method and derived estimation models are a valuable alternative to implanted sensors and are an essential step for the development of a physiological control algorithm for a fully implantable TAH. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Morality, values, traditional bullying, and cyberbullying in adolescence.

PubMed

Menesini, Ersilia; Nocentini, Annalaura; Camodeca, Marina

2013-03-01

The aim of the present study was to investigate moral aspects and human values in traditional bullying and cyberbullying, in order to detect differences between the two types of bullying and to test the role of immoral and disengaged behaviours in mediating the relationships between personal values and involvement in bullying. Sample comprised 390 adolescents aged 14-18, balanced for gender, attending different high schools. Traditional and cyberbullying were detected by means of two self-report measures, while the Portrait Values Questionnaire was used to assess 10 values in four dimensions according to the value system model by Schwartz (1992): self-trascendence, self-enhancement, openness to change, and conservation. Finally, immoral and disengaged behaviours were assessed by means of five items about behavioural and personal aspects salient for morality. Results showed that, irrespective of gender, self-enhancement and self-trascendence moderately predicted cyber and traditional bullying, respectively, while immoral and disengaged behaviours predicted both. Indirect effects showed that self-enhancement and openness to change predicted both forms of bullying through immoral behaviour. Results are discussed in terms of similarities and differences between cyber and traditional bullying and with attention to the central role of morality in explaining bullying nature. © 2011 The British Psychological Society.

Utilizing Remote Sensing Information to Improve Post-fire Rainfall-runoff Predictions after the 2010 Bull Fire in the Sequoia National Forest, CA

NASA Astrophysics Data System (ADS)

Kinoshita, A. M.; Hale, B.; Hogue, T. S.

2012-12-01

Post-fire management decisions are guided by rainfall-runoff predictions, which ultimately influence downstream treatment and mitigation costs. The current study investigates evolving rainfall-runoff partitioning at the watershed scale over a two-year period after the 2010 Bull Fire which occurred in the southern Sequoia National Forest in California. Stage height was measured at five-minute intervals using pressure transducers, tipping buckets were installed for rainfall duration and intensity, and channel cross-sections were measured approximately every two months to detail sediment deposition or scour. We also utilize remotely sensed vegetation data to evaluate vegetation recovery in the studied watersheds and the corresponding relationship to storm runoff. Normalized Difference Vegetation Index (NDVI), a measure of vegetation greenness, is evaluated for its potential use as a key recovery indicator. Preliminary results focus on alterations in annual and seasonal precipitation and discharge relationships using in-situ data and Landsat NDVI values for the period of study. NDVI values are consistent with a comprehensive burn, with an acute decrease observed in the initial post-fire period. However, vegetation recovery is highly variable in the studied systems and influenced by shorter-term biomass pulses (grasses) while longer-term recovery of other species (chaparral and pine) is ongoing. Runoff ratios are elevated during early storms and show some recovery in the later part of the study period. The ability to accurately and confidently predict post-fire runoff and longer-term recovery is critical for monitoring values-at-risk, reducing mitigation costs, and improving warnings to downstream public communities.

Brain injury patterns in hypoglycemia in neonatal encephalopathy.

PubMed

Wong, D S T; Poskitt, K J; Chau, V; Miller, S P; Roland, E; Hill, A; Tam, E W Y

2013-07-01

Low glucose values are often seen in term infants with NE, including HIE, yet the contribution of hypoglycemia to the pattern of neurologic injury remains unclear. We hypothesized that MR features of neonatal hypoglycemia could be detected, superimposed on the predominant HIE injury pattern. Term neonates (n = 179) with NE were prospectively imaged with day-3 MR studies and had glucose data available for review. The predominant imaging pattern of HIE was recorded as watershed, basal ganglia, total, focal-multifocal, or no injury. Radiologic hypoglycemia was diagnosed on the basis of selective edema in the posterior white matter, pulvinar, and anterior medial thalamic nuclei. Clinical charts were reviewed for evidence of NE, HIE, and hypoglycemia (<46 mg/dL). The predominant pattern of HIE injury imaged included 17 watershed, 25 basal ganglia, 10 total, 42 focal-multifocal, and 85 cases of no injury. A radiologic diagnosis of hypoglycemia was made in 34 cases. Compared with laboratory-confirmed hypoglycemia, MR findings had a positive predictive value of 82% and negative predictive value of 78%. Sixty (34%) neonates had clinical hypoglycemia before MR imaging. Adjusting for 5-minute Apgar scores and umbilical artery pH with logistic regression, clinical hypoglycemia was associated with a 17.6-fold higher odds of MR imaging identification (P < .001). Selective posterior white matter and pulvinar edema were most predictive of clinical hypoglycemia, and no injury (36%) or a watershed (32%) pattern of injury was seen more often in severe hypoglycemia. In term infants with NE and hypoglycemia, specific imaging features for both hypoglycemia and hypoxia-ischemia can be identified.

Transvaginal ultrasonographic cervical measurement in predicting failed labor induction and cesarean delivery for failure to progress in nulliparous women.

PubMed

Park, Kyo Hoon

2007-08-01

The aim of this study was to evaluate the value of transvaginal sonographic cervical measurement in predicting failed labor induction and cesarean delivery for failure to progress in nulliparous women. One hundred and sixty-one women scheduled for labor induction underwent transvaginal ultrasonography and digital cervical examinations. Logistic regression demonstrated that cervical length and gestational age at induction, but not the Bishop score, significantly and independently predicted failed labor induction. According to the receiver operating characteristic curves analysis, the best cut-off value of cervical length for predicting failed labor induction was 28 mm, with a sensitivity of 62% and a specificity of 60%. In terms of the likelihood of a cesarean delivery for failure to progress as the outcome variable, logistic regression indicated that maternal height and birth weight, but not cervical length or Bishop score, were significantly and independently associated with an increased risk of cesarean delivery for failure to progress. Transvaginal sonographic measurements of cervical length thus independently predicted failed labor induction in nulliparous women. However, the relatively poor predictive performance of this test undermines its clinical usefulness as a predictor of failed labor induction. Moreover, cervical length appears to have a poor predictive value for the likelihood of a cesarean delivery for failure to progress.

The value of short-term pain relief in predicting the long-term outcome of 'indirect' cervical epidural steroid injections.

PubMed

Joswig, Holger; Neff, Armin; Ruppert, Christina; Hildebrandt, Gerhard; Stienen, Martin Nikolaus

2018-05-01

The predictive value of short-term arm pain relief after 'indirect' cervical epidural steroid injection (ESI) for the 1-month treatment response has been previously demonstrated. It remained to be answered whether the long-term response could be estimated by the early post-interventional pain course as well. Prospective observational study, following a cohort of n = 45 patients for a period of 24 months after 'indirect' ESI for radiculopathy secondary to a single-level cervical disk herniation (CDH). Arm and neck pain on the visual analog scale (VAS), health-related quality of life with the Short Form-12 (SF-12), and functional outcome with the Neck Pain and Disability (NPAD) Scale were assessed. Any additional invasive treatment after a single injection (second injection or surgery) defined treatment outcome as 'non-response'. At 24 months, n = 30 (66.7%) patients were responders and n = 15 (33.3%) were non-responders. Non-responders exited the follow-up at 1 month (n = 10), at 3 months (n = 4), and at 6 months (n = 1). No patients were injected again or operated on between the 6- and 24-month follow-up. Patients with favorable treatment response at 24 months had significantly lower VAS arm pain (p < 0.05) than non-responders at days 6, 8-11, and at the 3-month follow-up. The previously defined cut-off of > 50% short term pain reduction was not a reliable predictor of the 24-month responder status. SF-12 and NPAD scores were better among treatment responders in the long term. Patients who require a second injection or surgery after 'indirect' cervical ESI for a symptomatic CDH do so within the first 6 months. Short-term pain relief cannot reliably predict the long-term outcome.

Vasospasm on transcranial Doppler is predictive of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis.

PubMed

Kumar, Gyanendra; Shahripour, Reza Bavarsad; Harrigan, Mark R

2016-05-01

OBJECT The impact of transcranial Doppler (TCD) ultrasonography evidence of vasospasm on patient-centered clinical outcomes following aneurysmal subarachnoid hemorrhage (aSAH) is unknown. Vasospasm is known to lead to delayed cerebral ischemia (DCI) and poor outcomes. This systematic review and meta-analysis evaluates the predictive value of vasospasm on DCI, as diagnosed on TCD. METHODS MEDLINE, Scopus, the Cochrane trial register, and clinicaltrials.gov were searched through September 2014 using key words and the terms "subarachnoid hemorrhage," "aneurysm," "aneurysmal," "cerebral vasospasm," "vasospasm," "transcranial Doppler," and "TCD." Sensitivities, specificities, and positive and negative predictive values were pooled by a DerSimonian and Laird random-effects model. RESULTS Seventeen studies (n = 2870 patients) met inclusion criteria. The amount of variance attributable to heterogeneity was significant (I(2) > 50%) for all syntheses. No studies reported the impact of TCD evidence of vasospasm on functional outcome or mortality. TCD evidence of vasospasm was found to be highly predictive of DCI. Pooled estimates for TCD diagnosis of vasospasm (for DCI) were sensitivity 90% (95% confidence interval [CI] 77%-96%), specificity 71% (95% CI 51%-84%), positive predictive value 57% (95% CI 38%-71%), and negative predictive value 92% (95% CI 83%-96%). CONCLUSIONS TCD evidence of vasospasm is predictive of DCI with high accuracy. Although high sensitivity and negative predictive value make TCD an ideal monitoring device, it is not a mandated standard of care in aSAH due to the paucity of evidence on clinically relevant outcomes, despite recommendation by national guidelines. High-quality randomized trials evaluating the impact of TCD monitoring on patient-centered and physician-relevant outcomes are needed.

Workshop on Planning and Learning in Multi- Agent Environments

DTIC Science & Technology

2014-12-31

needed for translating the physical aspects of an interaction (see Section 3.1) into the numeric utility values needed for game -theoretic...calculations. Furthermore, the game -theoretic techniques themselves will require significant enhancements. Game -theoretic solution concepts (e.g., Nash...robotics. Real-time strategy games may provide useful data for research on predictive models of ad- versaries, modeling long-term and short-term plans

Decisions in Motion: Decision Dynamics during Intertemporal Choice reflect Subjective Evaluation of Delayed Rewards

PubMed Central

O’Hora, Denis; Carey, Rachel; Kervick, Aoife; Crowley, David; Dabrowski, Maciej

2016-01-01

People tend to discount rewards or losses that occur in the future. Such delay discounting has been linked to many behavioral and health problems, since people choose smaller short-term gains over greater long-term gains. We investigated whether the effect of delays on the subjective value of rewards is expressed in how people move when they make choices. Over 600 patrons of the RISK LAB exhibition hosted by the Science Gallery DublinTM played a short computer game in which they used a computer mouse to choose between amounts of money at various delays. Typical discounting effects were observed and decision dynamics indicated that choosing smaller short-term rewards became easier (i.e., shorter response times, tighter trajectories, less vacillation) as the delays until later rewards increased. Based on a sequence of choices, subjective values of delayed outcomes were estimated and decision dynamics during initial choices predicted these values. Decision dynamics are affected by subjective values of available options and thus provide a means to estimate such values. PMID:26867497

Timing of birth: Parsimony favors strategic over dysregulated parturition.

PubMed

Catalano, Ralph; Goodman, Julia; Margerison-Zilko, Claire; Falconi, April; Gemmill, Alison; Karasek, Deborah; Anderson, Elizabeth

2016-01-01

The "dysregulated parturition" narrative posits that the human stress response includes a cascade of hormones that "dysregulates" and accelerates parturition but provides questionable utility as a guide to understand or prevent preterm birth. We offer and test a "strategic parturition" narrative that not only predicts the excess preterm births that dysregulated parturition predicts but also makes testable, sex-specific predictions of the effect of stressful environments on the timing of birth among term pregnancies. We use interrupted time-series modeling of cohorts conceived over 101 months to test for lengthening of early term male gestations in stressed population. We use an event widely reported to have stressed Americans and to have increased the incidence of low birth weight and fetal death across the country-the terrorist attacks of September 2001. We tested the hypothesis that the odds of male infants conceived in December 2000 (i.e., at term in September 2001) being born early as opposed to full term fell below the value expected from those conceived in the 50 prior and 50 following months. We found that term male gestations exposed to the terrorist attacks exhibited 4% lower likelihood of early, as opposed to full or late, term birth. Strategic parturition explains observed data for which the dysregulated parturition narrative offers no prediction-the timing of birth among gestations stressed at term. Our narrative may help explain why findings from studies examining associations between population- and/or individual-level stressors and preterm birth are generally mixed. © 2015 Wiley Periodicals, Inc.

Mate preferences do predict attraction and choices in the early stages of mate selection.

PubMed

Li, Norman P; Yong, Jose C; Tov, William; Sng, Oliver; Fletcher, Garth J O; Valentine, Katherine A; Jiang, Yun F; Balliet, Daniel

2013-11-01

Although mate preference research has firmly established that men value physical attractiveness more than women do and women value social status more than men do, recent speed-dating studies have indicated mixed evidence (at best) for whether people's sex-differentiated mate preferences predict actual mate choices. According to an evolutionary, mate preference priority model (Li, Bailey, Kenrick, & Linsenmeier, 2002; Li & Kenrick, 2006; Li, Valentine, & Patel, 2011), the sexes are largely similar in what they ideally like, but for long-term mates, they should differ on what they most want to avoid in early selection contexts. Following this model, we conducted experiments using online messaging and modified speed-dating platforms. Results indicate that when a mating pool includes people at the low end of social status and physical attractiveness, mate choice criteria are sex-differentiated: Men, more than women, chose mates based on physical attractiveness, whereas women, more than men, chose mates based on social status. In addition, individuals who more greatly valued social status or physical attractiveness on paper valued these traits more in their actual choices. In particular, mate choices were sex-differentiated when considering long-term relationships but not short-term ones, where both sexes shunned partners with low physical attractiveness. The findings validate a large body of mate preferences research and an evolutionary perspective on mating, and they have implications for research using speed-dating and other interactive contexts. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Early disturbances in multimodal evoked potentials as a prognostic factor for long-term disability in relapsing-remitting multiple sclerosis patients.

PubMed

London, Frédéric; El Sankari, Souraya; van Pesch, Vincent

2017-04-01

The aim of this study was to investigate whether early alterations in evoked potentials (EPs) have a prognostic value in relapsing-remitting multiple sclerosis (RRMS). We retrospectively selected 108 early MS patients with a neurological follow-up ranging from 5 to 15years, in whom multimodal EPs (visual, brainstem auditory, somatosensory and motor) were performed at diagnosis. A conventional ordinal score was used to quantify the observed abnormalities. The extent of change in the composite EP score was well correlated to the Expanded Disability Status Scale (EDSS) at ten years (Y 10 ) and up to 15years (Y 11-15 ) after disease onset. Analysis of the predictive value of the EP score showed an increased risk of disability progression at Y 10 and Y 11-15 of 60% (p<0.0001) and 73% (p<0.0001) respectively in patients with an EP score >4. Conversely, the risk of disability progression at Y 10 and Y 11-15 associated with a lower EP score (⩽4) was reduced to 16% and 20% respectively. Our data support the good predictive value for long-term disability progression of multimodal EPs performed early after disease onset in RRMS patients. This study, performed in a homogeneous RRMS cohort with long term follow-up, demonstrates the value of an early comprehensive neurophysiological assessment as a marker for future disability. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Reference Values for Spirometry Derived Using Lambda, Mu, Sigma (LMS) Method in Korean Adults: in Comparison with Previous References.

PubMed

Jo, Bum Seak; Myong, Jun Pyo; Rhee, Chin Kook; Yoon, Hyoung Kyu; Koo, Jung Wan; Kim, Hyoung Ryoul

2018-01-15

The present study aimed to update the prediction equations for spirometry and their lower limits of normal (LLN) by using the lambda, mu, sigma (LMS) method and to compare the outcomes with the values of previous spirometric reference equations. Spirometric data of 10,249 healthy non-smokers (8,776 females) were extracted from the fourth and fifth versions of the Korea National Health and Nutrition Examination Survey (KNHANES IV, 2007-2009; V, 2010-2012). Reference equations were derived using the LMS method which allows modeling skewness (lambda [L]), mean (mu [M]), and coefficient of variation (sigma [S]). The outcome equations were compared with previous reference values. Prediction equations were presented in the following form: predicted value = e{a + b × ln(height) + c × ln(age) + M - spline}. The new predicted values for spirometry and their LLN derived using the LMS method were shown to more accurately reflect transitions in pulmonary function in young adults than previous prediction equations derived using conventional regression analysis in 2013. There were partial discrepancies between the new reference values and the reference values from the Global Lung Function Initiative in 2012. The results should be interpreted with caution for young adults and elderly males, particularly in terms of the LLN for forced expiratory volume in one second/forced vital capacity in elderly males. Serial spirometry follow-up, together with correlations with other clinical findings, should be emphasized in evaluating the pulmonary function of individuals. Future studies are needed to improve the accuracy of reference data and to develop continuous reference values for spirometry across all ages. © 2018 The Korean Academy of Medical Sciences.

Association of midlife value priorities with health-related quality of life, frailty and mortality among older men: a 26-year follow-up of the Helsinki Businessmen Study (HBS).

PubMed

Urtamo, Annele; Kautiainen, Hannu; Pitkälä, Kaisu H; Strandberg, Timo E

2018-05-01

Personal values influence behavior and decision making, but their long-term associations with health-related quality of life (HRQoL), frailty, and mortality are less clear. We studied these associations from midlife to old age in a 26-year follow-up of the Helsinki Businessmen Study (HBS) cohort. In 1974, 1320 clinically healthy men (born 1919-1934) reported in a 12-item questionnaire their personal values. In 2000, a mailed questionnaire, including assessment of HRQoL with RAND-36 (SF-36) instrument, was sent to survivors, and 1025 men responded. In 2000, the presence of phenotypic frailty was assessed using modified Fried criteria including indicators of shrinking, physical weakness, exhaustion, and physical inactivity. Mortality through December 31, 2000 was verified from national registries. Using a factor analysis, the data of the 12-item questionnaire of personal values were loaded in 3 factors: valuing health ("Health"), enjoyable and varying life ("Enjoyment"), and comfort and work-oriented life ("Work-life-balance"). Adjusted for age, we found a significant positive association between valuing "Health" in midlife and RAND-36 domains of Physical functioning (p = .032) and Vitality (p = .005) in old age. "Health" also predicted less frailty (p = .008), and "Enjoyment" was associated with higher mortality (p = .017). Value priorities of men assessed in midlife had long-term associations with HRQoL and frailty in old age, and they may also predict mortality.

Evaluation of a method of estimating low-flow frequencies from base-flow measurements at Indiana streams

USGS Publications Warehouse

Wilson, John Thomas

2000-01-01

A mathematical technique of estimating low-flow frequencies from base-flow measurements was evaluated by using data for streams in Indiana. Low-flow frequencies at low- flow partial-record stations were estimated by relating base-flow measurements to concurrent daily flows at nearby streamflow-gaging stations (index stations) for which low-flowfrequency curves had been developed. A network of long-term streamflow-gaging stations in Indiana provided a sample of sites with observed low-flow frequencies. Observed values of 7-day, 10-year low flow and 7-day, 2-year low flow were compared to predicted values to evaluate the accuracy of the method. Five test cases were used to evaluate the method under a variety of conditions in which the location of the index station and its drainage area varied relative to the partial-record station. A total of 141 pairs of streamflow-gaging stations were used in the five test cases. Four of the test cases used one index station, the fifth test case used two index stations. The number of base-flow measurements was varied for each test case to see if the accuracy of the method was affected by the number of measurements used. The most accurate and least variable results were produced when two index stations on the same stream or tributaries of the partial-record station were used. All but one value of the predicted 7-day, 10-year low flow were within 15 percent of the values observed for the long-term continuous record, and all of the predicted values of the 7-day, 2-year lowflow were within 15 percent of the observed values. This apparent accuracy, to some extent, may be a result of the small sample set of 15. Of the four test cases that used one index station, the most accurate and least variable results were produced in the test case where the index station and partial-record station were on the same stream or on streams tributary to each other and where the index station had a larger drainage area than the partial-record station. In that test case, the method tended to over predict, based on the median relative error. In 23 of 28 test pairs, the predicted 7-day, 10-year low flow was within 15 percent of the observed value; in 26 of 28 test pairs, the predicted 7-day, 2-year low flow was within 15 percent of the observed value. When the index station and partial-record station were on the same stream or streams tributary to each other and the index station had a smaller drainage area than the partial-record station, the method tended to under predict the low-flow frequencies. Nineteen of 28 predicted values of the 7-day, 10-year low flow were within 15 percent of the observed values. Twenty-five of 28 predicted values of the 7-day, 2-year low flow were within 15 percent of the observed values. When the index station and the partial-record station were on different streams, the method tended to under predict regardless of whether the index station had a larger or smaller drainage area than that of the partial-record station. Also, the variability of the relative error of estimate was greatest for the test cases that used index stations and partial-record stations from different streams. This variability, in part, may be caused by using more streamflow-gaging stations with small low-flow frequencies in these test cases. A small difference in the predicted and observed values can equate to a large relative error when dealing with stations that have small low-flow frequencies. In the test cases that used one index station, the method tended to predict smaller low-flow frequencies as the number of base-flow measurements was reduced from 20 to 5. Overall, the average relative error of estimate and the variability of the predicted values increased as the number of base-flow measurements was reduced.

Use of early tumor shrinkage to predict long-term outcome in metastatic colorectal cancer treated with cetuximab.

PubMed

Piessevaux, Hubert; Buyse, Marc; Schlichting, Michael; Van Cutsem, Eric; Bokemeyer, Carsten; Heeger, Steffen; Tejpar, Sabine

2013-10-20

Early tumor shrinkage (ETS) is associated with long-term outcome in patients with chemorefractory metastatic colorectal cancer (mCRC) receiving cetuximab. This association was investigated in the first-line setting in the randomized CRYSTAL and OPUS mCRC trials, after controlling for KRAS tumor mutation status. Radiologic assessments at week 8 were used to calculate the relative change in the sum of the longest diameters of the target lesions. Time-dependent receiver operating characteristics provided Cτ-indices (time-dependent c-index). Cox regression models and subpopulation treatment effect pattern plot analysis investigated associations between ETS (radiologic tumor size decrease at week 8) and survival and progression-free survival (PFS). In both trials, in patients with KRAS wild-type mCRC, Cτ values for PFS and survival were higher (P < .001) in those receiving chemotherapy plus cetuximab versus chemotherapy alone, indicating a stronger predictive value of ETS for long-term outcome in these patients. In the CRYSTAL and OPUS trials, respectively, the cutoff value of ETS ≥ 20% (v < 20%) identified patients with KRAS wild-type mCRC receiving chemotherapy plus cetuximab with longer PFS (medians 14.1 v 7.3 months, hazard ratio [HR] = 0.32; P < .001, and medians 11.9 v 5.7 months, HR = 0.22; P < .001) and survival (medians 30.0 v 18.6 months, HR = 0.53; P < .001 and medians 26.0 v 15.7 months, HR = 0.43; P = .006). ETS was significantly associated with long-term outcome in patients with KRAS wild-type mCRC treated first-line with chemotherapy plus cetuximab. Validation in prospective trials is required to assess the value of this on-treatment marker in the clinical decision-making process.

From points to forecasts: Predicting invasive species habitat suitability in the near term

USGS Publications Warehouse

Holcombe, Tracy R.; Stohlgren, Thomas J.; Jarnevich, Catherine S.

2010-01-01

We used near-term climate scenarios for the continental United States, to model 12 invasive plants species. We created three potential habitat suitability models for each species using maximum entropy modeling: (1) current; (2) 2020; and (3) 2035. Area under the curve values for the models ranged from 0.92 to 0.70, with 10 of the 12 being above 0.83 suggesting strong and predictable species-environment matching. Change in area between the current potential habitat and 2035 ranged from a potential habitat loss of about 217,000 km2, to a potential habitat gain of about 133,000 km2.

Value of Excess Pressure Integral for Predicting 15-Year All-Cause and Cardiovascular Mortalities in End-Stage Renal Disease Patients.

PubMed

Huang, Jui-Tzu; Cheng, Hao-Min; Yu, Wen-Chung; Lin, Yao-Ping; Sung, Shih-Hsien; Wang, Jiun-Jr; Wu, Chung-Li; Chen, Chen-Huan

2017-11-29

The excess pressure integral (XSPI), derived from analysis of the arterial pressure curve, may be a significant predictor of cardiovascular events in high-risk patients. We comprehensively investigated the prognostic value of XSPI for predicting long-term mortality in end-stage renal disease patients undergoing regular hemodialysis. A total of 267 uremic patients (50.2% female; mean age 54.2±14.9 years) receiving regular hemodialysis for more than 6 months were enrolled. Cardiovascular parameters were obtained by echocardiography and applanation tonometry. Calibrated carotid arterial pressure waveforms were analyzed according to the wave-transmission and reservoir-wave theories. Multivariable Cox proportional hazard models were constructed to account for age, sex, diabetes mellitus, albumin, body mass index, and hemodialysis treatment adequacy. Incremental utility of the parameters to risk stratification was assessed by net reclassification improvement. During a median follow-up of 15.3 years, 124 deaths (46.4%) incurred. Baseline XSPI was significantly predictive of all-cause (hazard ratio per 1 SD 1.4, 95% confidence interval 1.15-1.70, P =0.0006) and cardiovascular mortalities (1.47, 1.18-1.84, P =0.0006) after accounting for the covariates. The addition of XSPI to the base prognostic model significantly improved prediction of both all-cause mortality (net reclassification improvement=0.1549, P =0.0012) and cardiovascular mortality (net reclassification improvement=0.1535, P =0.0033). XSPI was superior to carotid-pulse wave velocity, forward and backward wave amplitudes, and left ventricular ejection fraction in consideration of overall independent and incremental prognostics values. In end-stage renal disease patients undergoing regular hemodialysis, XSPI was significantly predictive of long-term mortality and demonstrated an incremental value to conventional prognostic factors. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Cortisol Secretion and Change in Sleep Problems in Early Childhood: Moderation by Maternal Overcontrol

PubMed Central

Kiel, Elizabeth J.; Hummel, Alexandra C.; Luebbe, Aaron M.

2015-01-01

Childhood sleep problems are prevalent and relate to a wide range of negative psychological outcomes. However, it remains unclear how biological processes, such as HPA activity, may predict sleep problems over time in childhood in the context of certain parenting environments. Fifty-one mothers and their 18–20 month-old toddlers participated in a short-term longitudinal study assessing how shared variance among morning levels, diurnal change, and nocturnal change in toddlers’ cortisol secretion predicted change in sleep problems in the context of maternal overprotection and critical control. A composite characterized by low variability in, and, to a lesser extent, high morning values of cortisol, predicted increasing sleep problems from age 2 to age 3 when mothers reported high critical control. Results suggest value in assessing shared variance among different indices of cortisol secretion patterns and the interaction between cortisol and the environment in predicting sleep problems in early childhood. PMID:25766262

Developing a predictive tropospheric ozone model for Tabriz

NASA Astrophysics Data System (ADS)

Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi

2013-04-01

Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.

Using multiscale texture and density features for near-term breast cancer risk analysis

PubMed Central

Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

2015-01-01

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

PubMed

Wardenaar, K J; van Loo, H M; Cai, T; Fava, M; Gruber, M J; Li, J; de Jonge, P; Nierenberg, A A; Petukhova, M V; Rose, S; Sampson, N A; Schoevers, R A; Wilcox, M A; Alonso, J; Bromet, E J; Bunting, B; Florescu, S E; Fukao, A; Gureje, O; Hu, C; Huang, Y Q; Karam, A N; Levinson, D; Medina Mora, M E; Posada-Villa, J; Scott, K M; Taib, N I; Viana, M C; Xavier, M; Zarkov, Z; Kessler, R C

2014-11-01

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

PubMed

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

Defining sarcopenia in terms of incident adverse outcomes.

PubMed

Woo, Jean; Leung, Jason; Morley, J E

2015-03-01

The objectives of this study were to compare the performance of different diagnoses of sarcopenia using European Working Group on Sarcopenia in Older People, International Working Group on Sarcopenia, and the US Foundation of National Institutes of Health (FNIH) criteria, and the screening tool SARC-F, against the Asian Working Group for Sarcopenia consensus panel definitions, in predicting physical limitation, slow walking speed, and repeated chair stand performance, days of hospital stay and mortality at follow up. Longitudinal study. Community survey in Hong Kong. Participants were 4000 men and women 65 years and older living in the community. Information from questionnaire regarding activities of daily living, physical functioning limitations, and constituent questions of SARC-F; body mass index (BMI), grip strength (GS), walking speed, and appendicular muscle mass (ASM). FNIH, consensus panel definitions, and the screening tool SARC-F all have similar AUC values in predicting incident physical limitation and physical performance measures at 4 years, walking speed at 7 years, days of hospital stay at 7 years, and mortality at 10 years. None of the definitions predicted increase in physical limitation at 4 years or mortality at 10 years in women, and none predicted all the adverse outcomes. The highest AUC values were observed for walking speed at 4 and 7 years. When applied to a Chinese elderly population, criteria used for diagnosis of sarcopenia derived from European, Asian, and international consensus panels, from US cutoff values defined from incident physical limitation, and the SARC-F screening tool, all have similar performance in predicting incident physical limitation and mortality. Copyright © 2015 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Application of Recursive Partitioning to Derive and Validate a Claims-Based Algorithm for Identifying Keratinocyte Carcinoma (Nonmelanoma Skin Cancer).

PubMed

Chan, An-Wen; Fung, Kinwah; Tran, Jennifer M; Kitchen, Jessica; Austin, Peter C; Weinstock, Martin A; Rochon, Paula A

2016-10-01

Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and health care costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers using diagnosis and procedural codes submitted for reimbursement purposes. To apply recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma with high sensitivity and specificity. Retrospective study using population-based administrative databases linked to 602 371 pathology episodes from a community laboratory for adults residing in Ontario, Canada, from January 1, 1992, to December 31, 2009. The final analysis was completed in January 2016. We used recursive partitioning (classification trees) to derive an algorithm based on health insurance claims. The performance of the derived algorithm was compared with 5 prespecified algorithms and validated using an independent academic hospital clinic data set of 2082 patients seen in May and June 2011. Sensitivity, specificity, positive predictive value, and negative predictive value using the histopathological diagnosis as the criterion standard. We aimed to achieve maximal specificity, while maintaining greater than 80% sensitivity. Among 602 371 pathology episodes, 131 562 (21.8%) had a diagnosis of keratinocyte carcinoma. Our final derived algorithm outperformed the 5 simple prespecified algorithms and performed well in both community and hospital data sets in terms of sensitivity (82.6% and 84.9%, respectively), specificity (93.0% and 99.0%, respectively), positive predictive value (76.7% and 69.2%, respectively), and negative predictive value (95.0% and 99.6%, respectively). Algorithm performance did not vary substantially during the 18-year period. This algorithm offers a reliable mechanism for ascertaining keratinocyte carcinoma for epidemiological research in the absence of cancer registry data. Our findings also demonstrate the value of recursive partitioning in deriving valid claims-based algorithms.

Predicting motor outcome at preschool age for infants tested at 7, 30, 60, and 90 days after term age using the Test of Infant Motor Performance.

PubMed

Kolobe, Thubi H A; Bulanda, Michelle; Susman, Louisa

2004-12-01

Accurate and diagnostic measures are central to early identification and intervention with infants who are at risk for developmental delays or disabilities. The purpose of this study was to examine (1) the ability of infants' Test of Infant Motor Performance (TIMP) scores at 7, 30, 60 and 90 days after term age to predict motor development at preschool age and (2) the contribution of the home environment and medical risk to the prediction. Sixty-one children from an original cohort of 90 infants who were assessed weekly with the TIMP, between 34 weeks gestational age and 4 months after term age, participated in this follow-up study. The Peabody Developmental Motor Scales, 2nd edition (PDMS-2), were administered to the children at the mean age of 57 months (SD=4.8 months). The quality and quantity of the home environment also were assessed at this age using the Early Childhood Home Observation for Measurement of the Environment (EC-HOME). Pearson product moment correlation coefficients, multiple regression, sensitivity and specificity, and positive and negative predictive values were used to assess the relationship among the TIMP, HOME, medical risk, and PDMS-2 scores. The correlation coefficients between the TIMP and PDMS-2 scores were statistically significant for all ages except at 7 days. The highest correlation coefficient was at 90 days (r=.69, P=.001). The TIMP scores at 30, 60, and 90 days after term; medical risk scores; and EC-HOME scores explained 24%, 23%, and 52% of the variance in the PDMS-2 scores, respectively. The TIMP score at 90 days after term was the most significant contributor to the prediction. The TIMP cutoff score of -0.5 standard deviation below the mean correctly classified 80%, 79%, and 87% of the children using a cutoff score of -2 standard deviations on the PDMS-2 at 30, 60, and 90 days, respectively. The results compare favorably with those of developmental tests administered to infants at 6 months of age or older. These findings underscore the need for age-specific test values and developmental surveillance of infants before making referrals.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Ventromedial prefrontal and anterior cingulate cortex adopt choice and default reference frames during sequential multialternative choice

PubMed Central

Boorman, Erie D; Rushworth, Matthew F; Behrens, Tim E

2013-01-01

Although damage to medial frontal cortex causes profound decision-making impairments, it has been difficult to pinpoint the relative contributions of key anatomical subdivisions. Here we use fMRI to examine the contributions of human ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (dACC) during sequential choices between multiple alternatives – two key features of choices made in ecological settings. By carefully constructing options whose current value at any given decision was dissociable from their longer-term value, we were able to examine choices in current and long-term frames of reference. We present evidence showing that activity at choice and feedback in vmPFC and dACC was tied to the current choice and the best long-term option, respectively. vmPFC, mid-cingulate, and PCC encoded the relative value between the chosen and next-best option at each sequential decision, whereas dACC encoded the relative value of adapting choices from the option with the highest value in the longer-term. Furthermore, at feedback we identify temporally dissociable effects that predict repetition of the current choice and adaptation away from the long-term best option in vmPFC and dACC, respectively. These functional dissociations at choice and feedback suggest that sequential choices are subject to competing cortical mechanisms. PMID:23392656

Definition of perspective scheme of organization of traffic using methods of forecasting and modeling

NASA Astrophysics Data System (ADS)

Vlasov, V. M.; Novikov, A. N.; Novikov, I. A.; Shevtsova, A. G.

2018-03-01

In the environment of highly developed urban agglomerations, one of the main problems arises - inability of the road network to reach a high level of motorization. The introduction of intelligent transport systems allows solving this problem, but the main issue in their implementation remains open: to what extent this or that method of improving the transport network will be effective and whether it is able to solve the problem of vehicle growth especially for the long-term period. The main goal of this work was the development of an approach to forecasting the increase in the intensity of traffic flow for a long-term period using the population and the level of motorization. The developed approach made it possible to determine the projected population and, taking into account the level of motorization, to determine the growth factor of the traffic flow intensity, which allows calculating the intensity value for a long-term period with high accuracy. The analysis of the main methods for predicting the characteristics of the transport stream is performed. The basic values and parameters necessary for their use are established. The analysis of the urban settlement is carried out and the level of motorization characteristic for the given locality is determined. A new approach to predicting the intensity of the traffic flow has been developed, which makes it possible to predict the change in the transport situation in the long term in high accuracy. Calculations of the magnitude of the intensity increase on the basis of the developed forecasting method are made and the errors in the data obtained are determined. The main recommendations on the use of the developed forecasting approach for the long-term functioning of the road network are formulated.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.

1989-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Assessing explicit error reporting in the narrative electronic medical record using keyword searching.

PubMed

Cao, Hui; Stetson, Peter; Hripcsak, George

2003-01-01

Many types of medical errors occur in and outside of hospitals, some of which have very serious consequences and increase cost. Identifying errors is a critical step for managing and preventing them. In this study, we assessed the explicit reporting of medical errors in the electronic record. We used five search terms "mistake," "error," "incorrect," "inadvertent," and "iatrogenic" to survey several sets of narrative reports including discharge summaries, sign-out notes, and outpatient notes from 1991 to 2000. We manually reviewed all the positive cases and identified them based on the reporting of physicians. We identified 222 explicitly reported medical errors. The positive predictive value varied with different keywords. In general, the positive predictive value for each keyword was low, ranging from 3.4 to 24.4%. Therapeutic-related errors were the most common reported errors and these reported therapeutic-related errors were mainly medication errors. Keyword searches combined with manual review indicated some medical errors that were reported in medical records. It had a low sensitivity and a moderate positive predictive value, which varied by search term. Physicians were most likely to record errors in the Hospital Course and History of Present Illness sections of discharge summaries. The reported errors in medical records covered a broad range and were related to several types of care providers as well as non-health care professionals.

Hemoglobin A1c can be helpful in predicting progression to diabetes after Whipple procedure.

PubMed

Hamilton, Lisa; Jeyarajah, D Rohan

2007-01-01

Normoglycemic patients undergoing pancreaticoduodenectomy (Whipple procedure) often inquire whether they will be diabetic postoperatively. There is limited information on this issue. We therefore looked at a more subtle measurement of long-term glycemic control, hemoglobin A1c (HgbA1c), as a prognostic tool in predicting progression to diabetes post Whipple. A retrospective review over a 6-year period of all patients undergoing Whipple procedures at a single institution was conducted. In all, 27 patients had no prior history of diabetes, complete follow-up, and measured preoperative HgbA1c values. Postoperative diabetes was defined as the need for oral hypoglycemic agents or insulin. These charts were analyzed for progression to diabetes after Whipple. Of the 27 patients, 10 were considered to have postoperative diabetes. The average preoperative HgbA1c value for these patients was 6.3+/-0.66. This was statistically different from the 17 patients without postoperative diabetes (average HgbA1c 5.2+/-0.39, p<0.001). The positive predictive value, negative predictive value, sensitivity, and specificity were 82%, 94%, 90%, and 88%, respectively. This study demonstrates that progression to diabetes is very unlikely after Whipple operation if the preoperative HgbA1c value is in the normal range. The apparent utility of HgbA1c in predicting postoperative diabetes in this small study suggests that this laboratory test may be very helpful in counseling patients for Whipple operation.

Short and Long-Term Outcomes After Surgical Procedures Lasting for More Than Six Hours.

PubMed

Cornellà, Natalia; Sancho, Joan; Sitges-Serra, Antonio

2017-08-23

Long-term all-cause mortality and dependency after complex surgical procedures have not been assessed in the framework of value-based medicine. The aim of this study was to investigate the postoperative and long-term outcomes after surgical procedures lasting for more than six hours. Retrospective cohort study of patients undergoing a first elective complex surgical procedure between 2004 and 2013. Heart and transplant surgery was excluded. Mortality and dependency from the healthcare system were selected as outcome variables. Gender, age, ASA, creatinine, albumin kinetics, complications, benign vs malignant underlying condition, number of drugs at discharge, and admission and length of stay in the ICU were recorded as predictive variables. Some 620 adult patients were included in the study. Postoperative, <1year and <5years cumulative mortality was 6.8%, 17.6% and 45%, respectively. Of patients discharged from hospital after surgery, 76% remained dependent on the healthcare system. In multivariate analysis for postoperative, <1year and <5years mortality, postoperative albumin concentration, ASA score and an ICU stay >7days, were the most significant independent predictive variables. Prolonged surgery carries a significant short and long-term mortality and disability. These data may contribute to more informed decisions taken concerning major surgery in the framework of value-based medicine.

Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

2018-03-01

The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation

PubMed Central

Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J.; Moore, Kenneth J.; Thorburn, Peter; Archontoulis, Sotirios V.

2016-01-01

Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability. PMID:27891133

Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

PubMed

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

2016-01-01

Improved prediction of optimal N fertilizer rates for corn ( Zea mays L. ) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean ( Glycine max L. ) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha -1 ) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha -1 ). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability.

Runoff as a factor in USLE/RUSLE technology

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2014-05-01

Modelling erosion for prediction purposes started with the development of the Universal Soil Loss Equation the focus of which was the prediction of long term (~20) average annul soil loss from field sized areas. That purpose has been maintained in the subsequent revision RUSLE, the most widely used erosion prediction model in the world. The lack of ability to predict short term soil loss saw the development of so-called process based models like WEPP and EUROSEM which focussed on predicting event erosion but failed to improve the prediction of long term erosion where the RUSLE worked well. One of the features of erosion recognised in the so-called process based modes is the fact that runoff is a primary factor in rainfall erosion and some modifications of USLE/RUSLE model have been proposed have included runoff as in independent factor in determining event erosivity. However, these models have ignored fundamental mathematical rules. The USLE-M which replaces the EI30 index by the product of the runoff ratio and EI30 was developed from the concept that soil loss is the product of runoff and sediment concentration and operates in a way that obeys the mathematical rules upon which the USLE/RUSLE model was based. In accounts for event soil loss better that the EI30 index where runoff values are known or predicted adequately. RUSLE2 now includes a capacity to model runoff driven erosion.

Prediction of daily sea surface temperature using efficient neural networks

NASA Astrophysics Data System (ADS)

Patil, Kalpesh; Deo, Makaranad Chintamani

2017-04-01

Short-term prediction of sea surface temperature (SST) is commonly achieved through numerical models. Numerical approaches are more suitable for use over a large spatial domain than in a specific site because of the difficulties involved in resolving various physical sub-processes at local levels. Therefore, for a given location, a data-driven approach such as neural networks may provide a better alternative. The application of neural networks, however, needs a large experimentation in their architecture, training methods, and formation of appropriate input-output pairs. A network trained in this manner can provide more attractive results if the advances in network architecture are additionally considered. With this in mind, we propose the use of wavelet neural networks (WNNs) for prediction of daily SST values. The prediction of daily SST values was carried out using WNN over 5 days into the future at six different locations in the Indian Ocean. First, the accuracy of site-specific SST values predicted by a numerical model, ROMS, was assessed against the in situ records. The result pointed out the necessity for alternative approaches. First, traditional networks were tried and after noticing their poor performance, WNN was used. This approach produced attractive forecasts when judged through various error statistics. When all locations were viewed together, the mean absolute error was within 0.18 to 0.32 °C for a 5-day-ahead forecast. The WNN approach was thus found to add value to the numerical method of SST prediction when location-specific information is desired.

Prognostic value of computed tomographic coronary angiography and exercise electrocardiography for cardiovascular events

PubMed Central

Kim, Kye-Hwan; Jeon, Kyung Nyeo; Kang, Min Gyu; Ahn, Jong Hwa; Koh, Jin-Sin; Park, Yongwhi; Hwang, Seok-Jae; Jeong, Young-Hoon; Kwak, Choong Hwan; Hwang, Jin-Yong; Park, Jeong Rang

2016-01-01

Background/Aims: This study is a head-to-head comparison of predictive values for long-term cardiovascular outcomes between exercise electrocardiography (ex-ECG) and computed tomography coronary angiography (CTCA) in patients with chest pain. Methods: Four hundred and forty-two patients (mean age, 56.1 years; men, 61.3%) who underwent both ex-ECG and CTCA for evaluation of chest pain were included. For ex-ECG parameters, the patients were classified according to negative or positive results, and Duke treadmill score (DTS). Coronary artery calcium score (CACS), presence of plaque, and coronary artery stenosis were evaluated as CTCA parameters. Cardiovascular events for prognostic evaluation were defined as unstable angina, acute myocardial infarction, revascularization, heart failure, and cardiac death. Results: The mean follow-up duration was 2.8 ± 1.1 years. Fifteen patients experienced cardiovascular events. Based on pretest probability, the low- and intermediate-risks of coronary artery disease were 94.6%. Odds ratio of CACS > 40, presence of plaque, coronary stenosis ≥ 50% and DTS ≤ 4 were significant (3.79, p = 0.012; 9.54, p = 0.030; 6.99, p < 0.001; and 4.58, p = 0.008, respectively). In the Cox regression model, coronary stenosis ≥ 50% (hazard ratio, 7.426; 95% confidence interval, 2.685 to 20.525) was only significant. After adding DTS ≤ 4 to coronary stenosis ≥ 50%, the integrated discrimination improvement and net reclassification improvement analyses did not show significant. Conclusions: CTCA was better than ex-ECG in terms of predicting long-term outcomes in low- to intermediate-risk populations. The predictive value of the combination of CTCA and ex-ECG was not superior to that of CTCA alone. PMID:27017387

Using instrumental (CIE and reflectance) measures to predict consumers' acceptance of beef colour.

PubMed

Holman, Benjamin W B; van de Ven, Remy J; Mao, Yanwei; Coombs, Cassius E O; Hopkins, David L

2017-05-01

We aimed to establish colorimetric thresholds based upon the capacity for instrumental measures to predict consumer satisfaction with beef colour. A web-based survey was used to distribute standardised photographs of beef M. longissimus lumborum with known colorimetrics (L*, a*, b*, hue, chroma, ratio of reflectance at 630nm and 580nm, and estimated deoxymyoglobin, oxymyoglobin and metmyoglobin concentrations) for scrutiny. Consumer demographics and perceived importance of colour to beef value were also evaluated. It was found that a* provided the most simple and robust prediction of beef colour acceptability. Beef colour was considered acceptable (with 95% acceptance) when a* values were equal to or above 14.5. Demographic effects on this threshold were negligible, but consumer nationality and gender did contribute to variation in the relative importance of colour to beef value. These results provide future beef colour studies with context to interpret objective colour measures in terms of consumer acceptance and market appeal. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Subsonic Longitudinal Performance Coefficient Extraction from Shuttle Flight Data: an Accuracy Assessment for Determination of Data Base Updates

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Kelly, G. M.; Mcconnell, J. G.; Compton, H. R.

1983-01-01

Longitudinal performance comparisons between flight derived and predicted values are presented for the first five NASA Space Shuttle Columbia flights. Though subsonic comparisons are emphasized, comparisons during the transonic and low supersonic regions of flight are included. Computed air data information based on the remotely sensed atmospheric measurements as well as in situ Orbiter Air Data System (ADS) measurements were incorporated. Each air data source provides for comparisons versus the predicted values from the LaRC data base. Principally, L/D, C sub L, and C sub D, comparisons are presented, though some pitching moment results are included. Similarities in flight conditions and spacecraft configuration during the first five flights are discussed. Contributions from the various elements of the data base are presented and the overall differences observed between the flight and predicted values are discussed in terms of expected variations. A discussion on potential data base updates is presented based on the results from the five flights to date.

Reagent strip testing is not sensitive for the screening of asymptomatic bacteriuria in pregnant women.

PubMed

Lumbiganon, Pisake; Chongsomchai, Chompilas; Chumworathayee, Bundit; Thinkhamrop, Jadsada

2002-08-01

The objective of the study was to assess the diagnostic performance of the reagent strip in screening for asymptomatic bacteriuria in pregnant women using urine culture as a gold standard. This study comprised 204 asymptomatic pregnant women who attended their first antenatal care at Srinagarind Hospital, Khon Kaen University from April 1, 1999 to June 30, 1999. Women with symptoms of urinary tract infection, antibiotic treatment within the previous 7 days, pregnancy-induced hypertension, bleeding per vagina and history of urinary tract diseases were excluded. Urine specimens were collected by clean catched midstream urine technique for urinalysis, reagent strip test and urine culture. Diagnostic performance of reagent strip in terms of sensitivity, specificity, positive and negative predictive value was analyzed. Urine reagent strip test had a sensitivity of 13.9 per cent, a specificity of 95.6 per cent, a positive predictive value of 46.1 per cent, a negative predictive value of 80.6 per cent in detecting asymptomatic bacteriuria in pregnant women.

A New Navigation Satellite Clock Bias Prediction Method Based on Modified Clock-bias Quadratic Polynomial Model

NASA Astrophysics Data System (ADS)

Wang, Y. P.; Lu, Z. P.; Sun, D. S.; Wang, N.

2016-01-01

In order to better express the characteristics of satellite clock bias (SCB) and improve SCB prediction precision, this paper proposed a new SCB prediction model which can take physical characteristics of space-borne atomic clock, the cyclic variation, and random part of SCB into consideration. First, the new model employs a quadratic polynomial model with periodic items to fit and extract the trend term and cyclic term of SCB; then based on the characteristics of fitting residuals, a time series ARIMA ~(Auto-Regressive Integrated Moving Average) model is used to model the residuals; eventually, the results from the two models are combined to obtain final SCB prediction values. At last, this paper uses precise SCB data from IGS (International GNSS Service) to conduct prediction tests, and the results show that the proposed model is effective and has better prediction performance compared with the quadratic polynomial model, grey model, and ARIMA model. In addition, the new method can also overcome the insufficiency of the ARIMA model in model recognition and order determination.

Motor Testing at 1 Year Improves the Prediction of Motor and Mental Outcome at 2 Years after Perinatal Hypoxic-Ischaemic Encephalopathy

ERIC Educational Resources Information Center

van Schie, Petra Em; Becher, Jules G.; Dallmeijer, Annet J.; Barkhof, Frederik; van Weissenbruch, Mirjam M.; Vermeulen, R. Jeroen

2010-01-01

Aim: To investigate the predictive value of motor testing at 1 year for motor and mental outcome at 2 years after perinatal hypoxic-ischaemic encephalopathy (HIE) in term neonates. Method: Motor and mental outcome at 2 years was assessed with the Bayley Scales of Infant Development, 2nd edition (BSID-II) in 32 surviving children (20 males, 12…

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

NASA Astrophysics Data System (ADS)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

The influence of speed abilities and technical skills in early adolescence on adult success in soccer: A long-term prospective analysis using ANOVA and SEM approaches

PubMed Central

2017-01-01

Several talent development programs in youth soccer have implemented motor diagnostics measuring performance factors. However, the predictive value of such tests for adult success is a controversial topic in talent research. This prospective cohort study evaluated the long-term predictive value of 1) motor tests and 2) players’ speed abilities (SA) and technical skills (TS) in early adolescence. The sample consisted of 14,178 U12 players from the German talent development program. Five tests (sprint, agility, dribbling, ball control, shooting) were conducted and players’ height, weight as well as relative age were assessed at nationwide diagnostics between 2004 and 2006. In the 2014/15 season, the players were then categorized as professional (n = 89), semi-professional (n = 913), or non-professional players (n = 13,176), indicating their adult performance level (APL). The motor tests’ prognostic relevance was determined using ANOVAs. Players’ future success was predicted by a logistic regression threshold model. This structural equation model comprised a measurement model with the motor tests and two correlated latent factors, SA and TS, with simultaneous consideration for the manifest covariates height, weight and relative age. Each motor predictor and anthropometric characteristic discriminated significantly between the APL (p < .001; η2 ≤ .02). The threshold model significantly predicted the APL (R2 = 24.8%), and in early adolescence the factor TS (p < .001) seems to have a stronger effect on adult performance than SA (p < .05). Both approaches (ANOVA, SEM) verified the diagnostics’ predictive validity over a long-term period (≈ 9 years). However, because of the limited effect sizes, the motor tests’ prognostic relevance remains ambiguous. A challenge for future research lies in the integration of different (e.g., person-oriented or multilevel) multivariate approaches that expand beyond the “traditional” topic of single tests’ predictive validity and toward more theoretically founded issues. PMID:28806410

Analysis of the regional MiKlip decadal prediction system over Europe: skill, added value of regionalization, and ensemble size dependeny

NASA Astrophysics Data System (ADS)

Reyers, Mark; Moemken, Julia; Pinto, Joaquim; Feldmann, Hendrik; Kottmeier, Christoph; MiKlip Module-C Team

2017-04-01

Decadal climate predictions can provide a useful basis for decision making support systems for the public and private sectors. Several generations of decadal hindcasts and predictions have been generated throughout the German research program MiKlip. Together with the global climate predictions computed with MPI-ESM, the regional climate model (RCM) COSMO-CLM is used for regional downscaling by MiKlip Module-C. The RCMs provide climate information on spatial and temporal scales closer to the needs of potential users. In this study, two downscaled hindcast generations are analysed (named b0 and b1). The respective global generations are both initialized by nudging them towards different reanalysis anomaly fields. An ensemble of five starting years (1961, 1971, 1981, 1991, and 2001), each comprising ten ensemble members, is used for both generations in order to quantify the regional decadal prediction skill for precipitation and near-surface temperature and wind speed over Europe. All datasets (including hindcasts, observations, reanalysis, and historical MPI-ESM runs) are pre-processed in an analogue manner by (i) removing the long-term trend and (ii) re-gridding to a common grid. Our analysis shows that there is potential for skillful decadal predictions over Europe in the regional MiKlip ensemble, but the skill is not systematic and depends on the PRUDENCE region and the variable. Further, the differences between the two hindcast generations are mostly small. As we used detrended time series, the predictive skill found in our study can probably attributed to reasonable predictions of anomalies which are associated with the natural climate variability. In a sensitivity study, it is shown that the results may strongly change when the long-term trend is kept in the datasets, as here the skill of predicting the long-term trend (e.g. for temperature) also plays a major role. The regionalization of the global ensemble provides an added value for decadal predictions for some complex regions like the Mediterranean and Iberian Peninsula, while for other regions no systematic improvement is found. A clear dependence of the performance of the regional MiKlip system on the ensemble size is detected. For all variables in both hindcast generations, the skill increases when the ensemble is enlarged. The results indicate that a number of ten members is an appropriate ensemble size for decadal predictions over Europe.

LANDSAT 4 band 6 data evaluation

NASA Technical Reports Server (NTRS)

1983-01-01

Satellite data collected over Lake Ontario were processed to observed surface temperature values. This involved computing apparent radiance values for each point where surface temperatures were known from averaged digital count values. These radiance values were then converted by using the LOWTRAN 5A atmospheric propagation model. This model was modified by incorporating a spectral response function for the LANDSAT band 6 sensors. A downwelled radiance term derived from LOWTRAN was included to account for reflected sky radiance. A blackbody equivalent source radiance was computed. Measured temperatures were plotted against the predicted temperature. The RMS error between the data sets is 0.51K.

[Validation of the portuguese version of the Mini-Social Phobia Inventory (Mini-SPIN)].

PubMed

D'El Rey, Gustavo José Fonseca; Matos, Cláudia Wilmor

2009-01-01

Social phobia (also known as social anxiety disorder) is a severe mental disorder that brings distress and disability. The aim of this study was validate to the Portuguese language the Mini-Social Phobia Inventory (Mini-SPIN) in a populational sample. We performed a discriminative validity study of the Mini-SPIN in a sample of 644 subjects (Mini-SPIN positive group: n = 218 and control/negative group: n = 426) of a study of anxiety disorders' prevalence in the city of Santo André-SP. The Portuguese version of the Mini-SPIN (with score of 6 points, suggested in the original English version) demonstrated a sensitivity of 95.0%, specificity of 80.3%, positive predictive value of 52.8%, negative predictive value of 98.6% and incorrect classification rate of 16.9%. With score of 7 points, was observed an increase in the specificity and positive predictive value (88.6% and 62.7%), while the sensitivity and negative predictive value (84.8% and 96.2%) remained high. The Portuguese version of the Mini-SPIN showed satisfactory psychometric qualities in terms of discriminative validity. In this study, the cut-off of 7, was considered to be the most suitable to screening of the generalized social phobia.

Estimation of influential points in any data set from coefficient of determination and its leave-one-out cross-validated counterpart.

PubMed

Tóth, Gergely; Bodai, Zsolt; Héberger, Károly

2013-10-01

Coefficient of determination (R (2)) and its leave-one-out cross-validated analogue (denoted by Q (2) or R cv (2) ) are the most frequantly published values to characterize the predictive performance of models. In this article we use R (2) and Q (2) in a reversed aspect to determine uncommon points, i.e. influential points in any data sets. The term (1 - Q (2))/(1 - R (2)) corresponds to the ratio of predictive residual sum of squares and the residual sum of squares. The ratio correlates to the number of influential points in experimental and random data sets. We propose an (approximate) F test on (1 - Q (2))/(1 - R (2)) term to quickly pre-estimate the presence of influential points in training sets of models. The test is founded upon the routinely calculated Q (2) and R (2) values and warns the model builders to verify the training set, to perform influence analysis or even to change to robust modeling.

Continuous noninvasive monitoring in the neonatal ICU.

PubMed

Sahni, Rakesh

2017-04-01

Standard hemodynamic monitoring such as heart rate and systemic blood pressure may only provide a crude estimation of organ perfusion during neonatal intensive care. Pulse oximetry monitoring allows for continuous noninvasive monitoring of hemoglobin oxygenation and thus provides estimation of end-organ oxygenation. This review aims to provide an overview of pulse oximetry and discuss its current and potential clinical use during neonatal intensive care. Technological advances in continuous assessment of dynamic changes in systemic oxygenation with pulse oximetry during transition to extrauterine life and beyond provide additional details about physiological interactions among the key hemodynamic factors regulating systemic blood flow distribution along with the subtle changes that are frequently transient and undetectable with standard monitoring. Noninvasive real-time continuous systemic oxygen monitoring has the potential to serve as biomarkers for early-organ dysfunction, to predict adverse short-term and long-term outcomes in critically ill neonates, and to optimize outcomes. Further studies are needed to establish values predicting adverse outcomes and to validate targeted interventions to normalize abnormal values to improve outcomes.

Hepatic Venous Pressure Gradient Predicts Long-Term Mortality in Patients with Decompensated Cirrhosis

PubMed Central

Kim, Tae Yeob; Lee, Jae Gon; Kim, Ji Yeoun; Kim, Sun Min; Kim, Jinoo; Jeong, Woo Kyoung

2016-01-01

Purpose The present study aimed to investigate the role of hepatic venous pressure gradient (HVPG) for prediction of long-term mortality in patients with decompensated cirrhosis. Materials and Methods Clinical data from 97 non-critically-ill cirrhotic patients with HVPG measurements were retrospectively and consecutively collected between 2009 and 2012. Patients were classified according to clinical stages and presence of ascites. The prognostic accuracy of HVPG for death, survival curves, and hazard ratios were analyzed. Results During a median follow-up of 24 (interquartile range, 13-36) months, 22 patients (22.7%) died. The area under the receiver operating characteristics curves of HVPG for predicting 1-year, 2-year, and overall mortality were 0.801, 0.737, and 0.687, respectively (all p<0.01). The best cut-off value of HVPG for predicting long-term overall mortality in all patients was 17 mm Hg. The mortality rates at 1 and 2 years were 8.9% and 19.2%, respectively: 1.9% and 11.9% with HVPG ≤17 mm Hg and 16.2% and 29.4% with HVPG >17 mm Hg, respectively (p=0.015). In the ascites group, the mortality rates at 1 and 2 years were 3.9% and 17.6% with HVPG ≤17 mm Hg and 17.5% and 35.2% with HVPG >17 mm Hg, respectively (p=0.044). Regarding the risk factors for mortality, both HVPG and model for end-stage liver disease were positively related with long-term mortality in all patients. Particularly, for the patients with ascites, both prothrombin time and HVPG were independent risk factors for predicting poor outcomes. Conclusion HVPG is useful for predicting the long-term mortality in patients with decompensated cirrhosis, especially in the presence of ascites. PMID:26632394

The Value of Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio for Detecting Early-onset Neonatal Sepsis.

PubMed

Can, Emrah; Hamilcikan, Şahin; Can, Ceren

2018-05-01

The purpose of this study was to investigate the relationship between neonate early-onset sepsis (EOS) and the neutrophil to lymphocyte ratio (NLR) and the platelet to lymphocyte ratio (PLR) of term neonates. This prospective observational study was conducted with term neonates diagnosed with EOS compared with 44 healthy controls. Exclusion criteria were prematurity, postmaturity, small or large for gestational age according to week of pregnancy, preeclampsia, gestational diabetes mellitus, chorioamnionitis, congenital major anomalies, and cyanotic congenital heart disease. A total of 122 term neonates were included in the study. Of these, 78 were diagnosed with EOS and 44 were healthy controls. Tachycardia and apnea with bradycardia were the most common clinical signs of the onset of EOS in neonates in the EOS group. This group had significantly higher neutrophil counts, axillary temperatures, NLRs, PLRs, C-reactive proteins, and procalcitonin levels compared with the control group. There was a positive association between neutrophil counts, NLR, and PLR in the EOS group. An NLR of 6.76 was determined as the predictive cutoff value of neonate EOS (sensitivity 97.4%; specificity 100%; area under the receiver-operating characteristic curve 0.99; P=0.001). A PLR of 94.05 was determined as the predictive cutoff value of neonate EOS (sensitivity 97.4; specificity 100%; area under the receiver-operating characteristic curve 0.93; P=0.001). NLRs and PLRs were positively correlated with EOS in term neonates, and these ratios can be used as diagnostic adjunct tests for neonate EOS workups.

The influence of leader's spiritual values of servant leadership on employee motivational autonomy and eudaemonic well-being.

PubMed

Chen, Chin-Yi; Chen, Chun-Hsi Vivian; Li, Chun-I

2013-06-01

This research examined the role of leader's spiritual values in terms of the "servant leadership" in the process of promoting employee's autonomous motivation and eudaemonic well-being. Sample consists of 265 Chinese supervisor-subordinate dyads recruited from a variety of industries in Taiwan. Spiritual values perceived by the subordinates, as well as the discrepancy between leader-subordinate perceptions, but not the leader's self-perceptions of spiritual values, were found to contribute significantly beyond transactional leadership in predicting subordinate motivational autonomy and eudaemonic well-being, and subordinate autonomous motivations fully mediates the relationship between spiritual values and eudaemonic well-being.

Predictors of work status and quality of life 9-13 years after aneurysmal subarachnoid hemorrahage.

PubMed

Vilkki, Juhani; Juvela, Seppo; Malmivaara, Kirsi; Siironen, Jari; Hernesniemi, Juha

2012-08-01

Aneurysmal subarachnoid hemorrhage (SAH) causes long-term psychosocial impairments even in patients who regain functional independence. Little is known about predictors of these impairments. We studied how early clinical data and neuropsychological results predict work status and health-related quality of life (HRQoL) 9-13 years after SAH. One hundred one patients performed a neuropsychological test battery and returned their self-rating and partner's rating of a psychosocial impairment questionnaire approximately 1 year after SAH. These data were analyzed for association to the patients' work status and self-rated HRQoL approximately 10 years later. Age inversely, lower levels of self-rated impairments, employment and higher levels of education at the first follow-up independently predicted employment at the long-term follow-up. Although most cognitive test results were significantly associated with employment status at the long-term follow-up, they were of limited additional value as predictors of work status. The best predictor combination for long-term high HRQoL was good performance in a face recognition test and lower levels of self-rated impairments at the first follow-up as well as male sex. Problems in usual activities at the long-term follow-up were predicted by poor results in the face recognition and in a word list-learning task. Questionnaire ratings of patients' psychosocial impairments 1 year after SAH give important information for the long-term prediction of their work status and HRQoL. In the long run, patients' unemployment becomes strongly associated with higher age, while their performance of usual activities can be predicted with learning and memory results.

The logistic score: a criterion for hypothermia after perinatal asphyxia?

PubMed

Wayenberg, Jean-Louis

2010-05-01

To identify during the first hour of life the asphyxiated term neonates who further develop moderate or severe neonatal encephalopathy. In 75 asphyxiated term infants, we measured postnatal arterial base deficit (BD30), assigned an early neurological score (ENS) according to their level of consciousness, respiration pattern and neonatal reflexes at 30 min of life and calculated the logistic score (LS) = (0.33 x BD30) - ENS. The receiver operating characteristics (ROC) methodology was applied to analyze the ability of the LS to correctly classify patients into two groups: normal or mild encephalopathy (60 patients) versus moderate or severe encephalopathy (15 patients). The area under the ROC curve of the LS for moderate or severe encephalopathy (+/- standard error) was 94.4 +/- 3.6%. At the threshold value of 1.2, the LS provided 87.5% sensitivity and 73.7% positive predictive value (PPV). The PPV of LS reaches 100% for a value >3.2, but this threshold allowed only 53.3% sensitivity. The LS is predictive of the neonatal neurological evolution after birth asphyxia and may help to select the high risk patients who are potential candidates for hypothermia therapy.

Predictive and concurrent validity of the Braden scale in long-term care: a meta-analysis.

PubMed

Wilchesky, Machelle; Lungu, Ovidiu

2015-01-01

Pressure ulcer prevention is an important long-term care (LTC) quality indicator. While the Braden Scale is a recommended risk assessment tool, there is a paucity of information specifically pertaining to its validity within the LTC setting. We, therefore, undertook a systematic review and meta-analysis comparing Braden Scale predictive and concurrent validity within this context. We searched the Medline, EMBASE, PsychINFO and PubMed databases from 1985-2014 for studies containing the requisite information to analyze tool validity. Our initial search yielded 3,773 articles. Eleven datasets emanating from nine published studies describing 40,361 residents met all meta-analysis inclusion criteria and were analyzed using random effects models. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive values were 86%, 38%, 28%, and 93%, respectively. Specificity was poorer in concurrent samples as compared with predictive samples (38% vs. 72%), while PPV was low in both sample types (25 and 37%). Though random effects model results showed that the Scale had good overall predictive ability [RR, 4.33; 95% CI, 3.28-5.72], none of the concurrent samples were found to have "optimal" sensitivity and specificity. In conclusion, the appropriateness of the Braden Scale in LTC is questionable given its low specificity and PPV, in particular in concurrent validity studies. Future studies should further explore the extent to which the apparent low validity of the Scale in LTC is due to the choice of cutoff point and/or preventive strategies implemented by LTC staff as a matter of course. © 2015 by the Wound Healing Society.

The essential value of long-term experimental data for hydrology and water management

NASA Astrophysics Data System (ADS)

Tetzlaff, D.; Carey, S. K.; McNamara, J. P.; Laudon, H.; Soulsby, C.

2017-12-01

Observations and data from long-term experimental watersheds are the foundation of hydrology as a geoscience. They allow us to benchmark process understanding, observe trends and natural cycles, and are pre-requisites for testing predictive models. Long-term experimental watersheds also are places where new measurement technologies are developed. These studies offer a crucial evidence base for understanding and managing the provision of clean water supplies; predicting and mitigating the effects of floods, and protecting ecosystem services provided by rivers and wetlands. They also show how to manage land and water in an integrated, sustainable way that reduces environmental and economic costs. We present a number of compelling examples illustrating how hydrologic process understanding has been generated through comparing hypotheses to data, and how this understanding has been essential for managing water supplies, floods, and ecosystem services today.

Comparison between presepsin and procalcitonin in early diagnosis of neonatal sepsis.

PubMed

Iskandar, Agustin; Arthamin, Maimun Z; Indriana, Kristin; Anshory, Muhammad; Hur, Mina; Di Somma, Salvatore

2018-05-09

Neonatal sepsis remains worldwide one of the leading causes of morbidity and mortality in both term and preterm infants. Lower mortality rates are related to timely diagnostic evaluation and prompt initiation of empiric antibiotic therapy. Blood culture, as gold standard examination for sepsis, has several limitations for early diagnosis, so that sepsis biomarkers could play an important role in this regard. This study was aimed to compare the value of the two biomarkers presepsin and procalcitonin in early diagnosis of neonatal sepsis. This was a prospective cross-sectional study performed, in Saiful Anwar General Hospital Malang, Indonesia, in 51 neonates that fulfill the criteria of systemic inflammatory response syndrome (SIRS) with blood culture as diagnostic gold standard for sepsis. At reviewer operating characteristic (ROC) curve analyses, using a presepsin cutoff of 706,5 pg/mL, the obtained area under the curve (AUCs) were: sensitivity = 85.7%, specificity = 68.8%, positive predictive value = 85.7%, negative predictive value = 68.8%, positive likelihood ratio = 2.75, negative likelihood ratio = 0.21, and accuracy = 80.4%. On the other hand, with a procalcitonin cutoff value of 161.33 pg/mL the obtained AUCs showed: sensitivity = 68.6%, specificity = 62.5%, positive predictive value = 80%, negative predictive value = 47.6%, positive likelihood ratio = 1.83, the odds ratio negative = 0.5, and accuracy = 66.7%. In early diagnosis of neonatal sepsis, compared with procalcitonin, presepsin seems to provide better early diagnostic value with consequent possible faster therapeutical decision making and possible positive impact on outcome of neonates.

Predicting structured metadata from unstructured metadata.

PubMed

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data-defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. © The Author(s) 2016. Published by Oxford University Press.

Predicting structured metadata from unstructured metadata

PubMed Central

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data—defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. Database URL: http://www.yeastgenome.org/ PMID:28637268

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

NASA Astrophysics Data System (ADS)

Thangsunan, Patcharapong; Kittiwachana, Sila; Meepowpan, Puttinan; Kungwan, Nawee; Prangkio, Panchika; Hannongbua, Supa; Suree, Nuttee

2016-06-01

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Can administrative health utilisation data provide an accurate diabetes prevalence estimate for a geographical region?

PubMed

Chan, Wing Cheuk; Papaconstantinou, Dean; Lee, Mildred; Telfer, Kendra; Jo, Emmanuel; Drury, Paul L; Tobias, Martin

2018-05-01

To validate the New Zealand Ministry of Health (MoH) Virtual Diabetes Register (VDR) using longitudinal laboratory results and to develop an improved algorithm for estimating diabetes prevalence at a population level. The assigned diabetes status of individuals based on the 2014 version of the MoH VDR is compared to the diabetes status based on the laboratory results stored in the Auckland regional laboratory result repository (TestSafe) using the New Zealand diabetes diagnostic criteria. The existing VDR algorithm is refined by reviewing the sensitivity and positive predictive value of the each of the VDR algorithm rules individually and as a combination. The diabetes prevalence estimate based on the original 2014 MoH VDR was 17% higher (n = 108,505) than the corresponding TestSafe prevalence estimate (n = 92,707). Compared to the diabetes prevalence based on TestSafe, the original VDR has a sensitivity of 89%, specificity of 96%, positive predictive value of 76% and negative predictive value of 98%. The modified VDR algorithm has improved the positive predictive value by 6.1% and the specificity by 1.4% with modest reductions in sensitivity of 2.2% and negative predictive value of 0.3%. At an aggregated level the overall diabetes prevalence estimated by the modified VDR is 5.7% higher than the corresponding estimate based on TestSafe. The Ministry of Health Virtual Diabetes Register algorithm has been refined to provide a more accurate diabetes prevalence estimate at a population level. The comparison highlights the potential value of a national population long term condition register constructed from both laboratory results and administrative data. Copyright © 2018 Elsevier B.V. All rights reserved.

Fluid manifold design for a solar energy storage tank

NASA Technical Reports Server (NTRS)

Humphries, W. R.; Hewitt, H. C.; Griggs, E. I.

1975-01-01

A design technique for a fluid manifold for use in a solar energy storage tank is given. This analytical treatment generalizes the fluid equations pertinent to manifold design, giving manifold pressures, velocities, and orifice pressure differentials in terms of appropriate fluid and manifold geometry parameters. Experimental results used to corroborate analytical predictions are presented. These data indicate that variations in discharge coefficients due to variations in orifices can cause deviations between analytical predictions and actual performance values.

Benchmarking the Fundamental Electronic Properties of small TiO 2 Nanoclusters by GW and Coupled Cluster Theory Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berardo, Enrico; Kaplan, Ferdinand; Bhaskaran-Nair, Kiran

We study the vertical ionisation potential, electron affinity, fundamental gap and exciton binding energy values of small bare and hydroxylated TiO 2 nanoclusters to understand how the excited state properties change as a function of size and hydroxylation. In addition, we have employed a range of many-body methods; including G 0 W 0, qs GW, EA/IP-EOM-CCSD and DFT (B3LYP, PBE), to compare the performance and predictions of the different classes of methods. We demonstrate that for bare (i.e. non-hydroxylated) clusters all many-body methods predict the same trend with cluster size. The highest occupied and lowest unoccupied DFT orbitals follow themore » same trends as the electron affinity and ionisation potentials predicted by the many-body methods but are generally far too shallow and deep respectively in absolute terms. In contrast, the ΔDFT method is found to yield values in the correct energy window. However, its predictions depend on the functional used and do not necessarily follow trends based on the many-body methods. The effect of hydroxylation of the clusters is to open up both the optical and fundamental gap. In conclusion, a simple microscopic explanation for the observed trends with cluster size and upon hydroxylation is proposed in terms of the Madelung onsite potential.« less

Application of Artificial Neural Network to Predict Colour Change, Shrinkage and Texture of Osmotically Dehydrated Pumpkin

NASA Astrophysics Data System (ADS)

Tang, S. Y.; Lee, J. S.; Loh, S. P.; Tham, H. J.

2017-06-01

The objectives of this study were to use Artificial Neural Network (ANN) to predict colour change, shrinkage and texture of osmotically dehydrated pumpkin slices. The effects of process variables such as concentration of osmotic solution, immersion temperature and immersion time on the above mentioned physical properties were studied. The colour of the samples was measured using a colorimeter and the net colour difference changes, ΔE were determined. The texture was measured in terms of hardness by using a Texture Analyzer. As for the shrinkage, displacement of volume method was applied and percentage of shrinkage was obtained in terms of volume changes. A feed-forward backpropagation network with sigmoidal function was developed and best network configuration was chosen based on the highest correlation coefficients between the experimental values versus predicted values. As a comparison, Response Surface Methodology (RSM) statistical analysis was also employed. The performances of both RSM and ANN modelling were evaluated based on absolute average deviation (AAD), correlation of determination (R2) and root mean square error (RMSE). The results showed that ANN has higher prediction capability as compared to RSM. The relative importance of the variables on the physical properties were also determined by using connection weight approach in ANN. It was found that solution concentration showed the highest influence on all three physical properties.

Benchmarking the Fundamental Electronic Properties of small TiO 2 Nanoclusters by GW and Coupled Cluster Theory Calculations

DOE PAGES

Berardo, Enrico; Kaplan, Ferdinand; Bhaskaran-Nair, Kiran; ...

2017-06-19

We study the vertical ionisation potential, electron affinity, fundamental gap and exciton binding energy values of small bare and hydroxylated TiO 2 nanoclusters to understand how the excited state properties change as a function of size and hydroxylation. In addition, we have employed a range of many-body methods; including G 0 W 0, qs GW, EA/IP-EOM-CCSD and DFT (B3LYP, PBE), to compare the performance and predictions of the different classes of methods. We demonstrate that for bare (i.e. non-hydroxylated) clusters all many-body methods predict the same trend with cluster size. The highest occupied and lowest unoccupied DFT orbitals follow themore » same trends as the electron affinity and ionisation potentials predicted by the many-body methods but are generally far too shallow and deep respectively in absolute terms. In contrast, the ΔDFT method is found to yield values in the correct energy window. However, its predictions depend on the functional used and do not necessarily follow trends based on the many-body methods. The effect of hydroxylation of the clusters is to open up both the optical and fundamental gap. In conclusion, a simple microscopic explanation for the observed trends with cluster size and upon hydroxylation is proposed in terms of the Madelung onsite potential.« less

Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review.

PubMed

Kim, Bum Jun; Kim, Jung Han; Kim, Hyeong Su; Zang, Dae Young

2017-02-21

The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: 'kidney or renal', 'carcinoma or cancer or neoplasm or malignancy', 'von Hippel-Lindau or VHL', 'alteration or mutation or methylation', and 'prognostic or predictive'. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC.

Model to predict hyperbilirubinemia in healthy term and near-term newborns with exclusive breast feeding.

PubMed

Huang, Hsin-Chung; Yang, Hwai-I; Chang, Yu-Hsun; Chang, Rui-Jane; Chen, Mei-Huei; Chen, Chien-Yi; Chou, Hung-Chieh; Hsieh, Wu-Shiun; Tsao, Po-Nien

2012-12-01

The aim of this study was to identify high-risk newborns who will subsequently develop significant hyperbilirubinemia Days 4 to 10 of life by using the clinical data from the first three days of life. We retrospectively collected exclusively breastfeeding healthy term and near-term newborns born in our nursery between May 1, 2002, to June 30, 2005. Clinical data, including serum bilirubin were collected and the significant predictors were identified. Bilirubin level ≥15mg/dL during Days 4 to 10 of life was defined as significant hyperbilirubinemia. A prediction model to predict subsequent hyperbilirubinemia was established. This model was externally validated in another group of newborns who were enrolled by the same criteria to test its discrimination capability. Totally, 1979 neonates were collected and 1208 cases were excluded by our exclusion criteria. Finally, 771 newborns were enrolled and 182 (23.6%) cases developed significant hyperbilirubinemia during Days 4 to 10 of life. In the logistic regression analysis, gestational age, maximal body weight loss percentage, and peak bilirubin level during the first 72 hours of life were significantly associated with subsequent hyperbilirubinemia. A prediction model was derived with the area under receiver operating characteristic (AUROC) curve of 0.788. Model validation in the separate study (N = 209) showed similar discrimination capability (AUROC = 0.8340). Gestational age, maximal body weight loss percentage, and peak serum bilirubin level during the first 3 days of life have highest predictive value of subsequent significant hyperbilirubinemia. We provide a good model to predict the risk of subsequent significant hyperbilirubinemia. Copyright © 2012. Published by Elsevier B.V.

Reconciling GRACE and GPS estimates of long-term load deformation in southern Greenland

NASA Astrophysics Data System (ADS)

Wang, Song-Yun; Chen, J. L.; Wilson, Clark R.; Li, Jin; Hu, Xiaogong

2018-02-01

We examine vertical load deformation at four continuous Global Positioning System (GPS) sites in southern Greenland relative to Gravity Recovery and Climate Experiment (GRACE) predictions of vertical deformation over the period 2002-2016. With limited spatial resolution, GRACE predictions require adjustment before they can be compared with GPS height time series. Without adjustment, both GRACE spherical harmonic (SH) and mascon solutions predict significant vertical displacement rate differences relative to GPS. We use a scaling factor method to adjust GRACE results, based on a long-term mass rate model derived from GRACE measurements, glacial geography, and ice flow data. Adjusted GRACE estimates show significantly improved agreement with GPS, both in terms of long-term rates and interannual variations. A deceleration of mass loss is observed in southern Greenland since early 2013. The success at reconciling GPS and GRACE observations with a more detailed mass rate model demonstrates the high sensitivity to load distribution in regions surrounding GPS stations. Conversely, the value of GPS observations in constraining mass changes in surrounding regions is also demonstrated. In addition, our results are consistent with recent estimates of GIA uplift (˜4.4 mm yr-1) at the KULU site.

Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species

PubMed Central

Thomas, Reuben; Thomas, Russell S.; Auerbach, Scott S.; Portier, Christopher J.

2013-01-01

Background Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. Objectives To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Methods Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Results Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Conclusions Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species. PMID:23737943

Biological networks for predicting chemical hepatocarcinogenicity using gene expression data from treated mice and relevance across human and rat species.

PubMed

Thomas, Reuben; Thomas, Russell S; Auerbach, Scott S; Portier, Christopher J

2013-01-01

Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species.

Differential Impact of Serial Measurement of Nonplatelet Thromboxane Generation on Long-Term Outcome After Cardiac Surgery.

PubMed

Kakouros, Nikolaos; Gluckman, Tyler J; Conte, John V; Kickler, Thomas S; Laws, Katherine; Barton, Bruce A; Rade, Jeffrey J

2017-11-02

Systemic thromboxane generation, not suppressible by standard aspirin therapy and likely arising from nonplatelet sources, increases the risk of atherothrombosis and death in patients with cardiovascular disease. In the RIGOR (Reduction in Graft Occlusion Rates) study, greater nonplatelet thromboxane generation occurred early compared with late after coronary artery bypass graft surgery, although only the latter correlated with graft failure. We hypothesize that a similar differential association exists between nonplatelet thromboxane generation and long-term clinical outcome. Five-year outcome data were analyzed for 290 RIGOR subjects taking aspirin with suppressed platelet thromboxane generation. Multivariable modeling was performed to define the relative predictive value of the urine thromboxane metabolite, 11-dehydrothromboxane B 2 (11-dhTXB 2 ), measured 3 days versus 6 months after surgery on the composite end point of death, myocardial infarction, revascularization or stroke, and death alone. 11-dhTXB 2 measured 3 days after surgery did not independently predict outcome, whereas 11-dhTXB 2 >450 pg/mg creatinine measured 6 months after surgery predicted the composite end point (adjusted hazard ratio, 1.79; P =0.02) and death (adjusted hazard ratio, 2.90; P =0.01) at 5 years compared with lower values. Additional modeling revealed 11-dhTXB 2 measured early after surgery associated with several markers of inflammation, in contrast to 11-dhTXB 2 measured 6 months later, which highly associated with oxidative stress. Long-term nonplatelet thromboxane generation after coronary artery bypass graft surgery is a novel risk factor for 5-year adverse outcome, including death. In contrast, nonplatelet thromboxane generation in the early postoperative period appears to be driven predominantly by inflammation and did not independently predict long-term clinical outcome. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Hybrid ARIMAX quantile regression method for forecasting short term electricity consumption in east java

NASA Astrophysics Data System (ADS)

Prastuti, M.; Suhartono; Salehah, NA

2018-04-01

The need for energy supply, especially for electricity in Indonesia has been increasing in the last past years. Furthermore, the high electricity usage by people at different times leads to the occurrence of heteroscedasticity issue. Estimate the electricity supply that could fulfilled the community’s need is very important, but the heteroscedasticity issue often made electricity forecasting hard to be done. An accurate forecast of electricity consumptions is one of the key challenges for energy provider to make better resources and service planning and also take control actions in order to balance the electricity supply and demand for community. In this paper, hybrid ARIMAX Quantile Regression (ARIMAX-QR) approach was proposed to predict the short-term electricity consumption in East Java. This method will also be compared to time series regression using RMSE, MAPE, and MdAPE criteria. The data used in this research was the electricity consumption per half-an-hour data during the period of September 2015 to April 2016. The results show that the proposed approach can be a competitive alternative to forecast short-term electricity in East Java. ARIMAX-QR using lag values and dummy variables as predictors yield more accurate prediction in both in-sample and out-sample data. Moreover, both time series regression and ARIMAX-QR methods with addition of lag values as predictor could capture accurately the patterns in the data. Hence, it produces better predictions compared to the models that not use additional lag variables.

The valuation of the EQ-5D in Portugal.

PubMed

Ferreira, Lara N; Ferreira, Pedro L; Pereira, Luis N; Oppe, Mark

2014-03-01

The EQ-5D is a preference-based measure widely used in cost-utility analysis (CUA). Several countries have conducted surveys to derive value sets, but this was not the case for Portugal. The purpose of this study was to estimate a value set for the EQ-5D for Portugal using the time trade-off (TTO). A representative sample of the Portuguese general population (n = 450) stratified by age and gender valued 24 health states. Face-to-face interviews were conducted by trained interviewers. Each respondent ranked and valued seven health states using the TTO. Several models were estimated at both the individual and aggregated levels to predict health state valuations. Alternative functional forms were considered to account for the skewed distribution of these valuations. The models were analyzed in terms of their coefficients, overall fit and the ability for predicting the TTO values. Random effects models were estimated using generalized least squares and were robust across model specification. The results are generally consistent with other value sets. This research provides the Portuguese EQ-5D value set based on the preferences of the Portuguese general population as measured by the TTO. This value set is recommended for use in CUA conducted in Portugal.

Analysis and Thermodynamic Prediction of Hydrogen Solution in Solid and Liquid Multicomponent Aluminum Alloys

NASA Astrophysics Data System (ADS)

Anyalebechi, P. N.

Reported experimentally determined values of hydrogen solubility in liquid and solid Al-H and Al-H-X (where X = Cu, Si, Zn, Mg, Li, Fe or Ti) systems have been critically reviewed and analyzed in terms of Wagner's interaction parameter. An attempt has been made to use Wagner's interaction parameter and statistic linear regression models derived from reported hydrogen solubility limits for binary aluminum alloys to predict the hydrogen solubility limits in liquid and solid (commercial) multicomponent aluminum alloys. Reasons for the observed poor agreement between the predicted and experimentally determined hydrogen solubility limits are discussed.

Revised and improved value of the QED tenth-order electron anomalous magnetic moment

NASA Astrophysics Data System (ADS)

Aoyama, Tatsumi; Kinoshita, Toichiro; Nio, Makiko

2018-02-01

In order to improve the theoretical prediction of the electron anomalous magnetic moment ae we have carried out a new numerical evaluation of the 389 integrals of Set V, which represent 6,354 Feynman vertex diagrams without lepton loops. During this work, we found that one of the integrals, called X 024 , was given a wrong value in the previous calculation due to an incorrect assignment of integration variables. The correction of this error causes a shift of -1.26 to the Set V contribution, and hence to the tenth-order universal (i.e., mass-independent) term A1(10 ). The previous evaluation of all other 388 integrals is free from errors and consistent with the new evaluation. Combining the new and the old (excluding X 024 ) calculations statistically, we obtain 7.606 (192 )(α /π )5 as the best estimate of the Set V contribution. Including the contribution of the diagrams with fermion loops, the improved tenth-order universal term becomes A1(10 )=6.675 (192 ) . Adding hadronic and electroweak contributions leads to the theoretical prediction ae(theory)=1 159 652 182.032 (720 )×10-12 . From this and the best measurement of ae, we obtain the inverse fine-structure constant α-1(ae)=137.035 999 1491 (331 ) . The theoretical prediction of the muon anomalous magnetic moment is also affected by the update of QED contribution and the new value of α , but the shift is much smaller than the theoretical uncertainty.

Enhancement of lung sounds based on empirical mode decomposition and Fourier transform algorithm.

PubMed

Mondal, Ashok; Banerjee, Poulami; Somkuwar, Ajay

2017-02-01

There is always heart sound (HS) signal interfering during the recording of lung sound (LS) signals. This obscures the features of LS signals and creates confusion on pathological states, if any, of the lungs. In this work, a new method is proposed for reduction of heart sound interference which is based on empirical mode decomposition (EMD) technique and prediction algorithm. In this approach, first the mixed signal is split into several components in terms of intrinsic mode functions (IMFs). Thereafter, HS-included segments are localized and removed from them. The missing values of the gap thus produced, is predicted by a new Fast Fourier Transform (FFT) based prediction algorithm and the time domain LS signal is reconstructed by taking an inverse FFT of the estimated missing values. The experiments have been conducted on simulated and recorded HS corrupted LS signals at three different flow rates and various SNR levels. The performance of the proposed method is evaluated by qualitative and quantitative analysis of the results. It is found that the proposed method is superior to the baseline method in terms of quantitative and qualitative measurement. The developed method gives better results compared to baseline method for different SNR levels. Our method gives cross correlation index (CCI) of 0.9488, signal to deviation ratio (SDR) of 9.8262, and normalized maximum amplitude error (NMAE) of 26.94 for 0 dB SNR value. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Curiosity and reward: Valence predicts choice and information prediction errors enhance learning.

PubMed

Marvin, Caroline B; Shohamy, Daphna

2016-03-01

Curiosity drives many of our daily pursuits and interactions; yet, we know surprisingly little about how it works. Here, we harness an idea implied in many conceptualizations of curiosity: that information has value in and of itself. Reframing curiosity as the motivation to obtain reward-where the reward is information-allows one to leverage major advances in theoretical and computational mechanisms of reward-motivated learning. We provide new evidence supporting 2 predictions that emerge from this framework. First, we find an asymmetric effect of positive versus negative information, with positive information enhancing both curiosity and long-term memory for information. Second, we find that it is not the absolute value of information that drives learning but, rather, the gap between the reward expected and reward received, an "information prediction error." These results support the idea that information functions as a reward, much like money or food, guiding choices and driving learning in systematic ways. (c) 2016 APA, all rights reserved).

Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

PubMed

Tabaton, Massimo; Odetti, Patrizio; Cammarata, Sergio; Borghi, Roberta; Monacelli, Fiammetta; Caltagirone, Carlo; Bossù, Paola; Buscema, Massimo; Grossi, Enzo

2010-01-01

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases were chosen from 195 aMCI subjects recruited by four Italian Alzheimer's disease units. The parameters of glucose metabolism disorder, female gender, and apolipoprotein E epsilon3/epsilon4 genotype were found to be the biological variables with high relevance for predicting the conversion of aMCI. The scores of attention and short term memory tests also were predictors. Surprisingly, the plasma concentration of amyloid-beta (42) had a low predictive value. The results support the utility of ANN analysis as a new tool in the interpretation of data from heterogeneous and distinct sources.

[Research of prevalence of schistosomiasis in Hunan province, 1984-2015].

PubMed

Li, F Y; Tan, H Z; Ren, G H; Jiang, Q; Wang, H L

2017-03-10

Objective: To analyze the prevalence of schistosomiasis in Hunan province, and provide scientific evidence for the control and elimination of schistosomiasis. Methods: The changes of infection rates of Schistosoma ( S .) japonicum among residents and cattle in Hunan from 1984 to 2015 were analyzed by using dynamic trend diagram; and the time regression model was used to fit the infection rates of S. japonicum , and predict the recent infection rate. Results: The overall infection rates of S. japonicum in Hunan from 1984 to 2015 showed downward trend (95.29% in residents and 95.16% in cattle). By using the linear regression model, the actual values of infection rates in residents and cattle were all in the 95% confidence intervals of the value predicted; and the prediction showed that the infection rates in the residents and cattle would continue to decrease from 2016 to 2020. Conclusion: The prevalence of schistosomiasis was in decline in Hunan. The regression model has a good effect in the short-term prediction of schistosomiasis prevalence.

The association between plasma big endothelin-1 levels at admission and long-term outcomes in patients with atrial fibrillation.

PubMed

Wu, Shuang; Yang, Yan-Min; Zhu, Jun; Ren, Jia-Meng; Wang, Juan; Zhang, Han; Shao, Xing-Hui

2018-05-01

The prognostic role of big endothelin-1 (ET-1) in atrial fibrillation (AF) is unclear. We aimed to assess its predictive value in patients with AF. A total of 716 AF patients were enrolled and divided into two groups based on the optimal cut-off value of big ET-1 in predicting all-cause mortality. The primary outcomes were all-cause mortality and major adverse events (MAEs). Cox regression analysis and net reclassification improvement (NRI) analysis were performed to assess the predictive value of big ET-1 on outcomes. With the optimal cut-off value of 0.55 pmol/L, 326 patients were classified into the high big ET-1 levels group. Cardiac dysfunction and left atrial dilation were factors related to high big ET-1 levels. During a median follow-up of 3 years, patients with big ET-1 ≥ 0.55 pmol/L had notably higher risk of all-cause death (44.8% vs. 11.5%, p < 0.001), MAEs (51.8% vs. 17.4%, p < 0.001), cardiovascular death, major bleeding, and tended to have higher thromboembolic risk. After adjusting for confounding factors, high big ET-1 level was an independent predictor of all-cause mortality (hazard ratio (HR) 2.11, 95% confidence interval (CI) 1.46-3.05; p < 0.001), MAEs (HR 2.05, 95% CI 1.50-2.80; p = 0.001), and cardiovascular death (HR 2.44, 95% CI 1.52-3.93; p < 0.001). NRI analysis showed that big ET-1 allowed a significant improvement of 0.32 in the accuracy of predicting the risk of both all-cause mortality and MAEs. Elevated big ET-1 levels is an independent predictor of long-term all-cause mortality, MAEs, and cardiovascular death in patients with AF. Copyright © 2018 Elsevier B.V. All rights reserved.

Neuropeptide Y2 Receptor (NPY2R) Expression in Saliva Predicts Feeding Immaturity in the Premature Neonate

PubMed Central

Maron, Jill L.; Johnson, Kirby L.; Dietz, Jessica A.; Chen, Minghua L.; Bianchi, Diana W.

2012-01-01

Background The current practice in newborn medicine is to subjectively assess when a premature infant is ready to feed by mouth. When the assessment is inaccurate, the resulting feeding morbidities may be significant, resulting in long-term health consequences and millions of health care dollars annually. We hypothesized that the developmental maturation of hypothalamic regulation of feeding behavior is a predictor of successful oral feeding in the premature infant. To test this hypothesis, we analyzed the gene expression of neuropeptide Y2 receptor (NPY2R), a known hypothalamic regulator of feeding behavior, in neonatal saliva to determine its role as a biomarker in predicting oral feeding success in the neonate. Methodology/Principal Findings Salivary samples (n = 116), were prospectively collected from 63 preterm and 13 term neonates (post-conceptual age (PCA) 26 4/7 to 41 4/7 weeks) from five predefined feeding stages. Expression of NPY2R in neonatal saliva was determined by multiplex RT-qPCR amplification. Expression results were retrospectively correlated with feeding status at time of sample collection. Statistical analysis revealed that expression of NPY2R had a 95% positive predictive value for feeding immaturity. NPY2R expression statistically significantly decreased with advancing PCA (Wilcoxon test p value<0.01), and was associated with feeding status (chi square p value  =  0.013). Conclusions/Significance Developmental maturation of hypothalamic regulation of feeding behavior is an essential component of oral feeding success in the newborn. NPY2R expression in neonatal saliva is predictive of an immature feeding pattern. It is a clinically relevant biomarker that may be monitored in saliva to improve clinical care and reduce significant feeding-associated morbidities that affect the premature neonate. PMID:22629465

Circulating tumor DNA evaluated by Next-Generation Sequencing is predictive of tumor response and prolonged clinical benefit with nivolumab in advanced non-small cell lung cancer.

PubMed

Giroux Leprieur, Etienne; Herbretau, Guillaume; Dumenil, Coraline; Julie, Catherine; Giraud, Violaine; Labrune, Sylvie; Dumoulin, Jennifer; Tisserand, Julie; Emile, Jean-François; Blons, Hélène; Chinet, Thierry

2018-01-01

Nivolumab is an anti-PD1 antibody, given in second-line or later treatment in advanced non-small cell lung cancer (NSCLC). The objective of this study was to describe the predictive value of circulating tumor DNA (ctDNA) on the efficacy of nivolumab in advanced NSCLC. We prospectively included all consecutive patients with advanced NSCLC treated with nivolumab in our Department between June 2015 and October 2016. Plasma samples were obtained before the first injection of nivolumab and at the first tumor evaluation with nivolumab. ctDNA was analyzed by Next-Generation Sequencing (NGS), and the predominant somatic mutation was followed for each patient and correlated with tumor response, clinical benefit (administration of nivolumab for more than 6 months), and progression-free survival (PFS). Of 23 patients, 15 had evaluable NGS results at both times of analysis. ctDNA concentration at the first tumor evaluation and ctDNA change correlated with tumor response, clinical benefit and PFS. ROC curve analyses showed good diagnostic performances for tumor response and clinical benefit, both for ctDNA concentration at the first tumor evaluation (tumor response: positive predictive value (PPV) at 100.0% and negative predictive value (NPV) at 71.0%; clinical benefit: PPV at 83.3% and NPV 77.8%) and the ctDNA change (tumor response: PPV 100.0% and NPV 62.5%; clinical benefit: PPV 100.0% and NPV 80.0%). Patients without ctDNA concentration increase >9% at 2 months had a long-term benefit of nivolumab. In conclusion, NGS analysis of ctDNA allows the early detection of tumor response and long-term clinical benefit with nivolumab in NSCLC.

A short-term ionospheric forecasting empirical regional model (IFERM) to predict the critical frequency of the F2 layer during moderate, disturbed, and very disturbed geomagnetic conditions over the European area

NASA Astrophysics Data System (ADS)

Pietrella, M.

2012-02-01

A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting procedures were developed by taking into account, hourly measurements of foF2, hourly quiet-time reference values of foF2 (foF2QT), and the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap, (ap(τ)), for each observatory. Under the assumption that the ionospheric disturbance index ln(foF2/foF2QT) is correlated to the integrated geomagnetic disturbance index ap(τ), a set of statistically significant regression coefficients were established for each observatory, over 12 months, over 24 h, and under 3 different ranges of geomagnetic activity. This data was then used as input to compute short-term ionospheric forecasting of foF2 at the 13 local stations under consideration. The empirical storm-time ionospheric correction model (STORM) was used to predict foF2 in two different ways: scaling both the hourly median prediction provided by IRI (STORM_foF2MED,IRI model), and the foF2QT values (STORM_foF2QT model) from each local station. The comparison between the performance of STORM_foF2MED,IRI, STORM_foF2QT, IFELM, and the foF2QT values, was made on the basis of root mean square deviation (r.m.s.) for a large number of periods characterized by moderate, disturbed, and very disturbed geomagnetic activity. The results showed that the 13 IFELM perform much better than STORM_foF2,sub>MED,IRI and STORM_foF2QT especially in the eastern part of the European area during the summer months (May, June, July, and August) and equinoctial months (March, April, September, and October) under disturbed and very disturbed geomagnetic conditions, respectively. The performance of IFELM is also very good in the western and central part of the Europe during the summer months under disturbed geomagnetic conditions. STORM_foF2MED,IRI performs particularly well in central Europe during the equinoctial months under moderate geomagnetic conditions and during the summer months under very disturbed geomagnetic conditions. The forecasting maps generated by IFERM on the basis of the results provided by the 13 IFELM, show very large areas located at middle-high and high latitudes where the foF2 predictions quite faithfully match the foF2 measurements, and consequently IFERM can be used for generating short-term forecasting maps of foF2 (up to 3 h ahead) over the European area.

Recurrent Neural Networks for Multivariate Time Series with Missing Values.

PubMed

Che, Zhengping; Purushotham, Sanjay; Cho, Kyunghyun; Sontag, David; Liu, Yan

2018-04-17

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness. There is very limited work on exploiting the missing patterns for effective imputation and improving prediction performance. In this paper, we develop novel deep learning models, namely GRU-D, as one of the early attempts. GRU-D is based on Gated Recurrent Unit (GRU), a state-of-the-art recurrent neural network. It takes two representations of missing patterns, i.e., masking and time interval, and effectively incorporates them into a deep model architecture so that it not only captures the long-term temporal dependencies in time series, but also utilizes the missing patterns to achieve better prediction results. Experiments of time series classification tasks on real-world clinical datasets (MIMIC-III, PhysioNet) and synthetic datasets demonstrate that our models achieve state-of-the-art performance and provide useful insights for better understanding and utilization of missing values in time series analysis.

Long Range Weather Prediction III: Miniaturized Distributed Sensors for Global Atmospheric Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teller, E; Leith, C; Canavan, G

2001-11-13

We continue consideration of ways-and-means for creating, in an evolutionary, ever-more-powerful manner, a continually-updated data-base of salient atmospheric properties sufficient for finite differenced integration-based, high-fidelity weather prediction over intervals of 2-3 weeks, leveraging the 10{sup 14} FLOPS digital computing systems now coming into existence. A constellation comprised of 10{sup 6}-10{sup 9} small atmospheric sampling systems--high-tech superpressure balloons carrying early 21st century semiconductor devices, drifting with the local winds over the meteorological spectrum of pressure-altitudes--that assays all portions of the troposphere and lower stratosphere remains the central feature of the proposed system. We suggest that these devices should be active-signaling, rather than passive-transponding, as we had previously proposed only for the ground- and aquatic-situated sensors of this system. Instead of periodic interrogation of the intra-atmospheric transponder population by a constellation of sophisticated small satellites in low Earth orbit, we now propose to retrieve information from the instrumented balloon constellation by existing satellite telephony systems, acting as cellular tower-nodes in a global cellular telephony system whose ''user-set'' is the atmospheric-sampling and surface-level monitoring constellations. We thereby leverage the huge investment in cellular (satellite) telephony and GPS technologies, with large technical and economic gains. This proposal minimizes sponsor forward commitment along its entire programmatic trajectory, and moreover may return data of weather-predictive value soon after field activities commence. We emphasize its high near-term value for making better mesoscale, relatively short-term weather predictions with computing-intensive means, and its great long-term utility in enhancing the meteorological basis for global change predictive studies. We again note that adverse impacts of weather involve continuing costs of the order of 1% of GDP, a large fraction of which could be retrieved if high-fidelity predictions of two weeks forward applicability were available. These {approx}more » $$10{sup 2} B annual savings dwarf the <$$1 B costs of operating a rational, long-range weather prediction system of the type proposed.« less

Long Range Weather Prediction III: Miniaturized Distributed Sensors for Global Atmospheric Measurements

DOE R&D Accomplishments Database

Teller, E.; Leith, C.; Canavan, G.; Wood, L.

2001-11-13

We continue consideration of ways-and-means for creating, in an evolutionary, ever-more-powerful manner, a continually-updated data-base of salient atmospheric properties sufficient for finite differenced integration-based, high-fidelity weather prediction over intervals of 2-3 weeks, leveraging the 10{sup 14} FLOPS digital computing systems now coming into existence. A constellation comprised of 10{sup 6}-10{sup 9} small atmospheric sampling systems--high-tech superpressure balloons carrying early 21st century semiconductor devices, drifting with the local winds over the meteorological spectrum of pressure-altitudes--that assays all portions of the troposphere and lower stratosphere remains the central feature of the proposed system. We suggest that these devices should be active-signaling, rather than passive-transponding, as we had previously proposed only for the ground- and aquatic-situated sensors of this system. Instead of periodic interrogation of the intra-atmospheric transponder population by a constellation of sophisticated small satellites in low Earth orbit, we now propose to retrieve information from the instrumented balloon constellation by existing satellite telephony systems, acting as cellular tower-nodes in a global cellular telephony system whose ''user-set'' is the atmospheric-sampling and surface-level monitoring constellations. We thereby leverage the huge investment in cellular (satellite) telephony and GPS technologies, with large technical and economic gains. This proposal minimizes sponsor forward commitment along its entire programmatic trajectory, and moreover may return data of weather-predictive value soon after field activities commence. We emphasize its high near-term value for making better mesoscale, relatively short-term weather predictions with computing-intensive means, and its great long-term utility in enhancing the meteorological basis for global change predictive studies. We again note that adverse impacts of weather involve continuing costs of the order of 1% of GDP, a large fraction of which could be retrieved if high-fidelity predictions of two weeks forward applicability were available. These{approx}$10{sup 2} B annual savings dwarf the<$1 B costs of operating a rational, long-range weather prediction system of the type proposed.

Protection from Premature Habituation Requires Functional Mushroom Bodies in "Drosophila"

ERIC Educational Resources Information Center

Acevedo, Summer F.; Froudarakis, Emmanuil I.; Kanellopoulos, Alexandros; Skoulakis, Efthimios M. C.

2007-01-01

Diminished responses to stimuli defined as habituation can serve as a gating mechanism for repetitive environmental cues with little predictive value and importance. We demonstrate that wild-type animals diminish their responses to electric shock stimuli with properties characteristic of short- and long-term habituation. We used spatially…

The work ability index and single-item question: associations with sick leave, symptoms, and health--a prospective study of women on long-term sick leave.

PubMed

Ahlstrom, Linda; Grimby-Ekman, Anna; Hagberg, Mats; Dellve, Lotta

2010-09-01

This study investigated the association between the work ability index (WAI) and the single-item question on work ability among women working in human service organizations (HSO) currently on long-term sick leave. It also examined the association between the WAI and the single-item question in relation to sick leave, symptoms, and health. Predictive values of the WAI, the changed WAI, the single-item question and the changed single-item question were investigated for degree of sick leave, symptoms, and health. This cohort study comprised 324 HSO female workers on long-term (>60 days) sick leave, with follow-ups at 6 and 12 months. Participants responded to questionnaires. Data on work ability, sick leave, health, and symptoms were analyzed with regard to associations and predictability. Spearman correlation and mixed-model analysis were performed for repeated measurements over time. The study showed a very strong association between the WAI and the single-item question among all participants. Both the WAI and the single-item question showed similar patterns of associations with sick leave, health, and symptoms. The predictive value for the degree of sick leave and health-related quality of life (HRQoL) was strong for both the WAI and the single-item question, and slightly less strong for vitality, neck pain, both self-rated general and mental health, and behavioral and current stress. This study suggests that the single-item question on work ability could be used as a simple indicator for assessing the status and progress of work ability among women on long-term sick leave.

Post-injury personality in the prediction of outcome following severe acquired brain injury.

PubMed

Cattran, Charlotte Jane; Oddy, Michael; Wood, Rodger Llewellyn; Moir, Jane Frances

2011-01-01

The aim of the study was to examine the utility of five measures of non-cognitive neurobehavioural (NCNB) changes that often occur following acquired brain injury, in predicting outcome (measured in terms of participation and social adaptation) at 1-year follow-up. The study employed a longitudinal, correlational design. Multiple regression was employed to investigate the value of five new NCNB measures of social perception, emotional regulation, motivation, impulsivity and disinhibition in the prediction of outcome as measured by the Mayo-Portland Adaptability Inventory (MPAI). Two NCNB measures (motivation and emotional regulation) were found to significantly predict outcome at 1-year follow-up, accounting for 53% of the variance in MPAI total scores. These measures provide a method of quantifying the extent of NCNB changes following brain injury. The predictive value of the measures indicates that they may represent a useful tool which could aid clinicians in identifying early-on those whose symptoms are likely to persist and who may require ongoing intervention. This could facilitate the planning of rehabilitation programmes.

Motivational state controls the prediction error in Pavlovian appetitive-aversive interactions.

PubMed

Laurent, Vincent; Balleine, Bernard W; Westbrook, R Frederick

2018-01-01

Contemporary theories of learning emphasize the role of a prediction error signal in driving learning, but the nature of this signal remains hotly debated. Here, we used Pavlovian conditioning in rats to investigate whether primary motivational and emotional states interact to control prediction error. We initially generated cues that positively or negatively predicted an appetitive food outcome. We then assessed how these cues modulated aversive conditioning when a novel cue was paired with a foot shock. We found that a positive predictor of food enhances, whereas a negative predictor of that same food impairs, aversive conditioning. Critically, we also showed that the enhancement produced by the positive predictor is removed by reducing the value of its associated food. In contrast, the impairment triggered by the negative predictor remains insensitive to devaluation of its associated food. These findings provide compelling evidence that the motivational value attributed to a predicted food outcome can directly control appetitive-aversive interactions and, therefore, that motivational processes can modulate emotional processes to generate the final error term on which subsequent learning is based. Copyright © 2017 Elsevier Inc. All rights reserved.

Reinforcement Learning Models and Their Neural Correlates: An Activation Likelihood Estimation Meta-Analysis

PubMed Central

Kumar, Poornima; Eickhoff, Simon B.; Dombrovski, Alexandre Y.

2015-01-01

Reinforcement learning describes motivated behavior in terms of two abstract signals. The representation of discrepancies between expected and actual rewards/punishments – prediction error – is thought to update the expected value of actions and predictive stimuli. Electrophysiological and lesion studies suggest that mesostriatal prediction error signals control behavior through synaptic modification of cortico-striato-thalamic networks. Signals in the ventromedial prefrontal and orbitofrontal cortex are implicated in representing expected value. To obtain unbiased maps of these representations in the human brain, we performed a meta-analysis of functional magnetic resonance imaging studies that employed algorithmic reinforcement learning models, across a variety of experimental paradigms. We found that the ventral striatum (medial and lateral) and midbrain/thalamus represented reward prediction errors, consistent with animal studies. Prediction error signals were also seen in the frontal operculum/insula, particularly for social rewards. In Pavlovian studies, striatal prediction error signals extended into the amygdala, while instrumental tasks engaged the caudate. Prediction error maps were sensitive to the model-fitting procedure (fixed or individually-estimated) and to the extent of spatial smoothing. A correlate of expected value was found in a posterior region of the ventromedial prefrontal cortex, caudal and medial to the orbitofrontal regions identified in animal studies. These findings highlight a reproducible motif of reinforcement learning in the cortico-striatal loops and identify methodological dimensions that may influence the reproducibility of activation patterns across studies. PMID:25665667

Magnetic resonance spectroscopic determination of a neuronal and axonal marker in white matter predicts reversibility of deficits in secondary normal pressure hydrocephalus

PubMed Central

Shiino, A; Nishida, Y; Yasuda, H; Suzuki, M; Matsuda, M; Inubushi, T

2004-01-01

Background: Normal pressure hydrocephalus (NPH) is considered to be a treatable form of dementia, because cerebrospinal fluid (CSF) shunting can lessen symptoms. However, neuroimaging has failed to predict when shunting will be effective. Objective: To investigate whether 1H (proton) magnetic resonance (MR) spectroscopy could predict functional outcome in patients after shunting. Methods: Neurological state including Hasegawa's dementia scale, gait, continence, and the modified Rankin scale were evaluated in 21 patients with secondary NPH who underwent ventriculo-peritoneal shunting. Outcomes were measured postoperatively at one and 12 months and were classified as excellent, fair, or poor. MR spectra were obtained from left hemispheric white matter. Results: Significant preoperative differences in N-acetyl aspartate (NAA)/creatine (Cr) and NAA/choline (Cho) were noted between patients with excellent and poor outcome at one month (p = 0.0014 and 0.0036, respectively). Multiple regression analysis linked higher preoperative NAA/Cr ratio, gait score, and modified Rankin scale to better one month outcome. Predictive value, sensitivity, and specificity for excellent outcome following shunting were 95.2%, 100%, and 87.5%. Multiple regression analysis indicated that NAA/Cho had the best predictive value for one year outcome (p = 0.0032); predictive value, sensitivity, and specificity were 89.5%, 90.0%, and 88.9%. Conclusions: MR spectroscopy predicted long term post-shunting outcomes in patients with secondary NPH, and it would be a useful assessment tool before lumbar drainage. PMID:15258216

Lepton mixing and the charged-lepton mass ratios

NASA Astrophysics Data System (ADS)

Jurčiukonis, Darius; Lavoura, Luís

2018-03-01

We construct a class of renormalizable models for lepton mixing that generate predictions given in terms of the charged-lepton mass ratios. We show that one of those models leads, when one takes into account the known experimental values, to almost maximal CP -breaking phases and to almost maximal neutrinoless double-beta decay. We study in detail the scalar potential of the models, especially the bounds imposed by unitarity on the values of the quartic couplings.

Decadal predictability of river discharge with climate oscillations over the 20th and early 21st century

NASA Astrophysics Data System (ADS)

Wanders, Niko; Wada, Yoshihide

2015-12-01

Long-term hydrological forecasts are important to increase our resilience and preparedness to extreme hydrological events. The skill in these forecasts is still limited due to large uncertainties inherent in hydrological models and poor predictability of long-term meteorological conditions. Here we show that strong (lagged) correlations exist between four different major climate oscillation modes and modeled and observed discharge anomalies over a 100 year period. The strongest correlations are found between the El Niño-Southern Oscillation signal and river discharge anomalies all year round, while North Atlantic Oscillation and Antarctic Oscillation time series are strongly correlated with winter discharge anomalies. The correlation signal is significant for periods up to 5 years for some regions, indicating a high added value of this information for long-term hydrological forecasting. The results suggest that long-term hydrological forecasting could be significantly improved by including the climate oscillation signals and thus improve our preparedness for hydrological extremes in the near future.

Variability of breathing during wakefulness while using CPAP predicts adherence.

PubMed

Fujita, Yukio; Yamauchi, Motoo; Uyama, Hiroki; Kumamoto, Makiko; Koyama, Noriko; Yoshikawa, Masanori; Strohl, Kingman P; Kimura, Hiroshi

2017-02-01

The standard therapy for obstructive sleep apnoea (OSA) is continuous positive airway pressure (CPAP) therapy. However, long-term adherence remains at ~50% despite improvements in behavioural and educational interventions. Based on prior work, we explored whether regularity of breathing during wakefulness might be a physiologic predictor of CPAP adherence. Of the 117 consecutive patients who were diagnosed with OSA and prescribed CPAP, 79 CPAP naïve patients were enrolled in this prospective study. During CPAP initiation, respiratory signals were collected using respiratory inductance plethysmography while wearing CPAP during wakefulness in a seated position. Breathing regularity was assessed by the coefficient of variation (CV) for breath-by-breath estimated tidal volume (V T ) and total duration of respiratory cycle (Ttot). In a derivation group (n = 36), we determined the cut-off CV value which predicted poor CPAP adherence at the first month of therapy, and verified the validity of this predetermined cut-off value in the remaining participants (validation group; n = 43). In the derivation group, the CV for estimated V T was significantly higher in patients with poor adherence than with good adherence (median (interquartile range): 44.2 (33.4-57.4) vs 26.0 (20.4-33.2), P < 0.001). The CV cut-off value for estimated V T for poor CPAP adherence was 34.0, according to a receiver-operating characteristic (ROC) curve. In the validation group, the CV value for estimated V T >34.0 confirmed to be predicting poor CPAP adherence (sensitivity, 0.78; specificity, 0.83). At the initiation of therapy, breathing regularity during wakefulness while wearing CPAP is an objective predictor of short-term CPAP adherence. © 2016 Asian Pacific Society of Respirology.

Psychological Factors and Alcohol Use in Problematic Mobile Phone Use in the Spanish Population

PubMed Central

De-Sola, José; Talledo, Hernán; Rubio, Gabriel; de Fonseca, Fernando Rodríguez

2017-01-01

This research aims to study the existing relationships among the factors of state anxiety, depression, impulsivity, and alcohol consumption regarding problematic mobile phone use, as assessed by the Mobile Phone Problem Use Scale. The study was conducted among 1,126 participants recruited among the general Spanish population, aged 16–65 years, by assessing the predictive value of these variables regarding this problematic use. Initially tobacco use was also considered being subsequently refused because of the low internal consistency of the scale used. In general terms, the results show that this problematic use is mainly related to state anxiety and impulsivity, through the dimensions of Positive and Negative Urgency. Considering its predictive value, multiple regression analysis reveals that state anxiety, positive and negative urgency, and alcohol consumption may predict problematic mobile phone use, ruling out the influence of depression. PMID:28217101

Psychological Factors and Alcohol Use in Problematic Mobile Phone Use in the Spanish Population.

PubMed

De-Sola, José; Talledo, Hernán; Rubio, Gabriel; de Fonseca, Fernando Rodríguez

2017-01-01

This research aims to study the existing relationships among the factors of state anxiety, depression, impulsivity, and alcohol consumption regarding problematic mobile phone use, as assessed by the Mobile Phone Problem Use Scale. The study was conducted among 1,126 participants recruited among the general Spanish population, aged 16-65 years, by assessing the predictive value of these variables regarding this problematic use. Initially tobacco use was also considered being subsequently refused because of the low internal consistency of the scale used. In general terms, the results show that this problematic use is mainly related to state anxiety and impulsivity, through the dimensions of Positive and Negative Urgency. Considering its predictive value, multiple regression analysis reveals that state anxiety, positive and negative urgency, and alcohol consumption may predict problematic mobile phone use, ruling out the influence of depression.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

Left lobe of the prostate during clinical prostate cancer screening: the dark side of the gland for right-handed examiners.

PubMed

Ploussard, G; Nicolaiew, N; Mongiat-Artus, P; Terry, S; Allory, Y; Vacherot, F; Abbou, C-C; Desgrandchamps, F; Salomon, L; de la Taille, A

2014-06-01

The predictive value of the abnormality side during digital rectal examination (DRE) has never been studied, suggesting that physicians examined the left lobe of the gland as well as the right lobe. We aimed to assess the predictive value of the side of DRE abnormality for prostate cancer (PCa) detection and aggressiveness in right-handed urologists. An analysis of a prospective database was carried out that included all consecutive men undergoing prostate biopsies between 2001 and 2012. The main end point was the predictive value of the abnormality side during DRE for cancer detection in clinically suspicious unilateral T2 disease. The diagnostic performance of left- versus right-sided abnormality was also assessed in terms of sensitivity, specificity and negative/positive predictive values. Overall, 308 patients had a suspicious unilateral clinical disease (detection rate 57.5%). The cancer detection rate was significantly higher in case of left-sided compared with right-sided clinical T2 stage (odds ratio 2.1). In case of left-sided disease, the number of positive cores, the rate of perineural invasion, the rate of primary grade 4 pattern and the percentage of cancer involvement per core were significantly higher compared with those reported for right-sided disease. The predictive value of abnormality laterality for cancer detection and aggressiveness remained statistically independent in multivariate models. The positive predictive value for cancer detection was 64.6 in case of suspicious left-sided disease versus 46.9 in case of right-sided disease. The risks of detecting PCa and aggressive disease on biopsy are significantly higher when DRE reveals a suspicious left-sided clinical disease as compared with right-sided disease. Right-handed physicians should be aware of this variance in diagnostic performance and potential underdetection of left-sided clinical disease, and should improve their examination of the left lobe of the gland by conducting longer exams or changing the patient's position.

Predictive performance of the human Cell Line Activation Test (h-CLAT) for lipophilic chemicals with high octanol-water partition coefficients.

PubMed

Takenouchi, Osamu; Miyazawa, Masaaki; Saito, Kazutoshi; Ashikaga, Takao; Sakaguchi, Hitoshi

2013-01-01

To meet the urgent need for a reliable alternative test for predicting skin sensitizing potential of many chemicals, we have developed a cell-based in vitro test, human Cell Line Activation Test (h-CLAT). However, the predictive performance for lipophilic chemicals in the h-CLAT still remains relatively unknown. Moreover, it's suggested that low water solubility of chemicals might induce false negative outcomes. Thus, in this study, we tested relatively low water soluble 37 chemicals with log Kow values above and below 3.5 in the h-CLAT. The small-scale assessment resulted in nine false negative outcomes for chemicals with log Kow values greater than 3.5. We then created a dataset of 143 chemicals by combining the existing dataset of 106 chemicals and examined the predictive performance of the h-CLAT for chemicals with a log Kow of less than 3.5; a total of 112 chemicals from the 143 chemicals in the dataset. The sensitivity and overall accuracy for the 143 chemicals were 83% and 80%, respectively. In contrast, sensitivity and overall accuracy for the 112 chemicals with log Kow values below 3.5 improved to 94% and 88%, respectively. These data suggested that the h-CLAT could successfully detect sensitizers with log Kow values up to 3.5. When chemicals with log Kow values greater than 3.5 that were deemed positive by h-CLAT were included with the 112 chemicals, the sensitivity and accuracy in terms of the resulting applicable 128 chemicals out of the 143 chemicals became 95% and 88%, respectively. The use of log Kow values gave the h-CLAT a higher predictive performance. Our results demonstrated that the h-CLAT could predict sensitizing potential of various chemicals, which contain lipophilic chemicals using a large-scale chemical dataset.

The predictive consequences of parameterization

NASA Astrophysics Data System (ADS)

White, J.; Hughes, J. D.; Doherty, J. E.

2013-12-01

In numerical groundwater modeling, parameterization is the process of selecting the aspects of a computer model that will be allowed to vary during history matching. This selection process is dependent on professional judgment and is, therefore, inherently subjective. Ideally, a robust parameterization should be commensurate with the spatial and temporal resolution of the model and should include all uncertain aspects of the model. Limited computing resources typically require reducing the number of adjustable parameters so that only a subset of the uncertain model aspects are treated as estimable parameters; the remaining aspects are treated as fixed parameters during history matching. We use linear subspace theory to develop expressions for the predictive error incurred by fixing parameters. The predictive error is comprised of two terms. The first term arises directly from the sensitivity of a prediction to fixed parameters. The second term arises from prediction-sensitive adjustable parameters that are forced to compensate for fixed parameters during history matching. The compensation is accompanied by inappropriate adjustment of otherwise uninformed, null-space parameter components. Unwarranted adjustment of null-space components away from prior maximum likelihood values may produce bias if a prediction is sensitive to those components. The potential for subjective parameterization choices to corrupt predictions is examined using a synthetic model. Several strategies are evaluated, including use of piecewise constant zones, use of pilot points with Tikhonov regularization and use of the Karhunen-Loeve transformation. The best choice of parameterization (as defined by minimum error variance) is strongly dependent on the types of predictions to be made by the model.

Entropy of gaseous boron monobromide

NASA Astrophysics Data System (ADS)

Wang, Jian-Feng; Peng, Xiao-Long; Zhang, Lie-Hui; Wang, Chao-Wen; Jia, Chun-Sheng

2017-10-01

We present an explicit representation of molar entropy for gaseous boron monobromide in terms of experimental values of only three molecular constants. Fortunately, through comparison of theoretically calculated results and experimental data, we find that the molar entropy of gaseous boron monobromide can be well predicted by employing the improved Manning-Rosen oscillator to describe the internal vibration of boron monobromide molecule. The present approach provides also opportunities for theoretical predictions of molar entropy for other gases with no use of large amounts of experimental spectroscopy data.

[A Retrospective Study of Mean Computed Tomography Value to Predict 
the Tumor Invasiveness in AAH and Clinical Stage Ia Lung Cancer].

PubMed

Wu, Hanran; Liu, Changqing; Xu, Meiqing; Xiong, Ran; Xu, Guangwen; Li, Caiwei; Xie, Mingran

2018-03-20

Recently, the detectable rate of ground-glass opacity (GGO ) was significantly increased, a appropriate diagnosis before clinic treatment tends to be important for patients with GGO lesions. The aim of this study is to validate the ability of the mean computed tomography (m-CT) value to predict tumor invasiveness, and compared with other measurements such as Max CT value, GGO size, solid size of GGO and C/T ratio (consolid/tumor ratio, C/T) to find out the best measurement to predict tumor invasiveness. A retrospective study was conducted of 129 patients who recieved lobectomy and were pathological confirmed as atypical adenomatous pyperplasia (AAH) or clinical stage Ia lung cance in our center between January 2012 and December 2013. Of those 129 patients, the number of patients of AAH, AIS, AIS and invasive adenocarcinoma were 43, 26, 17 and 43, respectively. We defined AAH and AIS as noninvasive cancer (NC), MIA and invasive adenocarcinoma were categorized as invasive cancer(IC). We used receiver operating characteristic (ROC) curve analysis to compare the ability to predict tumor invasiveness between m-CT value, consolidation/tumor ratio, tumor size and solid size of tumor. Multiple logistic regression analyses were performed to determine the independent variables for prediction of pathologic more invasive lung cancer. 129 patients were enrolled in our study (59 male and 70 female), the patients were a median age of (62.0±8.6) years (range, 44 to 82 years). The two groups were similar in terms of age, sex, differentiation (P>0.05). ROC curve analysis was performed to determine the appropriate cutoff value and area under the cure (AUC). The cutoff value of solid tumor size, tumor size, C/T ratio, m-CT value and Max CT value were 9.4 mm, 15.3 mm, 47.5%, -469.0 HU and -35.0 HU, respectively. The AUC of those variate were 0.89, 0.79, 0.82, 0.90, 0.85, respectively. When compared the clinical and radiologic data between two groups, we found the IC group was strongly associated with a high m-CT value, high Max CT value, high C/T ratio and large tumor size. Gender, solid tumor size, tumor size, C/T ratio, m-CT value and MaxCT value were selected factor for multivariate analysis, when using the preoperatively determined variables to predict the tumor invasiveness, revealed that tumor size, C/T ratio, m-CT value and Max CT value were independent predictive factors of IC. The musurements of Max CT value, GGO size, solid size of GGO and C/T ratio were significantly correlated with tumor invasiveness, and the evaluation of m-CT value is most useful musurement in predicting more invasive lung cancer.

Risk Prediction Models in Psychiatry: Toward a New Frontier for the Prevention of Mental Illnesses.

PubMed

Bernardini, Francesco; Attademo, Luigi; Cleary, Sean D; Luther, Charles; Shim, Ruth S; Quartesan, Roberto; Compton, Michael T

2017-05-01

We conducted a systematic, qualitative review of risk prediction models designed and tested for depression, bipolar disorder, generalized anxiety disorder, posttraumatic stress disorder, and psychotic disorders. Our aim was to understand the current state of research on risk prediction models for these 5 disorders and thus future directions as our field moves toward embracing prediction and prevention. Systematic searches of the entire MEDLINE electronic database were conducted independently by 2 of the authors (from 1960 through 2013) in July 2014 using defined search criteria. Search terms included risk prediction, predictive model, or prediction model combined with depression, bipolar, manic depressive, generalized anxiety, posttraumatic, PTSD, schizophrenia, or psychosis. We identified 268 articles based on the search terms and 3 criteria: published in English, provided empirical data (as opposed to review articles), and presented results pertaining to developing or validating a risk prediction model in which the outcome was the diagnosis of 1 of the 5 aforementioned mental illnesses. We selected 43 original research reports as a final set of articles to be qualitatively reviewed. The 2 independent reviewers abstracted 3 types of data (sample characteristics, variables included in the model, and reported model statistics) and reached consensus regarding any discrepant abstracted information. Twelve reports described models developed for prediction of major depressive disorder, 1 for bipolar disorder, 2 for generalized anxiety disorder, 4 for posttraumatic stress disorder, and 24 for psychotic disorders. Most studies reported on sensitivity, specificity, positive predictive value, negative predictive value, and area under the (receiver operating characteristic) curve. Recent studies demonstrate the feasibility of developing risk prediction models for psychiatric disorders (especially psychotic disorders). The field must now advance by (1) conducting more large-scale, longitudinal studies pertaining to depression, bipolar disorder, anxiety disorders, and other psychiatric illnesses; (2) replicating and carrying out external validations of proposed models; (3) further testing potential selective and indicated preventive interventions; and (4) evaluating effectiveness of such interventions in the context of risk stratification using risk prediction models. © Copyright 2017 Physicians Postgraduate Press, Inc.

Overgeneral memory predicts stability of short-term outcome of electroconvulsive therapy for depression.

PubMed

Raes, Filip; Sienaert, Pascal; Demyttenaere, Koen; Peuskens, Joseph; Williams, J Mark G; Hermans, Dirk

2008-03-01

To investigate the predictive value of overgeneral memory (OGM) for outcome of electroconvulsive therapy (ECT) for depression. The Autobiographical Memory Test was used to measure OGM in 25 patients with depression before ECT. The Hamilton Rating Scale for Depression (HRSD) was administered weekly to 1 week posttreatment. Overgeneral memory did not predict HRSD scores from the last ECT treatment, but did predict HRSD change scores from the last treatment to 1-week follow-up: patients high in OGM experienced a relatively greater increase in HRSD scores after the last treatment. Results further extend the status of OGM as a predictor of an unfavorable course of depression to a previously unstudied ECT population.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring.

PubMed

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D; Larson, Timothy V; Keller, Joshua P; Kaufman, Joel D

2017-01-01

Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children's Health Study (CHS), and the Inhalable Particulate Network (IPN). In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84-0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00-0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38-46; http://dx.doi.org/10.1289/EHP131.

Prognostic Value of the Thrombolysis in Myocardial Infarction Risk Score in ST-Elevation Myocardial Infarction Patients With Left Ventricular Dysfunction (from the EPHESUS Trial).

PubMed

Popovic, Batric; Girerd, Nicolas; Rossignol, Patrick; Agrinier, Nelly; Camenzind, Edoardo; Fay, Renaud; Pitt, Bertram; Zannad, Faiez

2016-11-15

The Thrombolysis in Myocardial Infarction (TIMI) risk score remains a robust prediction tool for short-term and midterm outcome in the patients with ST-elevation myocardial infarction (STEMI). However, the validity of this risk score in patients with STEMI with reduced left ventricular ejection fraction (LVEF) remains unclear. A total of 2,854 patients with STEMI with early coronary revascularization participating in the randomized EPHESUS (Epleronone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study) trial were analyzed. TIMI risk score was calculated at baseline, and its predictive value was evaluated using C-indexes from Cox models. The increase in reclassification of other variables in addition to TIMI score was assessed using the net reclassification index. TIMI risk score had a poor predictive accuracy for all-cause mortality (C-index values at 30 days and 1 year ≤0.67) and recurrent myocardial infarction (MI; C-index values ≤0.60). Among TIMI score items, diabetes/hypertension/angina, heart rate >100 beats/min, and systolic blood pressure <100 mm Hg were inconsistently associated with survival, whereas none of the TIMI score items, aside from age, were significantly associated with MI recurrence. Using a constructed predictive model, lower LVEF, lower estimated glomerular filtration rate (eGFR), and previous MI were significantly associated with all-cause mortality. The predictive accuracy of this model, which included LVEF and eGFR, was fair for both 30-day and 1-year all-cause mortality (C-index values ranging from 0.71 to 0.75). In conclusion, TIMI risk score demonstrates poor discrimination in predicting mortality or recurrent MI in patients with STEMI with reduced LVEF. LVEF and eGFR are major factors that should not be ignored by predictive risk scores in this population. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope

NASA Astrophysics Data System (ADS)

Deshmukh, Dhananjay Suresh; Chaube, Umesh Chandra; Ekube Hailu, Ambaye; Aberra Gudeta, Dida; Tegene Kassa, Melaku

2013-06-01

The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall-runoff events is termed as CN(PQ), land use and land cover (LULC) is termed as CN(LU) and the CN based on land slope is termed as SACN2. The estimated annual CN(PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN(PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN(LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN(LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN(LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN(LU) and CN(PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA-CN2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS-CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.

Evaluation of calibration efficacy under different levels of uncertainty

DOE PAGES

Heo, Yeonsook; Graziano, Diane J.; Guzowski, Leah; ...

2014-06-10

This study examines how calibration performs under different levels of uncertainty in model input data. It specifically assesses the efficacy of Bayesian calibration to enhance the reliability of EnergyPlus model predictions. A Bayesian approach can be used to update uncertain values of parameters, given measured energy-use data, and to quantify the associated uncertainty.We assess the efficacy of Bayesian calibration under a controlled virtual-reality setup, which enables rigorous validation of the accuracy of calibration results in terms of both calibrated parameter values and model predictions. Case studies demonstrate the performance of Bayesian calibration of base models developed from audit data withmore » differing levels of detail in building design, usage, and operation.« less

Pre-selection and assessment of green organic solvents by clustering chemometric tools.

PubMed

Tobiszewski, Marek; Nedyalkova, Miroslava; Madurga, Sergio; Pena-Pereira, Francisco; Namieśnik, Jacek; Simeonov, Vasil

2018-01-01

The study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables - bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as "green". Values for logBCF, logK OW and logK OA were modelled for 43 rather nonpolar solvents and 69 polar ones. Application of multivariate statistics was also proved to be useful in the assessment of the obtained modelling results. The presented approach can be one of the first steps and support tools in the assessment of chemicals in terms of their greenness. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictors of long-term compliance in attending a worksite hypertension programme.

PubMed

Landers, R; Riccobene, A; Beyreuther, M; Neusy, A J

1993-12-01

Variables such as patient's anxiety, knowledge, number of medication changes, medication-induced side-effects and programme-derived benefits and conveniences have been reported or theorised to be important determinants of patient's attendance at worksite hypertension programmes. This study investigates whether these variables have predictive value in differentiating compliers from noncompliers attending a union-sponsored worksite hypertension programme for at least five years. Scores were created from a questionnaire distributed to 243 patients with a response rate of 98%. Compliance was defined as missing < or = 25% of scheduled clinic appointments. By discriminant statistical analysis scores for patient's anxiety, knowledge, number of medication changes, medication side-effects, perceived benefits and conveniences failed to show any predictive value for patient's compliance with appointment keeping.

Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis.

PubMed

Beauchet, Olivier; Annweiler, Cédric; Callisaya, Michele L; De Cock, Anne-Marie; Helbostad, Jorunn L; Kressig, Reto W; Srikanth, Velandai; Steinmetz, Jean-Paul; Blumen, Helena M; Verghese, Joe; Allali, Gilles

2016-06-01

Poor gait performance predicts risk of developing dementia. No structured critical evaluation has been conducted to study this association yet. The aim of this meta-analysis was to systematically examine the association of poor gait performance with incidence of dementia. An English and French Medline search was conducted in June 2015, with no limit of date, using the medical subject headings terms "Gait" OR "Gait Disorders, Neurologic" OR "Gait Apraxia" OR "Gait Ataxia" AND "Dementia" OR "Frontotemporal Dementia" OR "Dementia, Multi-Infarct" OR "Dementia, Vascular" OR "Alzheimer Disease" OR "Lewy Body Disease" OR "Frontotemporal Dementia With Motor Neuron Disease" (Supplementary Concept). Poor gait performance was defined by standardized tests of walking, and dementia was diagnosed according to international consensus criteria. Four etiologies of dementia were identified: any dementia, Alzheimer disease (AD), vascular dementia (VaD), and non-AD (ie, pooling VaD, mixed dementias, and other dementias). Fixed effects meta-analyses were performed on the estimates in order to generate summary values. Of the 796 identified abstracts, 12 (1.5%) were included in this systematic review and meta-analysis. Poor gait performance predicted dementia [pooled hazard ratio (HR) combined with relative risk and odds ratio = 1.53 with P < .001 for any dementia, pooled HR = 1.79 with P < .001 for VaD, HR = 1.89 with P value < .001 for non-AD]. Findings were weaker for predicting AD (HR = 1.03 with P value = .004). This meta-analysis provides evidence that poor gait performance predicts dementia. This association depends on the type of dementia; poor gait performance is a stronger predictor of non-AD dementias than AD. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

First-trimester mean arterial blood pressure and the risk of preeclampsia: The Great Obstetrical Syndromes (GOS) study.

PubMed

Gasse, Cédric; Boutin, Amélie; Coté, Maxime; Chaillet, Nils; Bujold, Emmanuel; Demers, Suzanne

2018-04-01

To estimate the predictive value of first-trimester mean arterial pressure (MAP) for the hypertensive disorders of pregnancy (HDP). We performed a prospective cohort study of nulliparous women recruited at 11 0/7 -13 6/7  weeks. MAP was calculated from blood pressure measured on both arms simultaneously using an automated device taking a series of recordings until blood pressure stability was reached. MAP was reported as multiples of the median adjusted for gestational age. Participants were followed for development of gestational hypertension (GH), preeclampsia (PE), preterm PE (<37 weeks) and early-onset (EO) PE (<34 weeks). Receiver operating characteristic curves and the area under the curve (AUC) were used to estimate the predictive values of MAP. Multivariate logistic regressions were used to develop predictive models combining MAP and maternal characteristics. We obtained complete follow-up in 4700 (99%) out of 4749 eligible participants. GH without PE was observed in 250 (5.3%) participants, and PE in 241 (5.1%), including 33 (0.7%) preterm PE and 10 (0.2%) EO-PE. First-trimester MAP was associated with GH (AUC: 0.77; 95%CI: 0.74-0.80); term PE (0.73; 95%CI: 0.70-0.76), preterm PE (0.80; 95%CI: 0.73-0.87) and EO-PE (0.79; 95%CI: 0.62-0.96). At a 10% false-positive rate, first-trimester MAP could have predicted 39% of GH, 34% of term PE, 48% of preterm PE and 60% of EO-PE. The addition of maternal characteristics improved the predictive values (to 40%, 37%, 55% and 70%, respectively). First-trimester MAP is a strong predictor of GH and PE in nulliparous women. Copyright © 2017 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Prediction of successful memory encoding based on single-trial rhinal and hippocampal phase information.

PubMed

Höhne, Marlene; Jahanbekam, Amirhossein; Bauckhage, Christian; Axmacher, Nikolai; Fell, Juergen

2016-10-01

Mediotemporal EEG characteristics are closely related to long-term memory formation. It has been reported that rhinal and hippocampal EEG measures reflecting the stability of phases across trials are better suited to distinguish subsequently remembered from forgotten trials than event-related potentials or amplitude-based measures. Theoretical models suggest that the phase of EEG oscillations reflects neural excitability and influences cellular plasticity. However, while previous studies have shown that the stability of phase values across trials is indeed a relevant predictor of subsequent memory performance, the effect of absolute single-trial phase values has been little explored. Here, we reanalyzed intracranial EEG recordings from the mediotemporal lobe of 27 epilepsy patients performing a continuous word recognition paradigm. Two-class classification using a support vector machine was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies and time points. We demonstrate that it is possible to successfully predict single-trial memory formation in the majority of patients (23 out of 27) based on only three single-trial phase values given by a rhinal phase, a hippocampal phase, and a rhinal-hippocampal phase difference. Overall classification accuracy across all subjects was 69.2% choosing frequencies from the range between 0.5 and 50Hz and time points from the interval between -0.5s and 2s. For 19 patients, above chance prediction of subsequent memory was possible even when choosing only time points from the prestimulus interval (overall accuracy: 65.2%). Furthermore, prediction accuracies based on single-trial phase surpassed those based on single-trial power. Our results confirm the functional relevance of mediotemporal EEG phase for long-term memory operations and suggest that phase information may be utilized for memory enhancement applications based on deep brain stimulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Tidal Response of Preliminary Jupiter Model

NASA Astrophysics Data System (ADS)

Wahl, Sean M.; Hubbard, William B.; Militzer, Burkhard

2016-11-01

In anticipation of improved observational data for Jupiter’s gravitational field, from the Juno spacecraft, we predict the static tidal response for a variety of Jupiter interior models based on ab initio computer simulations of hydrogen-helium mixtures. We calculate hydrostatic-equilibrium gravity terms, using the non-perturbative concentric Maclaurin Spheroid method that eliminates lengthy expansions used in the theory of figures. Our method captures terms arising from the coupled tidal and rotational perturbations, which we find to be important for a rapidly rotating planet like Jupiter. Our predicted static tidal Love number, {k}2=0.5900, is ˜10% larger than previous estimates. The value is, as expected, highly correlated with the zonal harmonic coefficient J 2, and is thus nearly constant when plausible changes are made to the interior structure while holding J 2 fixed at the observed value. We note that the predicted static k 2 might change, due to Jupiter’s dynamical response to the Galilean moons, and find reasons to argue that the change may be detectable—although we do not present here a theory of dynamical tides for highly oblate Jovian planets. An accurate model of Jupiter’s tidal response will be essential for interpreting Juno observations and identifying tidal signals from effects of other interior dynamics of Jupiter’s gravitational field.

The validation of a human force model to predict dynamic forces resulting from multi-joint motions

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Maida, James C.; Aldridge, Ann M.; Hasson, Scott M.; Woolford, Barbara J.

1992-01-01

The development and validation is examined of a dynamic strength model for humans. This model is based on empirical data. The shoulder, elbow, and wrist joints were characterized in terms of maximum isolated torque, or position and velocity, in all rotational planes. This data was reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining torque as a function of position and velocity. The isolated joint torque equations were then used to compute forces resulting from a composite motion, in this case, a ratchet wrench push and pull operation. A comparison of the predicted results of the model with the actual measured values for the composite motion indicates that forces derived from a composite motion of joints (ratcheting) can be predicted from isolated joint measures. Calculated T values comparing model versus measured values for 14 subjects were well within the statistically acceptable limits and regression analysis revealed coefficient of variation between actual and measured to be within 0.72 and 0.80.

Bigger is Better, but at What Cost? Estimating the Economic Value of Incremental Data Assets.

PubMed

Dalessandro, Brian; Perlich, Claudia; Raeder, Troy

2014-06-01

Many firms depend on third-party vendors to supply data for commercial predictive modeling applications. An issue that has received very little attention in the prior research literature is the estimation of a fair price for purchased data. In this work we present a methodology for estimating the economic value of adding incremental data to predictive modeling applications and present two cases studies. The methodology starts with estimating the effect that incremental data has on model performance in terms of common classification evaluation metrics. This effect is then translated into economic units, which gives an expected economic value that the firm might realize with the acquisition of a particular data asset. With this estimate a firm can then set a data acquisition price that targets a particular return on investment. This article presents the methodology in full detail and illustrates it in the context of two marketing case studies.

Equilibration of quantum hall edge states and its conductance fluctuations in graphene p-n junctions

NASA Astrophysics Data System (ADS)

Kumar, Chandan; Kuiri, Manabendra; Das, Anindya

2018-02-01

We report an observation of conductance fluctuations (CFs) in the bipolar regime of quantum hall (QH) plateaus in graphene (p-n-p/n-p-n) devices. The CFs in the bipolar regime are shown to decrease with increasing bias and temperature. At high temperature (above 7 K) the CFs vanishes completely and the flat quantized plateaus are recovered in the bipolar regime. The values of QH plateaus are in theoretical agreement based on full equilibration of chiral channels at the p-n junction. The amplitude of CFs for different filling factors follows a trend predicted by the random matrix theory. Although, there are mismatch in the values of CFs between the experiment and theory but at higher filling factors the experimental values become closer to the theoretical prediction. The suppression of CFs and its dependence has been understood in terms of time dependent disorders present at the p-n junctions.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

Structural and Functional Lung Impairment in Adult Survivors of Bronchopulmonary Dysplasia.

PubMed

Caskey, Steven; Gough, Aisling; Rowan, Stephen; Gillespie, Scott; Clarke, Jim; Riley, Marshall; Megarry, Jacqui; Nicholls, Paul; Patterson, Chris; Halliday, Henry L; Shields, Michael D; McGarvey, Lorcan

2016-08-01

As more preterm infants recover from severe bronchopulmonary dysplasia (BPD), it is critical to understand the clinical consequences of this condition on the lung health of adult survivors. To assess structural and functional lung parameters in young adult BPD survivors and preterm and term control subjects. Young adult survivors of BPD (mean age, 24 yr) underwent spirometry, lung volume assessment, transfer factor, lung clearance index, and fractional exhaled nitric oxide measurements, together with high-resolution chest computed tomography and cardiopulmonary exercise testing. Twenty-five adult BPD survivors (mean ± SD gestational age, 26.8 ± 2.3 wk; birth weight, 866 ± 255 g), 24 adult prematurely born non-BPD control subjects (gestational age, 30.6 ± 1.9 wk; birth weight, 1,234 ± 207 g), and 25 adult term-birth control subjects (gestational age, 38.5 ± 0.9 wk; birth weight, 3,569 ± 2,979 g) were studied. Subjects with BPD were more likely to be wakened by cough (odds ratio, 9.7; 95% confidence interval, 1.8-52.6; P < 0.01) or wheeze and breathlessness (odds ratio, 12.2; 95% confidence interval; 1.3-112; P < 0.05) than term control subjects after adjusting for sex and current smoking. Preterm subjects had greater airway obstruction than term subjects. Subjects with BPD had significantly lower values for FEV1 and forced expiratory flow, midexpiratory phase (percent predicted and z-scores), than term control subjects (both P < 0.001). Although non-BPD subjects also had lower spirometric values than term control subjects, none of the differences reached statistical significance. More subjects with BPD (25%) had fixed airflow obstruction than non-BPD (12.5%) and term (0%) subjects (P = 0.004). Both BPD and non-BPD subjects had significantly greater impairment in gas transfer (Kco percent predicted) than term subjects (both P < 0.05). Eighteen (37%) preterm participants were classified as small for gestational age (birth weight below the 10th percentile for gestational age). These subjects had significantly greater impairment in FEV1 (percent predicted values and z-scores) than those born appropriate for gestational age. BPD survivors had significantly more severe radiographic structural lung impairment than non-BPD subjects. Both preterm groups had impaired exercise capacity compared with term control subjects. There was a trend for greater limitation and leg discomfort in BPD survivors. Adult preterm birth survivors, especially those who developed BPD, continue to experience respiratory symptoms and exhibit clinically important levels of pulmonary impairment.

The value of Doppler ultrasound in predicting delayed graft function occurrence after kidney transplantation.

PubMed

Mocny, Grzegorz; Bachul, Piotr; Chang, Ea-Sle; Kulig, Piotr

The aim of this study was to assess the predictive value of blood flow velocity and vascular resistance measured by Doppler ultrasound in terms of pulsatility index (PI) and resistive index (RI) respectively, in the occurrence of delayed graft function (DGF) after kidney transplantation. This prospective study enrolled kidney transplant recipients operated from January 2005 to April 2009 in the 1st Department of General, Oncological and Gastroenterological Surgery, Jagiellonian University Medical College, Kraków, Poland. The medical records of 53 kidney transplant recipients from deceased donors were reviewed. PI and RI values of the graft arcuate artery were calculated immediately after blood flow restoration and on the 1st, 2nd, 4th and 8th post-operative day. DGF was observed in 20 patients (37.7%), while 33 patients (62.3%) had immediate restoration of the kidney function. The mean intraoperative values of RI and PI from patients with DGF were significantly higher in comparison to patients without DGF (0.9 vs. 0.74, p <0.001; 1.76 vs. 1.54, p = 0.019, respectively). Post-operatively, the RI and PI values remained stable and significantly higher in DGF group. The highest sensitivity of RI to predict DGF occurrence was observed intraoperatively and on the first postoperative day, with values of 77.8% and 72.2%, respectively. The risk of DGF occurrence with intraoperative RI value ≥0.9 increased by 13-fold, and with intraoperative PI value ≥1.9 by 12-fold. This increase was even more prominent during the first post-operative day with RI value ≥0.9 or PI value ≥1.9 with 19-fold increase in the risk of DGF occurrence. According to our study, the utilization of Doppler ultrasound with measurement of hemodynamic parameters (PI, RI), play a crucial role in predicting the outcomes of kidney transplantation.

Immediate perception of a reward is distinct from the reward’s long-term salience

PubMed Central

McGinnis, John P; Jiang, Huoqing; Agha, Moutaz Ali; Sanchez, Consuelo Perez; Lange, Jeff; Yu, Zulin; Marion-Poll, Frederic; Si, Kausik

2016-01-01

Reward perception guides all aspects of animal behavior. However, the relationship between the perceived value of a reward, the latent value of a reward, and the behavioral response remains unclear. Here we report that, given a choice between two sweet and chemically similar sugars—L- and D-arabinose—Drosophila melanogaster prefers D- over L- arabinose, but forms long-term memories of L-arabinose more reliably. Behavioral assays indicate that L-arabinose-generated memories require sugar receptor Gr43a, and calcium imaging and electrophysiological recordings indicate that L- and D-arabinose differentially activate Gr43a-expressing neurons. We posit that the immediate valence of a reward is not always predictive of the long-term reinforcement value of that reward, and that a subset of sugar-sensing neurons may generate distinct representations of similar sugars, allowing for rapid assessment of the salient features of various sugar rewards and generation of reward-specific behaviors. However, how sensory neurons communicate information about L-arabinose quality and concentration—features relevant for long-term memory—remains unknown. DOI: http://dx.doi.org/10.7554/eLife.22283.001 PMID:28005005

Big Data Analytics for a Smart Green Infrastructure Strategy

NASA Astrophysics Data System (ADS)

Barrile, Vincenzo; Bonfa, Stefano; Bilotta, Giuliana

2017-08-01

As well known, Big Data is a term for data sets so large or complex that traditional data processing applications aren’t sufficient to process them. The term “Big Data” is referred to using predictive analytics. It is often related to user behavior analytics, or other advanced data analytics methods which from data extract value, and rarely to a particular size of data set. This is especially true for the huge amount of Earth Observation data that satellites constantly orbiting the earth daily transmit.

Conceptual Design of an Enlisted Force Management System for the Air Force.

DTIC Science & Technology

1983-08-01

system will be ected toward qrade restructurisq, personne planniuq, and personnel proqrammiaq. Accossion Por NT1 - rPAS:T LBy- Distribhition/ Availability...used as loss predictors are stable enough that one can assign mean values to a cell in the inventory (for medium-term prediction), and which...characteristics require expansion of the number of cells ? We expect that the first- term force will be divided into more cells than the career force. 5.5. DATA TO

C-Arm Cone-Beam CT-Guided Transthoracic Lung Core Needle Biopsy as a Standard Diagnostic Tool

PubMed Central

Jaconi, Marta; Pagni, Fabio; Vacirca, Francesco; Leni, Davide; Corso, Rocco; Cortinovis, Diego; Bidoli, Paolo; Bono, Francesca; Cuttin, Maria S.; Valente, Maria G.; Pesci, Alberto; Bedini, Vittorio A.; Leone, Biagio E.

2015-01-01

Abstract C-arm cone-beam computed tomography (CT)-guided transthoracic lung core needle biopsy (CNB) is a safe and accurate procedure for the evaluation of patients with pulmonary nodules. This article will focus on the clinical features related to CNB in terms of diagnostic performance and complication rate. Moreover, the concept of categorizing pathological diagnosis into 4 categories, which could be used for clinical management, follow-up, and quality assurance is also introduced. We retrospectively collected data regarding 375 C-arm cone-beam CT-guided CNBs from January 2010 and June 2014. Clinical and radiological variables were evaluated in terms of success or failure rate. Pathological reports were inserted in 4 homogenous groups (nondiagnostic-L1, benign-L2, malignant not otherwise specified-L3, and malignant with specific histotype-L4), defining for each category a hierarchy of suggested actions. The sensitivity, specificity, and positive and negative predictive value and accuracy for patients subjected to CNBs were of 96.8%, 100%, 100%, 100%, and 97.2%, respectively. Roughly 75% of our samples were diagnosed as malignant, with 60% lung adenocarcinoma diagnoses. Molecular analyses were performed on 85 malignant samples to verify applicability of targeted therapy. The rate of “nondiagnostic” samples was 12%. C-arm cone-beam CT-guided transthoracic lung CNB can represent the gold standard for the diagnostic evaluation of pulmonary nodules. A clinical and pathological multidisciplinary evaluation of CNBs was needed in terms of integration of radiological, histological, and oncological data. This approach provided exceptional performances in terms of specificity, positive and negative predictive values; sensitivity in our series was lower compared with other large studies, probably due to the application of strong criteria of adequacy for CNBs (L1 class rate). The satisfactory rate of collected material was evaluated not only in terms of merely diagnostic performances but also for predictive results by molecular analysis. PMID:25816042

C-arm cone-beam CT-guided transthoracic lung core needle biopsy as a standard diagnostic tool: an observational study.

PubMed

Jaconi, Marta; Pagni, Fabio; Vacirca, Francesco; Leni, Davide; Corso, Rocco; Cortinovis, Diego; Bidoli, Paolo; Bono, Francesca; Cuttin, Maria S; Valente, Maria G; Pesci, Alberto; Bedini, Vittorio A; Leone, Biagio E

2015-03-01

C-arm cone-beam computed tomography (CT)-guided transthoracic lung core needle biopsy (CNB) is a safe and accurate procedure for the evaluation of patients with pulmonary nodules. This article will focus on the clinical features related to CNB in terms of diagnostic performance and complication rate. Moreover, the concept of categorizing pathological diagnosis into 4 categories, which could be used for clinical management, follow-up, and quality assurance is also introduced. We retrospectively collected data regarding 375 C-arm cone-beam CT-guided CNBs from January 2010 and June 2014. Clinical and radiological variables were evaluated in terms of success or failure rate. Pathological reports were inserted in 4 homogenous groups (nondiagnostic--L1, benign--L2, malignant not otherwise specified--L3, and malignant with specific histotype--L4), defining for each category a hierarchy of suggested actions. The sensitivity, specificity, and positive and negative predictive value and accuracy for patients subjected to CNBs were of 96.8%, 100%, 100%, 100%, and 97.2%, respectively. Roughly 75% of our samples were diagnosed as malignant, with 60% lung adenocarcinoma diagnoses. Molecular analyses were performed on 85 malignant samples to verify applicability of targeted therapy. The rate of "nondiagnostic" samples was 12%. C-arm cone-beam CT-guided transthoracic lung CNB can represent the gold standard for the diagnostic evaluation of pulmonary nodules. A clinical and pathological multidisciplinary evaluation of CNBs was needed in terms of integration of radiological, histological, and oncological data. This approach provided exceptional performances in terms of specificity, positive and negative predictive values; sensitivity in our series was lower compared with other large studies, probably due to the application of strong criteria of adequacy for CNBs (L1 class rate). The satisfactory rate of collected material was evaluated not only in terms of merely diagnostic performances but also for predictive results by molecular analysis.

Response of urinary liver-type fatty acid-binding protein to contrast media administration has a potential to predict one-year renal outcome in patients with ischemic heart disease.

PubMed

Fujita, Daishi; Takahashi, Masao; Doi, Kent; Abe, Mitsuru; Tazaki, Junichi; Kiyosue, Arihiro; Myojo, Masahiro; Ando, Jiro; Fujita, Hideo; Noiri, Eisei; Sugaya, Takeshi; Hirata, Yasunobu; Komuro, Issei

2015-05-01

Urinary liver-type fatty acid-binding proteins (uL-FABP) have recently been recognized as a useful biomarker for predicting contrast-induced nephropathy. Although accumulating studies have evaluated short-term outcomes, its prognostic value for long-term renal prognosis in patients undergoing coronary angiography (CAG) has not been fully examined. This study aimed to evaluate the predictive value of uL-FABP for long-term renal outcome in patients with ischemic heart disease (IHD). Consecutive 24 patients with impaired renal function (serum creatinine >1.2 mg/dL) who underwent CAG were enrolled. uL-FABP was measured before CAG, 24 and 48 h after CAG. The changes in estimated glomerular filtration rate (eGFR) throughout CAG and at 1 year later were compared with the uL-FABP levels. The patients with a greater decrease in eGFR 1 year later had higher uL-FABP levels at all points, but only the value at 48 h after CAG reached statistical significance (lower vs. higher decreased eGFR group, 4.61 ± 3.87 vs. 17.71 ± 12.96; P < 0.01). Measurement of uL-FABP at 48 h after CAG (48h-uL-FABP) showed better correlation with the change in eGFR (pre-CAG uL-FABP vs. 48h-uL-FABP: R = 0.27, P = 0.20 vs. R = 0.65, P < 0.01). Moreover, the high-pre and high-48h-uL-FABP group showed a significantly larger decrease in eGFR compared with the high-pre and low-48h-uL-FABP group (change in eGFR; 8.12 ± 4.06 vs. 1.25 ± 2.23 mL/min/1.73 m2, P < 0.01), although the baseline eGFR levels were similar between these two groups. In this pilot study, measurement of uL-FABP levels at 48 h after CAG may be useful in detecting renal damage, and in predicting 1-year renal outcome in IHD patients undergoing CAG.

Is Ecosystem-Atmosphere Observation in Long-Term Networks actually Science?

NASA Astrophysics Data System (ADS)

Schmid, H. P. E.

2015-12-01

Science uses observations to build knowledge by testable explanations and predictions. The "scientific method" requires controlled systematic observation to examine questions, hypotheses and predictions. Thus, enquiry along the scientific method responds to questions of the type "what if …?" In contrast, long-term observation programs follow a different strategy: we commonly take great care to minimize our influence on the environment of our measurements, with the aim to maximize their external validity. We observe what we think are key variables for ecosystem-atmosphere exchange and ask questions such as "what happens next?" or "how did this happen?" This apparent deviation from the scientific method begs the question whether any explanations we come up with for the phenomena we observe are actually contributing to testable knowledge, or whether their value remains purely anecdotal. Here, we present examples to argue that, under certain conditions, data from long-term observations and observation networks can have equivalent or even higher scientific validity than controlled experiments. Internal validity is particularly enhanced if observations are combined with modeling. Long-term observations of ecosystem-atmosphere fluxes identify trends and temporal scales of variability. Observation networks reveal spatial patterns and variations, and long-term observation networks combine both aspects. A necessary condition for such observations to gain validity beyond the anecdotal is the requirement that the data are comparable: a comparison of two measured values, separated in time or space, must inform us objectively whether (e.g.) one value is larger than the other. In turn, a necessary condition for the comparability of data is the compatibility of the sensors and procedures used to generate them. Compatibility ensures that we compare "apples to apples": that measurements conducted in identical conditions give the same values (within suitable uncertainty intervals). In principle, a useful tool to achieve comparability and compatibility is the standardization of sensors and methods. However, due to the diversity of ecosystems and settings, standardization in ecosystem-atmosphere exchange is difficult. We discuss some of the challenges and pitfalls of standardization across networks.

Beyond SaGMRotI: Conversion to SaArb, SaSN, and SaMaxRot

USGS Publications Warehouse

Watson-Lamprey, J. A.; Boore, D.M.

2007-01-01

In the seismic design of structures, estimates of design forces are usually provided to the engineer in the form of elastic response spectra. Predictive equations for elastic response spectra are derived from empirical recordings of ground motion. The geometric mean of the two orthogonal horizontal components of motion is often used as the response value in these predictive equations, although it is not necessarily the most relevant estimate of forces within the structure. For some applications it is desirable to estimate the response value on a randomly chosen single component of ground motion, and in other applications the maximum response in a single direction is required. We give adjustment factors that allow converting the predictions of geometric-mean ground-motion predictions into either of these other two measures of seismic ground-motion intensity. In addition, we investigate the relation of the strike-normal component of ground motion to the maximum response values. We show that the strike-normal component of ground motion seldom corresponds to the maximum horizontal-component response value (in particular, at distances greater than about 3 km from faults), and that focusing on this case in exclusion of others can result in the underestimation of the maximum component. This research provides estimates of the maximum response value of a single component for all cases, not just near-fault strike-normal components. We provide modification factors that can be used to convert predictions of ground motions in terms of the geometric mean to the maximum spectral acceleration (SaMaxRot) and the random component of spectral acceleration (SaArb). Included are modification factors for both the mean and the aleatory standard deviation of the logarithm of the motions.

Potential uncertainty reduction in model-averaged benchmark dose estimates informed by an additional dose study.

PubMed

Shao, Kan; Small, Mitchell J

2011-10-01

A methodology is presented for assessing the information value of an additional dosage experiment in existing bioassay studies. The analysis demonstrates the potential reduction in the uncertainty of toxicity metrics derived from expanded studies, providing insights for future studies. Bayesian methods are used to fit alternative dose-response models using Markov chain Monte Carlo (MCMC) simulation for parameter estimation and Bayesian model averaging (BMA) is used to compare and combine the alternative models. BMA predictions for benchmark dose (BMD) are developed, with uncertainty in these predictions used to derive the lower bound BMDL. The MCMC and BMA results provide a basis for a subsequent Monte Carlo analysis that backcasts the dosage where an additional test group would have been most beneficial in reducing the uncertainty in the BMD prediction, along with the magnitude of the expected uncertainty reduction. Uncertainty reductions are measured in terms of reduced interval widths of predicted BMD values and increases in BMDL values that occur as a result of this reduced uncertainty. The methodology is illustrated using two existing data sets for TCDD carcinogenicity, fitted with two alternative dose-response models (logistic and quantal-linear). The example shows that an additional dose at a relatively high value would have been most effective for reducing the uncertainty in BMA BMD estimates, with predicted reductions in the widths of uncertainty intervals of approximately 30%, and expected increases in BMDL values of 5-10%. The results demonstrate that dose selection for studies that subsequently inform dose-response models can benefit from consideration of how these models will be fit, combined, and interpreted. © 2011 Society for Risk Analysis.

Value of semen parameters, with special reference to TNF-α, in predicting the quality of boar semen after short-term storage.

PubMed

Mrkun, Janko; Kosec, Marjan; Zrimšek, Petra

2013-06-01

The aim of this study was to address the question whether changes in boar semen quality after short-term storage could be predicted on the basis of standard semen parameters and TNF-α level determined on the day of semen collection under commercial conditions. Progressive motility showed the highest positive correlation with morphology on day 0 of collection, and progressive motility on day 3 (P < 0.05) showed a negative correlation with acrosome abnormalities (P < 0.05). According to the area under receiver operating characteristics (ROC) curves (AUCs), progressive motility could also be used in predicting semen quality after 3 days of storage (AUC > 0.5; P < 0.05). TNF-α in seminal plasma is the only parameter measured on day 0 to show a significant correlation with the percentage of viable spermatozoa after 3 days of semen storage (r = 0.495, P < 0.05). ROC analysis shows that TNF-α level is helpful in discriminating viability outcome after semen storage (AUC = 0.94, P < 0.001). We can predict with 92.35% certainty that fresh semen samples with more than 150 pg/ml of TNF-α in the seminal plasma will retain more than 85% of viable spermatozoa after 3 days of storage. Thus, TNF-α can contribute to predicting the quality of short-term stored semen.

Text mining approach to predict hospital admissions using early medical records from the emergency department.

PubMed

Lucini, Filipe R; S Fogliatto, Flavio; C da Silveira, Giovani J; L Neyeloff, Jeruza; Anzanello, Michel J; de S Kuchenbecker, Ricardo; D Schaan, Beatriz

2017-04-01

Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ 2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Prediction of Long Term Degradation of Insulating Materials

DTIC Science & Technology

2015-05-01

may be installed in less than half the time it would take to install board and mem- brane systems. The fiberglass tested had a paper coated backing...humidity between the plywood and the ccSPF. In dryer conditions, ccSPF foam initially increases in R-value, and then proceeds to degrade in R-value. This...frequency number in the spectra. Figures 4-17 and 4-18 include an overlay of IR spectra of the three aerogel composites at two different humidity

Low-flow characteristics of streams in Virginia

USGS Publications Warehouse

Hayes, Donald C.

1991-01-01

Streamflow data were collected and low-flow characteristics computed for 715 gaged sites in Virginia Annual minimum average 7-consecutive-day flows range from 0 to 2,195 cubic feet per second for a 2-year recurrence interval and from 0 to 1,423 cubic feet per second for a 10-year recurrence interval. Drainage areas range from 0.17 to 7,320 square miles. Existing and discontinued gaged sites are separated into three types: long-term continuous-record sites, short-term continuous-record sites, and partial-record sites. Low-flow characteristics for long-term continuous-record sites are determined from frequency curves of annual minimum average 7-consecutive-day flows . Low-flow characteristics for short-term continuous-record sites are estimated by relating daily mean base-flow discharge values at a short-term site to concurrent daily mean discharge values at nearby long-term continuous-record sites having similar basin characteristics . Low-flow characteristics for partial-record sites are estimated by relating base-flow measurements to daily mean discharge values at long-term continuous-record sites. Information from the continuous-record sites and partial-record sites in Virginia are used to develop two techniques for estimating low-flow characteristics at ungaged sites. A flow-routing method is developed to estimate low-flow values at ungaged sites on gaged streams. Regional regression equations are developed for estimating low-flow values at ungaged sites on ungaged streams. The flow-routing method consists of transferring low-flow characteristics from a gaged site, either upstream or downstream, to a desired ungaged site. A simple drainage-area proration is used to transfer values when there are no major tributaries between the gaged and ungaged sites. Standard errors of estimate for108 test sites are 19 percent of the mean for estimates of low-flow characteristics having a 2-year recurrence interval and 52 percent of the mean for estimates of low-flow characteristics having a 10-year recurrence interval . A more complex transfer method must be used when major tributaries enter the stream between the gaged and ungaged sites. Twenty-four stream networks are analyzed, and predictions are made for 84 sites. Standard errors of estimate are 15 percent of the mean for estimates of low-flow characteristics having a 2-year recurrence interval and 22 percent of the mean for estimates of low-flow characteristics having a 10-year recurrence interval. Regional regression equations were developed for estimating low-flow values at ungaged sites on ungaged streams. The State was divided into eight regions on the basis of physiography and geographic grouping of the residuals computed in regression analyses . Basin characteristics that were significant in the regression analysis were drainage area, rock type, and strip-mined area. Standard errors of prediction range from 60 to139 percent for estimates of low-flow characteristics having a 2-year recurrence interval and 90 percent to 172 percent for estimates of low-flow characteristics having a 10-year recurrence interval.

On the long-term stability of terrestrial reference frame solutions based on Kalman filtering

NASA Astrophysics Data System (ADS)

Soja, Benedikt; Gross, Richard S.; Abbondanza, Claudio; Chin, Toshio M.; Heflin, Michael B.; Parker, Jay W.; Wu, Xiaoping; Nilsson, Tobias; Glaser, Susanne; Balidakis, Kyriakos; Heinkelmann, Robert; Schuh, Harald

2018-06-01

The Global Geodetic Observing System requirement for the long-term stability of the International Terrestrial Reference Frame is 0.1 mm/year, motivated by rigorous sea level studies. Furthermore, high-quality station velocities are of great importance for the prediction of future station coordinates, which are fundamental for several geodetic applications. In this study, we investigate the performance of predictions from very long baseline interferometry (VLBI) terrestrial reference frames (TRFs) based on Kalman filtering. The predictions are computed by extrapolating the deterministic part of the coordinate model. As observational data, we used over 4000 VLBI sessions between 1980 and the middle of 2016. In order to study the predictions, we computed VLBI TRF solutions only from the data until the end of 2013. The period of 2014 until 2016.5 was used to validate the predictions of the TRF solutions against the measured VLBI station coordinates. To assess the quality, we computed average WRMS values from the coordinate differences as well as from estimated Helmert transformation parameters, in particular, the scale. We found that the results significantly depend on the level of process noise used in the filter. While larger values of process noise allow the TRF station coordinates to more closely follow the input data (decrease in WRMS of about 45%), the TRF predictions exhibit larger deviations from the VLBI station coordinates after 2014 (WRMS increase of about 15%). On the other hand, lower levels of process noise improve the predictions, making them more similar to those of solutions without process noise. Furthermore, our investigations show that additionally estimating annual signals in the coordinates does not significantly impact the results. Finally, we computed TRF solutions mimicking a potential real-time TRF and found significant improvements over the other investigated solutions, all of which rely on extrapolating the coordinate model for their predictions, with WRMS reductions of almost 50%.

Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

PubMed

Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

A Quality Classification System for Young Hardwood Trees - The First Step in Predicting Future Products

Treesearch

David L. Sonderman; Robert L. Brisbin

1978-01-01

Forest managers have no objective way to determine the relative value of culturally treated forest stands in terms of product potential. This paper describes the first step in the development of a quality classification system based on the measurement of individual tree characteristics for young hardwood stands.

Attributions and Coping in Sexually Abused Adolescents Referred for Group Treatment

ERIC Educational Resources Information Center

Daigneault, Isabelle; Hebert, Martine; Tourigny, Marc

2006-01-01

This study aims to assess the predictive value of two sets of variables, self-attributions, and coping behaviors, on sexually abused (SA) teenagers' functioning, while controlling for abuse-related and family variables. A total of 103 female adolescents completed self-report measures to assess their psychological functioning in terms of anxiety,…

A new approximate sum rule for bulk alloy properties

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Ferrante, John

1991-01-01

A new, approximate sum rule is introduced for determining bulk properties of multicomponent systems, in terms of the pure components properties. This expression is applied for the study of lattice parameters, cohesive energies, and bulk moduli of binary alloys. The correct experimental trends (i.e., departure from average values) are predicted in all cases.

The Role of Identity Development, Values, and Costs in College STEM Retention

ERIC Educational Resources Information Center

Perez, Tony; Cromley, Jennifer G.; Kaplan, Avi

2014-01-01

The current short-term longitudinal study investigated the role of college students' identity development and motivational beliefs in predicting their chemistry achievement and intentions to leave science, technology, engineering, and math (STEM) majors. We collected 4 waves of data over 1 semester from 363 diverse undergraduate STEM students…

Public-Interest Values and Program Sustainability: Some Implications for Evaluation Practice

ERIC Educational Resources Information Center

Chelimsky, Eleanor

2014-01-01

Evaluating the longer-term sustainability of government programs and policies seems in many ways to go beyond the boundaries of typical evaluation practice. Not only have intervention failures over time been difficult to predict, but the question of sustainability itself tends to fall outside current evaluation thinking, timing and functions. This…

Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

PubMed

Zhang, Buzhong; Li, Linqing; Lü, Qiang

2018-05-25

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson's correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

Long-term observations of cloud condensation nuclei in the Amazon rain forest

NASA Astrophysics Data System (ADS)

Pöhlker, Mira L.; Pöhlker, Christopher; Ditas, Florian; Klimach, Thomas; Hrabe de Angelis, Isabella; Brito, Joel; Carbone, Samara; Cheng, Yafang; Martin, Scot T.; Moran-Zuloaga, Daniel; Rose, Diana; Saturno, Jorge; Su, Hang; Thalman, Ryan; Walter, David; Wang, Jian; Barbosa, Henrique; Artaxo, Paulo; Andreae, Meinrat O.; Pöschl, Ulrich

2017-04-01

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014 - Feb 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site [1,2]. The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol. The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes. For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data. In addition, we analyzed the CCN short-term variability in relation to air mass changes as well as aerosol emission and transformation processes. The CCN short term variability is presented for selected case studies, which analyze particularly interesting and characteristic events/conditions in the Amazon region. References: [1] Andreae, M. O., et al. (2015), Atmos. Chem. Phys., 15, 10723-10776. [2] Pöhlker, M. L.., et al. (2016), Atmos. Chem. Phys., 16, 15709-15740.

Predicting hydrologic function with the streamwater mircobiome

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2017-12-01

Recent advances in microbiology allow for rapid and cost-effective determination of the presence of a nearly limitless number of bacterial (and other) species within a water sample. Here, we posit that the quasi-unique taxonomic composition of the aquatic microbiome is an emergent property of a catchment that contains information about hydrologic function at multiple temporal and spatial scales, and term this approach `genohydrolgy.' As first a genohydrology case study, we show that the relative abundance of bacterial species within different operational taxonomic units (OTUs) from six large arctic rivers can be used to predict river discharge at monthly and longer timescales. Using only OTU abundance information and a machine-learning algorithm trained on OTU and discharge data from the other five rivers, our genohydrology approach is able to predict mean monthly discharge values throughout the year with an average Nash-Sutcliffe efficiency (NSE) of 0.50, while the recurrence interval of extreme flows at longer times scales in these rivers was predicted with an NSE of 0.04. This approach demonstrates considerable improvement over prediction of these quantities in each river based only on discharge data from the other five (our null hypothesis), which had average NSE values of -1.19 and -5.50 for the seasonal and recurrence interval discharge values, respectively. Overall the genohydrology approach demonstrates that bacterial diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Prognostic value of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in acute pulmonary embolism: a systematic review and meta-analysis.

PubMed

Wang, Qian; Ma, Junfen; Jiang, Zhiyun; Ming, Liang

2018-02-01

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been reported to predict prognosis of acute pulmonary embolism (PE). However, the prognostic value of NLR and PLR remained inconsistent between studies. The aim of this meta-analysis was to assess the prognostic role of NLR and PLR in acute PE. We systematically searched Pubmed, Embase, Web of Science and CNKI for relative literature up to March 2017. The pooled statistics for all outcomes were expressed as odds ratio (OR) and 95% confidence intervals (95% CI). The statistical analyses were performed using Review Manager 5.3.5 analysis software and Stata software. Totally 7 eligible studies consisting of 2323 patients were enrolled in our meta-analysis. Elevated NLR was significantly associated with overall (short-term and long-term) mortality (OR 10.13, 95% CI 6.57-15.64, P<0.001) and short-term (in-hospital and 30 days) mortality (OR 8.43, 95% CI 5.23-13.61, P<0.001). And elevated PLR was significantly associated with overall mortality (OR 6.32, 95% CI 4.52-8.84, P<0.001), short-term mortality (OR 6.69, 95% CI 2.86-15.66, P<0.001) and long-term mortality (OR 6.11, 95% CI 3.90-9.55, P<0.001). Our meta-analysis revealed that NLR and PLR are promising biomarkers in predicting prognosis in acute PE patients. We suggest NLR and PLR be used routinely in the PE prognostic assessment.

A life prediction methodology for encapsulated solar cells

NASA Technical Reports Server (NTRS)

Coulbert, C. D.

1978-01-01

This paper presents an approach to the development of a life prediction methodology for encapsulated solar cells which are intended to operate for twenty years or more in a terrestrial environment. Such a methodology, or solar cell life prediction model, requires the development of quantitative intermediate relationships between local environmental stress parameters and the basic chemical mechanisms of encapsulant aging leading to solar cell failures. The use of accelerated/abbreviated testing to develop these intermediate relationships and in revealing failure modes is discussed. Current field and demonstration tests of solar cell arrays and the present laboratory tests to qualify solar module designs provide very little data applicable to predicting the long-term performance of encapsulated solar cells. An approach to enhancing the value of such field tests to provide data for life prediction is described.

Preoperative galactose elimination capacity predicts complications and survival after hepatic resection.

PubMed

Redaelli, Claudio A; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W; Reichen, Jürg

2002-01-01

To analyze a single center's 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection.

Preoperative Galactose Elimination Capacity Predicts Complications and Survival After Hepatic Resection

PubMed Central

Redaelli, Claudio A.; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W.; Reichen, Jürg

2002-01-01

Objective To analyze a single center’s 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Summary Background Data Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. Methods In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. Results In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. Conclusions This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection. PMID:11753045

Otoacoustic emissions versus audiometry in monitoring hearing loss after long-term noise exposure - a systematic review.

PubMed

Helleman, Hiske W; Eising, Hilde; Limpens, Jacqueline; Dreschler, Wouter A

2018-03-15

Objectives The objective of this systematic review was to compare otoacoustic emissions (OAE) with audiometry in their effectiveness to monitor effects of long-term noise exposure on hearing. Methods We conducted a systematic search of MEDLINE, Embase and the non-MEDLINE subset of PubMed up to March 2016 to identify longitudinal studies on effects of noise exposure on hearing as determined by both audiometry and OAE. Results This review comprised 13 articles, with 30-350 subjects in the longitudinal analysis. A meta-analysis could not be performed because the studies were very heterogeneous in terms of measurement paradigms, follow-up time, age of included subjects, inclusion of data points, outcome parameters and method of analysis. Overall there seemed to be small changes in both audiometry and OAE over time. Individual shifts were detected by both methods but a congruent pattern could not be observed. Some studies found that initial abnormal or low-level emissions might predict future hearing loss but at the cost of low specificity due to a high number of false positives. Other studies could not find such predictive value. Conclusions The reported heterogeneity in the studies calls for more uniformity in including, reporting and analyzing longitudinal data for audiometry and OAE. For the overall results, both methods showed small changes from baseline towards a deterioration in hearing. OAE could not reliably detect threshold shifts at individual level. With respect to the predictive value of OAE, the evidence was not conclusive and studies were not in agreement. The reported predictors had low specificity.

Prediction of near-term breast cancer risk using local region-based bilateral asymmetry features in mammography

NASA Astrophysics Data System (ADS)

Li, Yane; Fan, Ming; Li, Lihua; Zheng, Bin

2017-03-01

This study proposed a near-term breast cancer risk assessment model based on local region bilateral asymmetry features in Mammography. The database includes 566 cases who underwent at least two sequential FFDM examinations. The `prior' examination in the two series all interpreted as negative (not recalled). In the "current" examination, 283 women were diagnosed cancers and 283 remained negative. Age of cancers and negative cases completely matched. These cases were divided into three subgroups according to age: 152 cases among the 37-49 age-bracket, 220 cases in the age-bracket 50- 60, and 194 cases with the 61-86 age-bracket. For each image, two local regions including strip-based regions and difference-of-Gaussian basic element regions were segmented. After that, structural variation features among pixel values and structural similarity features were computed for strip regions. Meanwhile, positional features were extracted for basic element regions. The absolute subtraction value was computed between each feature of the left and right local-regions. Next, a multi-layer perception classifier was implemented to assess performance of features for prediction. Features were then selected according stepwise regression analysis. The AUC achieved 0.72, 0.75 and 0.71 for these 3 age-based subgroups, respectively. The maximum adjustable odds ratios were 12.4, 20.56 and 4.91 for these three groups, respectively. This study demonstrate that the local region-based bilateral asymmetry features extracted from CC-view mammography could provide useful information to predict near-term breast cancer risk.

Measuring short-term and long-term physiological stress effects by cortisol reactivity in saliva and hair.

PubMed

van Holland, Berry J; Frings-Dresen, Monique H W; Sluiter, Judith K

2012-11-01

The aims of this study were to investigate (1) the concurrent relationship between short-term and long-term stress reactivity measured by cortisol excretion and (2) the relationship of these physiological stress effects with self-reported stress and need for recovery after work (NFR). Participants were production workers in the meat-processing industry. Short-term cortisol excretion was calculated by summing 18 saliva samples, sampled over a 3-day period. Samples were delivered by 37 participants. Twenty-nine of them also supplied one hair sample of at least 3 cm in length for an analysis of long-term (3 months) cortisol excretion. All of them filled in a short questionnaire on self-reported stress and NFR. Self-reported stress was assessed by a three-item stress screener; NFR was assessed by an 11-item scale. Short-term and long-term cortisol excretion are significantly, but moderately, associated (r = 0.41, P = 0.03). Short-term and long-term cortisol excretion correlated weakly to self-reported stress and NFR (correlations varied from -0.04 to 0.21). Short-term and long-term physiological stress excretion levels are moderately associated. Physiological stress effects assessed from saliva and hair cannot be used interchangeably with self-reported stress because they only correlate weakly. To better predict long-term cortisol excretion in workers, the predictive value of short-term cortisol excretion must be evaluated in a prognostic longitudinal study in a working population.

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pöhlker, Mira L.; Pöhlker, Christopher; Ditas, Florian

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172more » nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.« less

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

DOE PAGES

Pöhlker, Mira L.; Pöhlker, Christopher; Ditas, Florian; ...

2016-12-20

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172more » nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.« less

A comparison of positive and negative alcohol expectancy and value and their multiplicative composite as predictors of post-treatment abstinence survivorship.

PubMed

Jones, B T; McMahon, J

1996-01-01

Within social learning theory, positive alcohol expectancies represent motivation to drink and negative expectancies, motivation to restrain. It is also recognized that a subjective evaluation of expectancies ought to moderate their impact, although the evidence for this in social drinkers is problematic. This paper addresses the speculation that the moderating effect will be more evident in clinical populations. This study shows that (i) both expectancy and value reliably, independently and equally predict clients' abstinence survivorship following discharge from a treatment programme (and that this is almost entirely confined to the negative rather than positive terms). When (ii) expectancy evaluations are processed against expectancy through multiplicative composites (i.e. expectancy x value), their predictive power is only equivalent to either expectancy or value on its own. However (iii) when the multiplicative composite is assessed following the statistical guidelines advocated by Evans (1991) (i.e. within the same model as its constituents, expectancy and value) the increase in outcome variance explained by its inclusion is negligible and casts doubt upon its use in alcohol research. This does not appear to apply to value, however, and its possible role in treatment is discussed.

A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN

NASA Astrophysics Data System (ADS)

Fan, J.; Li, Q.; Hou, J.; Feng, X.; Karimian, H.; Lin, S.

2017-10-01

Time series data in practical applications always contain missing values due to sensor malfunction, network failure, outliers etc. In order to handle missing values in time series, as well as the lack of considering temporal properties in machine learning models, we propose a spatiotemporal prediction framework based on missing value processing algorithms and deep recurrent neural network (DRNN). By using missing tag and missing interval to represent time series patterns, we implement three different missing value fixing algorithms, which are further incorporated into deep neural network that consists of LSTM (Long Short-term Memory) layers and fully connected layers. Real-world air quality and meteorological datasets (Jingjinji area, China) are used for model training and testing. Deep feed forward neural networks (DFNN) and gradient boosting decision trees (GBDT) are trained as baseline models against the proposed DRNN. Performances of three missing value fixing algorithms, as well as different machine learning models are evaluated and analysed. Experiments show that the proposed DRNN framework outperforms both DFNN and GBDT, therefore validating the capacity of the proposed framework. Our results also provides useful insights for better understanding of different strategies that handle missing values.

Three dimensional finite temperature SU(3) gauge theory near the phase transition

NASA Astrophysics Data System (ADS)

Bialas, P.; Daniel, L.; Morel, A.; Petersson, B.

2013-06-01

We have measured the correlation function of Polyakov loops on the lattice in three dimensional SU(3) gauge theory near its finite temperature phase transition. Using a new and powerful application of finite size scaling, we furthermore extend the measurements of the critical couplings to considerably larger values of the lattice sizes, both in the temperature and space directions, than was investigated earlier in this theory. With the help of these measurements we perform a detailed finite size scaling analysis, showing that for the critical exponents of the two dimensional three state Potts model the mass and the susceptibility fall on unique scaling curves. This strongly supports the expectation that the gauge theory is in the same universality class. The Nambu-Goto string model on the other hand predicts that the exponent ν has the mean field value, which is quite different from the value in the abovementioned Potts model. Using our values of the critical couplings we also determine the continuum limit of the value of the critical temperature in terms of the square root of the zero temperature string tension. This value is very near to the prediction of the Nambu-Goto string model in spite of the different critical behaviour.

Structure-Activity Relationship Models for Rat Carcinogenesis and Assessing the Role Mutagens Play in Model Predictivity

PubMed Central

Carrasquer, C. Alex; Batey, Kaylind; Qamar, Shahid; Cunningham, Albert R.; Cunningham, Suzanne L.

2016-01-01

We previously demonstrated that fragment based cat-SAR carcinogenesis models consisting solely of mutagenic or non-mutagenic carcinogens varied greatly in terms of their predictive accuracy. This led us to investigate how well the rat cancer cat-SAR model predicted mutagens and non-mutagens in their learning set. Four rat cancer cat-SAR models were developed: Complete Rat, Transgender Rat, Male Rat, and Female Rat, with leave-one-out (LOO) validation concordance values of 69%, 74%, 67%, and 73%, respectively. The mutagenic carcinogens produced concordance values in the range of 69–76% as compared to only 47–53% for non-mutagenic carcinogens. As a surrogate for mutagenicity comparisons between single site and multiple site carcinogen SAR models was analyzed. The LOO concordance values for models consisting of 1-site, 2-site, and 4+-site carcinogens were 66%, 71%, and 79%, respectively. As expected, the proportion of mutagens to non-mutagens also increased, rising from 54% for 1-site to 80% for 4+-site carcinogens. This study demonstrates that mutagenic chemicals, in both SAR learning sets and test sets, are influential in assessing model accuracy. This suggests that SAR models for carcinogens may require a two-step process in which mutagenicity is first determined before carcinogenicity can be accurately predicted. PMID:24697549

Modeling and predicting the biofilm formation of Salmonella Virchow with respect to temperature and pH.

PubMed

Ariafar, M Nima; Buzrul, Sencer; Akçelik, Nefise

2016-03-01

Biofilm formation of Salmonella Virchow was monitored with respect to time at three different temperature (20, 25 and 27.5 °C) and pH (5.2, 5.9 and 6.6) values. As the temperature increased at a constant pH level, biofilm formation decreased while as the pH level increased at a constant temperature, biofilm formation increased. Modified Gompertz equation with high adjusted determination coefficient (Radj(2)) and low mean square error (MSE) values produced reasonable fits for the biofilm formation under all conditions. Parameters of the modified Gompertz equation could be described in terms of temperature and pH by use of a second order polynomial function. In general, as temperature increased maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation decreased; whereas, as pH increased; maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation increased. Two temperature (23 and 26 °C) and pH (5.3 and 6.3) values were used up to 24 h to predict the biofilm formation of S. Virchow. Although the predictions did not perfectly match with the data, reasonable estimates were obtained. In principle, modeling and predicting the biofilm formation of different microorganisms on different surfaces under various conditions could be possible.

Triiodothyronine and brain natriuretic peptide: similar long-term prognostic values for chronic heart failure.

PubMed

Kozdag, Guliz; Ertas, Gokhan; Kilic, Teoman; Acar, Eser; Sahin, Tayfun; Ural, Dilek

2010-01-01

Although low levels of free triiodothyronine and high levels of brain natriuretic peptide have been shown as independent predictors of death in chronic heart failure patients, few studies have compared their prognostic values. The aim of this prospective study was to measure free triiodothyronine and brain natriuretic peptide levels and to compare their prognostic values among such patients.A total of 334 patients (mean age, 62 ± 13 yr; 218 men) with ischemic and nonischemic dilated cardiomyopathy were included in the study. The primary endpoint was a major cardiac event.During the follow-up period, 92 patients (28%) experienced a major cardiac event. Mean free triiodothyronine levels were lower and median brain natriuretic peptide levels were higher in patients with major cardiac events than in those without. A significant negative correlation was found between free triiodothyronine and brain natriuretic peptide levels. Receiver operating characteristic curve analysis showed that the predictive cutoff values were < 2.12 pg/mL for free triiodothyronine and > 686 pg/mL for brain natriuretic peptide. Cumulative survival was significantly lower among patients with free triiodothyronine < 2.12 pg/mL and among patients with brain natriuretic peptide > 686 pg/mL. In multivariate analysis, the significant independent predictors of major cardiac events were age, free triiodothyronine, and brain natriuretic peptide.In the present study, free triiodothyronine and brain natriuretic peptide had similar prognostic values for predicting long-term prognosis in chronic heart failure patients. These results also suggested that combining these biomarkers may provide an important risk indicator for patients with heart failure.

The significance of serum urea and renal function in patients with heart failure.

PubMed

Gotsman, Israel; Zwas, Donna; Planer, David; Admon, Dan; Lotan, Chaim; Keren, Andre

2010-07-01

Renal function and urea are frequently abnormal in patients with heart failure (HF) and are predictive of increased mortality. The relative importance of each parameter is less clear. We prospectively compared the predictive value of renal function and serum urea on clinical outcome in patients with HF. Patients hospitalized with definite clinical diagnosis of HF (n = 355) were followed for short-term (1 yr) and long-term (mean, 6.5 yr) survival and HF rehospitalization. Increasing tertiles of discharge estimated glomerular filtration rate (eGFR) were an independent predictor of increased long-term survival (hazard ratio [HR], 0.65; 95% confidence interval [CI], 0.47-0.91; p = 0.01) but not short-term survival. Admission and discharge serum urea and blood urea nitrogen (BUN)/creatinine ratio were predictors of reduced short- and long-term survival on multivariate Cox regression analysis. Increasing tertiles of discharge urea were a predictor of reduced 1-year survival (HR, 2.13; 95% CI, 1.21-3.73; p = 0.009) and long-term survival (HR, 1.93; 95% CI, 1.37-2.71; p < 0.0001). Multivariate analysis including discharge eGFR and serum urea demonstrated that only serum urea remained a significant predictor of long-term survival; however, eGFR and BUN/creatinine ratio were both independently predictive of survival. Urea was more discriminative than eGFR in predicting long-term survival by area under the receiver operating characteristic curve (0.803 vs. 0.787; p = 0.01). Increasing tertiles of discharge serum urea and BUN/creatinine were independent predictors of HF rehospitalization and combined death and HF rehospitalization. This study suggests that serum urea is a more powerful predictor of survival than eGFR in patients with HF. This may be due to urea's relation to key biological parameters including renal, hemodynamic, and neurohormonal parameters pertaining to the overall clinical status of the patient with chronic HF.

Predictive Values of the New Sarcopenia Index by the Foundation for the National Institutes of Health Sarcopenia Project for Mortality among Older Korean Adults.

PubMed

Moon, Joon Ho; Kim, Kyoung Min; Kim, Jung Hee; Moon, Jae Hoon; Choi, Sung Hee; Lim, Soo; Lim, Jae-Young; Kim, Ki Woong; Park, Kyong Soo; Jang, Hak Chul

2016-01-01

We evaluated the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project's recommended criteria for sarcopenia's association with mortality among older Korean adults. We conducted a community-based prospective cohort study which included 560 (285 men and 275 women) older Korean adults aged ≥65 years. Muscle mass (appendicular skeletal muscle mass-to-body mass index ratio (ASM/BMI)), handgrip strength, and walking velocity were evaluated in association with all-cause mortality during 6-year follow-up. Both the lowest quintile for each parameter (ethnic-specific cutoff) and FNIH-recommended values were used as cutoffs. Forty men (14.0%) and 21 women (7.6%) died during 6-year follow-up. The deceased subjects were older and had lower ASM, handgrip strength, and walking velocity. Sarcopenia defined by both low lean mass and weakness had a 4.13 (95% CI, 1.69-10.11) times higher risk of death, and sarcopenia defined by a combination of low lean mass, weakness, and slowness had a 9.56 (3.16-28.90) times higher risk of death after adjusting for covariates in men. However, these significant associations were not observed in women. In terms of cutoffs of each parameter, using the lowest quintile showed better predictive values in mortality than using the FNIH-recommended values. Moreover, new muscle mass index, ASM/BMI, provided better prognostic values than ASM/height2 in all associations. New sarcopenia definition by FNIH was better able to predict 6-year mortality among Korean men. Moreover, ethnic-specific cutoffs, the lowest quintile for each parameter, predicted the higher risk of mortality than the FNIH-recommended values.

Predictive Values of the New Sarcopenia Index by the Foundation for the National Institutes of Health Sarcopenia Project for Mortality among Older Korean Adults

PubMed Central

Kim, Jung Hee; Moon, Jae Hoon; Choi, Sung Hee; Lim, Soo; Lim, Jae-Young; Kim, Ki Woong; Park, Kyong Soo; Jang, Hak Chul

2016-01-01

Objective We evaluated the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project’s recommended criteria for sarcopenia’s association with mortality among older Korean adults. Methods We conducted a community-based prospective cohort study which included 560 (285 men and 275 women) older Korean adults aged ≥65 years. Muscle mass (appendicular skeletal muscle mass-to-body mass index ratio (ASM/BMI)), handgrip strength, and walking velocity were evaluated in association with all-cause mortality during 6-year follow-up. Both the lowest quintile for each parameter (ethnic-specific cutoff) and FNIH-recommended values were used as cutoffs. Results Forty men (14.0%) and 21 women (7.6%) died during 6-year follow-up. The deceased subjects were older and had lower ASM, handgrip strength, and walking velocity. Sarcopenia defined by both low lean mass and weakness had a 4.13 (95% CI, 1.69–10.11) times higher risk of death, and sarcopenia defined by a combination of low lean mass, weakness, and slowness had a 9.56 (3.16–28.90) times higher risk of death after adjusting for covariates in men. However, these significant associations were not observed in women. In terms of cutoffs of each parameter, using the lowest quintile showed better predictive values in mortality than using the FNIH-recommended values. Moreover, new muscle mass index, ASM/BMI, provided better prognostic values than ASM/height2 in all associations. Conclusions New sarcopenia definition by FNIH was better able to predict 6-year mortality among Korean men. Moreover, ethnic-specific cutoffs, the lowest quintile for each parameter, predicted the higher risk of mortality than the FNIH-recommended values. PMID:27832145

Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review

PubMed Central

Kim, Bum Jun; Kim, Jung Han; Kim, Hyeong Su; Zang, Dae Young

2017-01-01

The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: ‘kidney or renal’, ‘carcinoma or cancer or neoplasm or malignancy’, ‘von Hippel-Lindau or VHL’, ‘alteration or mutation or methylation’, and ‘prognostic or predictive’. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC. PMID:28103578

Predicting Severity of Acute Kidney Injury in Term Neonates with Perinatal Asphyxia Using Urinary Neutrophil Gelatinase Associated Lipocalin.

PubMed

Tanigasalam, Vasanthan; Bhat, Ballambattu Vishnu; Adhisivam, Bethou; Sridhar, Magadi Gopalakrishna; Harichandrakumar, Kottyen Thazath

2016-11-01

To evaluate the utility of urinary Neutrophil Gelatinase Associated Lipocalin (NGAL) as a biomarker for predicting Acute Kidney Injury (AKI) and its severity among neonates with perinatal asphyxia. This descriptive study included 120 term neonates with perinatal asphyxia. Renal parameters of neonates were monitored and AKI was ascertained as per Acute Kidney Injury Network criteria. Urinary NGAL was estimated and correlated with severity of AKI. Among the 120 neonates with perinatal asphyxia, 55(46 %) had AKI. The median urinary NGAL level was 165 ng/ml (88.8-245.8) in neonates with AKI compared to 58.97(42.8-74.7) in those without AKI. The median NGAL was 134.45(112.2-162.5), 301.2(255.5-361.2), 416.2(412.2-465.5) in AKI stages 1, 2 and 3 respectively. An NGAL cut off value of 86.82 ng/ml had 87 % sensitivity and 87.7 % specificity in predicting AKI. Urinary NGAL is a useful biomarker for predicting AKI and its severity among neonates with perinatal asphyxia.

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

PubMed

Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

Surrogate utility estimation by long-term partners and unfamiliar dyads.

PubMed

Tunney, Richard J; Ziegler, Fenja V

2015-01-01

To what extent are people able to make predictions about other people's preferences and values?We report two experiments that present a novel method assessing some of the basic processes in surrogate decision-making, namely surrogate-utility estimation. In each experiment participants formed dyads who were asked to assign utilities to health related items and commodity items, and to predict their partner's utility judgments for the same items. In experiment one we showed that older adults in long-term relationships were able to accurately predict their partner's wishes. In experiment two we showed that younger adults who were relatively unfamiliar with one another were also able to predict other people's wishes. Crucially we demonstrated that these judgments were accurate even after partialling out each participant's own preferences indicating that in order to make surrogate utility estimations people engage in perspective-taking rather than simple anchoring and adjustment, suggesting that utility estimation is not the cause of inaccuracy in surrogate decision-making. The data and implications are discussed with respect to theories of surrogate decision-making.

Theoretical Study of pKa Values for Trivalent Rare-Earth Metal Cations in Aqueous Solution.

PubMed

Yu, Donghai; Du, Ruobing; Xiao, Ji-Chang; Xu, Shengming; Rong, Chunying; Liu, Shubin

2018-01-18

Molecular acidity of trivalent rare-earth metal cations in aqueous solution is an important factor dedicated to the efficiency of their extraction and separation processes. In this work, the aqueous acidity of these metal ions has been quantitatively investigated using a few theoretical approaches. Our computational results expressed in terms of pK a values agree well with the tetrad effect of trivalent rare-earth ions extensively reported in the extraction and separation of these elements. Strong linear relationships have been observed between the acidity and quantum electronic descriptors such as the molecular electrostatic potential on the acidic nucleus and the sum of the valence natural atomic orbitals energies of the dissociating proton. Making use of the predicted pK a values, we have also predicted the major ionic forms of these species in the aqueous environment with different pH values, which can be employed to rationalize the behavior difference of different rare-earth metal cations during the extraction process. Our present results should provide needed insights not only for the qualitatively understanding about the extraction and separation between yttrium and lanthanide elements but also for the prediction of novel and more efficient rare-earth metal extractants in the future.

A Behavioral Economic Reward Index Predicts Drinking Resolutions: Moderation Re-visited and Compared with Other Outcomes

PubMed Central

Tucker, Jalie A.; Roth, David L.; Vignolo, Mary J.; Westfall, Andrew O.

2014-01-01

Data were pooled from three studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1-2 year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes compared to abstinence or relapse and to be predicted by more balanced pre-resolution monetary allocations between short- and longer-term objectives (i.e., drinking and saving for the future). Standardized odds ratios (OR) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this “Alcohol-Savings Discretionary Expenditure” index predicted higher rates of both abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p < .0001) compared to moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of pre-resolution spending patterns aids in predicting moderation. PMID:19309182

Choosing a model to predict hospital admission: an observational study of new variants of predictive models for case finding

PubMed Central

Billings, John; Georghiou, Theo; Blunt, Ian; Bardsley, Martin

2013-01-01

Objectives To test the performance of new variants of models to identify people at risk of an emergency hospital admission. We compared (1) the impact of using alternative data sources (hospital inpatient, A&E, outpatient and general practitioner (GP) electronic medical records) (2) the effects of local calibration on the performance of the models and (3) the choice of population denominators. Design Multivariate logistic regressions using person-level data adding each data set sequentially to test value of additional variables and denominators. Setting 5 Primary Care Trusts within England. Participants 1 836 099 people aged 18–95 registered with GPs on 31 July 2009. Main outcome measures Models to predict hospital admission and readmission were compared in terms of the positive predictive value and sensitivity for various risk strata and with the receiver operating curve C statistic. Results The addition of each data set showed moderate improvement in the number of patients identified with little or no loss of positive predictive value. However, even with inclusion of GP electronic medical record information, the algorithms identified only a small number of patients with no emergency hospital admissions in the previous 2 years. The model pooled across all sites performed almost as well as the models calibrated to local data from just one site. Using population denominators from GP registers led to better case finding. Conclusions These models provide a basis for wider application in the National Health Service. Each of the models examined produces reasonably robust performance and offers some predictive value. The addition of more complex data adds some value, but we were unable to conclude that pooled models performed less well than those in individual sites. Choices about model should be linked to the intervention design. Characteristics of patients identified by the algorithms provide useful information in the design/costing of intervention strategies to improve care coordination/outcomes for these patients. PMID:23980068

Alcohol Use among Recent Immigrant Latino/a Youth: Acculturation, Gender, and the Theory of Reasoned Action

PubMed Central

Lorenzo-Blanco, Elma I.; Schwartz, Seth J.; Unger, Jennifer B.; Zamboanga, Byron L.; Rosiers, Sabrina E. Des; Baezconde-Garbanati, Lourdes; Huang, Shi; Villamar, Juan A.; Soto, Daniel; Pattarroyo, Monica

2016-01-01

Objective Latino/a youth are at risk for alcohol use. This risk seems to rise with increasing U.S. cultural orientation and decreasing Latino cultural orientation, especially among girls. To ascertain how acculturation may influence Latino/a youth alcohol use, in this study we integrated an expanded multi-domain model of acculturation with the Theory of Reasoned Action. Design Participants were 302 recent Latino/a immigrant youth (141 girls, 160 boys; 152 from Miami, 150 from Los Angeles) who completed surveys at 4 time points. Youth completed measures of acculturation (measured in terms of Latino/a practices, Latino/a identity, collectivistic values; U.S. cultural practices, U.S. identity, and individualistic values), attitudes toward drinking, perceived subjective norms regarding alcohol use, intention to drink, and alcohol use. Results Structural equation modeling indicated that collectivistic values predicted more perceived disapproval of drinking, which negatively predicted intention to drink. Intention to drink predicted elevated alcohol use. Conclusion Although the association between collectivistic values and social disapproval of drinking was relatively small (β=.19, p < .05), findings suggest that collectivistic values may help protect Latino/a immigrant youth from alcohol use by influencing their perceived social disapproval of drinking, leading to lower intention to drink. Educational preventive interventions aimed at reducing or preventing alcohol use in recent Latino/a immigrant youth could promote collectivistic values and disseminate messages about the negative consequences of drinking. PMID:27220730

A Modified LS+AR Model to Improve the Accuracy of the Short-term Polar Motion Prediction

NASA Astrophysics Data System (ADS)

Wang, Z. W.; Wang, Q. X.; Ding, Y. Q.; Zhang, J. J.; Liu, S. S.

2017-03-01

There are two problems of the LS (Least Squares)+AR (AutoRegressive) model in polar motion forecast: the inner residual value of LS fitting is reasonable, but the residual value of LS extrapolation is poor; and the LS fitting residual sequence is non-linear. It is unsuitable to establish an AR model for the residual sequence to be forecasted, based on the residual sequence before forecast epoch. In this paper, we make solution to those two problems with two steps. First, restrictions are added to the two endpoints of LS fitting data to fix them on the LS fitting curve. Therefore, the fitting values next to the two endpoints are very close to the observation values. Secondly, we select the interpolation residual sequence of an inward LS fitting curve, which has a similar variation trend as the LS extrapolation residual sequence, as the modeling object of AR for the residual forecast. Calculation examples show that this solution can effectively improve the short-term polar motion prediction accuracy by the LS+AR model. In addition, the comparison results of the forecast models of RLS (Robustified Least Squares)+AR, RLS+ARIMA (AutoRegressive Integrated Moving Average), and LS+ANN (Artificial Neural Network) confirm the feasibility and effectiveness of the solution for the polar motion forecast. The results, especially for the polar motion forecast in the 1-10 days, show that the forecast accuracy of the proposed model can reach the world level.

Value of mechanical dyssynchrony as assessed by radionuclide ventriculography to predict the cardiac resynchronization therapy response.

PubMed

Tournoux, Francois; Chequer, Renata; Sroussi, Marjorie; Hyafil, Fabien; Algalarrondo, Vincent; Cohen-Solal, Alain; Bodson-Clermont, Paule; Le Guludec, Dominique; Rouzet, Francois

2016-11-01

To assess the value of mechanical dyssynchrony measured by equilibrium radionuclide angiography (ERNA) in predicting long-term outcome in cardiac resynchronization therapy (CRT) patients. We reviewed 146 ERNA studies performed in heart failure patients between 2001 and 2011 at our institution. Long-term follow-up focused on death from any cause or heart transplantation. Phase images were computed using the first harmonic Fourier transform. Intra-ventricular dyssynchrony was calculated as the delay between the earliest and most delayed 20% of the left ventricular (LV) (IntraV-20/80) and inter-ventricular dyssynchrony as the difference between LV- and right ventricular (RV)-mode phase angles (InterV). Eighty-three patients (57%) were implanted with a CRT device after ERNA. Median follow-up was 35 [21-50] months. Twenty-four events were observed during the first 41 months. Median baseline ERNA dyssynchrony values were 28 [3 to 46] degrees for intraV-20/80 and 9 [-6 to 24] degrees for interV. Comparing survival between CRT and non-CRT patients according to dyssynchrony status, log-rank tests showed no difference in survival in patients with no ERNA dyssynchrony (P = 0.34) while a significant difference was observed in ERNA patients with high level of mechanical dyssynchrony (P = 0.004). ERNA mechanical dyssynchrony could be of value in CRT patient selection. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Measuring self-esteem in context: the importance of stability of self-esteem in psychological functioning.

PubMed

Kernis, Michael H

2005-12-01

In this article, I report on a research program that has focused on the joint roles of stability and level of self-esteem in various aspects of psychological functioning. Stability of self-esteem refers to the magnitude of short-term fluctuations that people experience in their current, contextually based feelings of self-worth. In contrast, level of self-esteem refers to representations of people's general, or typical, feelings of self-worth. A considerable amount of research reveals that self-esteem stability has predictive value beyond the predictive value of self-esteem level. Moreover, considering self-esteem stability provides one way to distinguish fragile from secure forms of high self-esteem. Results from a number of studies are presented and theoretical implications are discussed.

Study on creep of fiber reinforced ultra-high strength concrete based on strength

NASA Astrophysics Data System (ADS)

Peng, Wenjun; Wang, Tao

2018-04-01

To complement the creep performance of ultra-high strength concrete, the long creep process of fiber reinforced concrete was studied in this paper. The long-term creep process and regularity of ultra-high strength concrete with 0.5% PVA fiber under the same axial compression were analyzed by using concrete strength (C80/C100/C120) as a variable. The results show that the creep coefficient of ultra-high strength concrete decreases with the increase of concrete strength. Compared with ACI209R (92), GL2000 models, it is found that the predicted value of ACI209R (92) are close to the experimental value, and the creep prediction model suitable for this experiment is proposed based on ACI209R (92).

Numerical and Experimental Validation of a New Damage Initiation Criterion

NASA Astrophysics Data System (ADS)

Sadhinoch, M.; Atzema, E. H.; Perdahcioglu, E. S.; van den Boogaard, A. H.

2017-09-01

Most commercial finite element software packages, like Abaqus, have a built-in coupled damage model where a damage evolution needs to be defined in terms of a single fracture energy value for all stress states. The Johnson-Cook criterion has been modified to be Lode parameter dependent and this Modified Johnson-Cook (MJC) criterion is used as a Damage Initiation Surface (DIS) in combination with the built-in Abaqus ductile damage model. An exponential damage evolution law has been used with a single fracture energy value. Ultimately, the simulated force-displacement curves are compared with experiments to validate the MJC criterion. 7 out of 9 fracture experiments were predicted accurately. The limitations and accuracy of the failure predictions of the newly developed damage initiation criterion will be discussed shortly.

Fuzzy time series forecasting model with natural partitioning length approach for predicting the unemployment rate under different degree of confidence

NASA Astrophysics Data System (ADS)

Ramli, Nazirah; Mutalib, Siti Musleha Ab; Mohamad, Daud

2017-08-01

Fuzzy time series forecasting model has been proposed since 1993 to cater for data in linguistic values. Many improvement and modification have been made to the model such as enhancement on the length of interval and types of fuzzy logical relation. However, most of the improvement models represent the linguistic term in the form of discrete fuzzy sets. In this paper, fuzzy time series model with data in the form of trapezoidal fuzzy numbers and natural partitioning length approach is introduced for predicting the unemployment rate. Two types of fuzzy relations are used in this study which are first order and second order fuzzy relation. This proposed model can produce the forecasted values under different degree of confidence.

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

PubMed

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

2017-09-01

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

Early prediction of blonanserin response in Japanese patients with schizophrenia.

PubMed

Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

2014-01-01

Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Our results suggest that the blonanserin response at week 4 could predict the later response at week 8.

Early prediction of blonanserin response in Japanese patients with schizophrenia

PubMed Central

Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

2014-01-01

Background Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. Methods An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Results Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Conclusion Our results suggest that the blonanserin response at week 4 could predict the later response at week 8. PMID:25285009

Developing hybrid approaches to predict pKa values of ionizable groups

PubMed Central

Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

2011-01-01

Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

Predictive validity of the Braden Scale, Norton Scale, and Waterlow Scale in the Czech Republic.

PubMed

Šateková, Lenka; Žiaková, Katarína; Zeleníková, Renáta

2017-02-01

The aim of this study was to determine the predictive validity of the Braden, Norton, and Waterlow scales in 2 long-term care departments in the Czech Republic. Assessing the risk for developing pressure ulcers is the first step in their prevention. At present, many scales are used in clinical practice, but most of them have not been properly validated yet (for example, the Modified Norton Scale in the Czech Republic). In the Czech Republic, only the Braden Scale has been validated so far. This is a prospective comparative instrument testing study. A random sample of 123 patients was recruited. The predictive validity of the pressure ulcer risk assessment scales was evaluated based on sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve. The data were collected from April to August 2014. In the present study, the best predictive validity values were observed for the Norton Scale, followed by the Braden Scale and the Waterlow Scale, in that order. We recommended that the above 3 pressure ulcer risk assessment scales continue to be evaluated in the Czech clinical setting. © 2016 John Wiley & Sons Australia, Ltd.

Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

PubMed Central

2014-01-01

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

Long-term survival with modern therapeutic agents against metastatic melanoma-vemurafenib and ipilimumab in a daily life setting.

PubMed

Lang, B M; Peveling-Oberhag, A; Faidt, D; Hötker, A M; Weyer-Elberich, V; Grabbe, S; Loquai, C

2018-01-31

Despite new therapeutic options, metastatic melanoma remains to be one of the most fatal tumors. With the development of BRAF inhibitors and immune checkpoint inhibitors, overall survival could be prolonged significantly for the first time. Clinical studies implied that even long-term survival is possible with both types of drugs, but predictive markers are so far missing. In this study, we analyzed survival data from patients that received the first-in-class substances vemurafenib and ipilimumab, respectively, during the time period from registration of the drugs until availability of combination treatments. We aimed to evaluate the possibility of long-term survival in a daily life setting and to characterize patients that benefit from these drugs in order to gain insight into predictive attributes. Eighty patients were evaluated who were treated with either vemurafenib (n = 40) or ipilimumab (n = 40), and overall survival was analyzed. Subgroup analysis was performed for patients who were still alive 24 months after induction of therapy (long-term survival). Median overall survival (OS) was 8.0 months for patients treated with vemurafenib and 10.0 months for patients treated with ipilimumab (log-rank P value = 0.689). Long-term survival was achieved in 32.5% of patients (42.3% vemurafenib, 57.7% ipilimumab). Negative predictors of long-term survival in the vemurafenib group were brain and liver metastases, as well as elevated LDH, S100ß and liver enzymes. For ipilimumab, an increase in lymphocytes and eosinophils during course of treatment correlated with long-term survival. Our real-life experience shows that long-term survival is possible with using both therapeutic agents, vemurafenib and ipilimumab. Pattern of metastases and laboratory values might be of interest in decision making for a specific therapeutic approach. Combination of drugs and observational studies in larger patient cohorts are necessary to further validate our findings.

Evidence for the speed-value trade-off: human and monkey decision making is magnitude sensitive.

PubMed

Pirrone, Angelo; Azab, Habiba; Hayden, Benjamin Y; Stafford, Tom; Marshall, James A R

2018-04-01

Complex natural systems from brains to bee swarms have evolved to make adaptive multifactorial decisions. Recent theoretical and empirical work suggests that many evolved systems may take advantage of common motifs across multiple domains. We are particularly interested in value sensitivity (i.e., sensitivity to the magnitude or intensity of the stimuli or reward under consideration) as a mechanism to resolve deadlocks adaptively. This mechanism favours long-term reward maximization over accuracy in a simple manner, because it avoids costly delays associated with ambivalence between similar options; speed-value trade-offs have been proposed to be evolutionarily advantageous for many kinds of decision. A key prediction of the value-sensitivity hypothesis is that choices between equally-valued options will proceed faster when the options have a high value than when they have a low value. However, value-sensitivity is not part of idealised choice models such as diffusion to bound. Here we examine two different choice behaviours in two different species, perceptual decisions in humans and economic choices in rhesus monkeys, to test this hypothesis. We observe the same value sensitivity in both human perceptual decisions and monkey value-based decisions. These results endorse the idea that neural decision systems make use of the same basic principle of value-sensitivity in order to resolve costly deadlocks and thus improve long-term reward intake.

Evidence for the speed-value trade-off: human and monkey decision making is magnitude sensitive

PubMed Central

Pirrone, Angelo; Azab, Habiba; Hayden, Benjamin Y.; Stafford, Tom; Marshall, James A. R.

2017-01-01

Complex natural systems from brains to bee swarms have evolved to make adaptive multifactorial decisions. Recent theoretical and empirical work suggests that many evolved systems may take advantage of common motifs across multiple domains. We are particularly interested in value sensitivity (i.e., sensitivity to the magnitude or intensity of the stimuli or reward under consideration) as a mechanism to resolve deadlocks adaptively. This mechanism favours long-term reward maximization over accuracy in a simple manner, because it avoids costly delays associated with ambivalence between similar options; speed-value trade-offs have been proposed to be evolutionarily advantageous for many kinds of decision. A key prediction of the value-sensitivity hypothesis is that choices between equally-valued options will proceed faster when the options have a high value than when they have a low value. However, value-sensitivity is not part of idealised choice models such as diffusion to bound. Here we examine two different choice behaviours in two different species, perceptual decisions in humans and economic choices in rhesus monkeys, to test this hypothesis. We observe the same value sensitivity in both human perceptual decisions and monkey value-based decisions. These results endorse the idea that neural decision systems make use of the same basic principle of value-sensitivity in order to resolve costly deadlocks and thus improve long-term reward intake. PMID:29682592

In patients with minimally symptomatic OSA can baseline characteristics and early patterns of CPAP usage predict those who are likely to be longer-term users of CPAP.

PubMed

Turnbull, Christopher D; Bratton, Daniel J; Craig, Sonya E; Kohler, Malcolm; Stradling, John R

2016-02-01

Long-term continuous positive airway pressure (CPAP) usage varies between individuals. It would be of value to be able to identify those who are likely to benefit from CPAP (and use it long term), versus those who would not, and might therefore benefit from additional help early on. First, we explored whether baseline characteristics predicted CPAP usage in minimally symptomatic obstructive sleep apnoea (OSA) patients, a group who would be expected to have low usage. Second, we explored if early CPAP usage was predictive of longer-term usage, as has been shown in more symptomatic OSA patients. The MOSAIC trial was a multi-centre randomised controlled trial where minimally symptomatic OSA patients were randomised to CPAP, or standard care, for 6 months. Here we have studied only those patients randomised to CPAP treatment. Baseline characteristics including symptoms, questionnaires [including the Epworth sleepiness score (ESS)] and sleep study parameters were recorded. CPAP usage was recorded at 2-4 weeks after initiation and after 6 months. The correlation and association between baseline characteristics and 6 months CPAP usage was assessed, as was the correlation between 2 and 4 weeks CPAP usage and 6 months CPAP usage. One hundred and ninety-five patients randomised to CPAP therapy had median [interquartile range (IQR)] CPAP usage of 2:49 (0:44, 5:13) h:min/night (h/n) at the 2-4 weeks visit, and 2:17 (0:08, 4:54) h/n at the 6 months follow-up visit. Only male gender was associated with increased long-term CPAP use (male usage 2:56 h/n, female 1:57 h/n; P=0.02). There was a moderate correlation between the usage of CPAP at 2-4 weeks and 6 months, with about 50% of the variability in long-term use being predicted by the short-term use. In patients with minimally symptomatic OSA, our study has shown that male gender (and not OSA severity or symptom burden) is associated with increased long-term use of CPAP at 6 months. Although, in general, early patterns of CPAP usage predicted longer term use, there are patients in whom this is not the case, and patients with low initial usage may need to extend their CPAP trial before a decision about longer-term use is made.

Predictive value of lidocaine for treatment success of oxcarbazepine in patients with neuropathic pain syndrome.

PubMed

Schipper, Sivan; Gantenbein, Andreas R; Maurer, Konrad; Alon, Eli; Sándor, Peter S

2013-06-01

Pharmacotherapy in patients with neuropathic pain syndromes (NPS) can be associated with long periods of trial and error before reaching satisfactory analgesia. The aim of this study was to investigate whether a short intravenous (i.v.) infusion of lidocaine may have a predictive value for the efficacy of oxcarbazepine. In total, 16 consecutive patients with NPS were studied in a prospective, uncontrolled, open-label study design. Each patient received i.v. lidocaine (5 mg/kg) within 30 min followed by a long-term oral oxcarbazepine treatment (900-1,500 mg/day). During an observation period of 28 days, treatment response was documented by a questionnaire including the average daily pain score documented on a numeric rating scale (NRS). A total of 6 out of 16 patients (38%) were lidocaine responders (defined as pain reduction >50% during the infusion), and 4 of 16 (25%) were oxcarbazepine responders. In total, 6 out of 16 participants (38%) discontinued oxcarbazepine treatment due to side effects. In an interim analysis predictive value of the lidocaine infusion was low with a Kendall's tau correlation coefficient of 0.29 and coefficient of determination R(2) of 0.119 (95% confidence interval -0.29 to 0.72). As a consequence of this low correlation, the study was discontinued for ethical reasons. In conclusion, lidocaine infusion has a low predictive value for effectiveness of oxcarbazepine-if at all.

Diagnostic accuracy of patch test in children with food allergy.

PubMed

Caglayan Sozmen, Sule; Povesi Dascola, Carlotta; Gioia, Edoardo; Mastrorilli, Carla; Rizzuti, Laura; Caffarelli, Carlo

2015-08-01

The gold standard test for confirming whether a child has clinical hypersensitivity reactions to foods is the oral food challenge. Therefore, there is increasing interest in simpler diagnostic markers of food allergy, especially in children, to avoid oral food challenge. The goal of this study was to assess the diagnostic accuracy of atopy patch test in comparison with oral food challenge. We investigated 243 children (mean age, 51 months) referred for evaluation of suspected egg or cow's milk allergy. Skin prick test and atopy patch test were carried out, and after a 2 weeks elimination diet, oral food challenge was performed. Two hundred and forty-three children underwent OFC to the suspected food. We found clinically relevant food allergies in 40 (65%) children to egg and in 22 (35%) to cow's milk. The sensitivity of skin prick test for both milk and egg was 92%, specificity 91%, positive predictive value 35%, and negative predictive value of 93%. Sensitivity, specificity, positive predictive value, and negative predictive value of atopy patch test for both milk and egg were 21%, 73%, 20%, and 74%, respectively. Our study suggests that there is insufficient evidence for the routine use of atopy patch test for the evaluation of egg and cow's milk allergy. OFC remains gold standard for the diagnosis of egg and milk allergy even in the presence of high costs in terms of both time and risks during application. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Risk and Protective Factors Influencing Life Skills among Youths in Long-Term Foster Care.

ERIC Educational Resources Information Center

Nollan, K. A.; Pecora, P. J.; Nurius, P. N.; Whittaker, J. K.

2002-01-01

Examined through mail surveys of youth, parents, and social workers the predictive value of selected risk and protective factors in explaining self-sufficiency skills of 219 ethnically diverse 12- to 15-year-olds in foster care. Found that protective factors related to greater self-sufficiency skills, and risk factors were negatively associated.…

More than Content: The Persistent Cross-Subject Effects of English Language Arts Teachers' Instruction

ERIC Educational Resources Information Center

Master, Benjamin; Loeb, Susanna; Wyckoff, James

2017-01-01

Evidence that teachers' short-term instructional effects persist over time and predict substantial long-run impacts on students' lives provides much of the impetus for a wide range of educational reforms focused on identifying and responding to differences in teachers' value-added to student learning. However, relatively little research has…

Failing to Succeed the First School: Exploring Phonological Factors and Letter Reading Ability in Grade 1

ERIC Educational Resources Information Center

Gafoor, Kunnathodi Abdul; Remia, K. R.

2013-01-01

The context of this paper is studies worldwide on influence of phonological factors in language development of children. Such studies reveal the significance of Phonological Awareness in development language skills: including, predictive value of phonological short-term memory for reading skills in Grade 1. This paper throws light on factors in…

Estimation of the base temperature and growth phase duration in terms of thermal time for four grapevine cultivars

NASA Astrophysics Data System (ADS)

Zapata, D.; Salazar, M.; Chaves, B.; Keller, M.; Hoogenboom, G.

2015-12-01

Thermal time models have been used to predict the development of many different species, including grapevine ( Vitis vinifera L.). These models normally assume that there is a linear relationship between temperature and plant development. The goal of this study was to estimate the base temperature and duration in terms of thermal time for predicting veraison for four grapevine cultivars. Historical phenological data for four cultivars that were collected in the Pacific Northwest were used to develop the thermal time model. Base temperatures ( T b) of 0 and 10 °C and the best estimated T b using three different methods were evaluated for predicting veraison in grapevine. Thermal time requirements for each individual cultivar were evaluated through analysis of variance, and means were compared using the Fisher's test. The methods that were applied to estimate T b for the development of wine grapes included the least standard deviation in heat units, the regression coefficient, and the development rate method. The estimated T b varied among methods and cultivars. The development rate method provided the lowest T b values for all cultivars. For the three methods, Chardonnay had the lowest T b ranging from 8.7 to 10.7 °C, while the highest T b values were obtained for Riesling and Cabernet Sauvignon with 11.8 and 12.8 °C, respectively. Thermal time also differed among cultivars, when either the fixed or estimated T b was used. Predictions of the beginning of ripening with the estimated temperature resulted in the lowest variation in real days when compared with predictions using T b = 0 or 10 °C, regardless of the method that was used to estimate the T b.

[Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].

PubMed

Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João

2016-11-01

Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional prognosis after ischemic stroke.

Correlation of Noncancer Benchmark Doses in Short- and Long-Term Rodent Bioassays.

PubMed

Kratchman, Jessica; Wang, Bing; Fox, John; Gray, George

2018-05-01

This study investigated whether, in the absence of chronic noncancer toxicity data, short-term noncancer toxicity data can be used to predict chronic toxicity effect levels by focusing on the dose-response relationship instead of a critical effect. Data from National Toxicology Program (NTP) technical reports have been extracted and modeled using the Environmental Protection Agency's Benchmark Dose Software. Best-fit, minimum benchmark dose (BMD), and benchmark dose lower limits (BMDLs) have been modeled for all NTP pathologist identified significant nonneoplastic lesions, final mean body weight, and mean organ weight of 41 chemicals tested by NTP between 2000 and 2012. Models were then developed at the chemical level using orthogonal regression techniques to predict chronic (two years) noncancer health effect levels using the results of the short-term (three months) toxicity data. The findings indicate that short-term animal studies may reasonably provide a quantitative estimate of a chronic BMD or BMDL. This can allow for faster development of human health toxicity values for risk assessment for chemicals that lack chronic toxicity data. © 2017 Society for Risk Analysis.

Using Dynamic Risk and Protective Factors to Predict Inpatient Aggression: Reliability and Validity of START Assessments

PubMed Central

Desmarais, Sarah L.; Nicholls, Tonia L.; Wilson, Catherine M.; Brink, Johann

2012-01-01

The Short-Term Assessment of Risk and Treatability (START) is a relatively new structured professional judgment guide for the assessment and management of short-term risks associated with mental, substance use, and personality disorders. The scheme may be distinguished from other violence risk instruments because of its inclusion of 20 dynamic factors that are rated in terms of both vulnerability and strength. This study examined the reliability and validity of START assessments in predicting inpatient aggression. Research assistants completed START assessments for 120 male forensic psychiatric patients through review of hospital files. They additionally completed Historical-Clinical-Risk Management – 20 (HCR-20) and the Hare Psychopathy Checklist: Screening Version (PCL:SV) assessments. Outcome data was coded from hospital files for a 12-month follow-up period using the Overt Aggression Scale (OAS). START assessments evidenced excellent interrater reliability and demonstrated both predictive and incremental validity over the HCR-20 Historical subscale scores and PCL:SV total scores. Overall, results support the reliability and validity of START assessments, and use of the structured professional judgment approach more broadly, as well as the value of using dynamic risk and protective factors to assess violence risk. PMID:22250595

Dilatation-dissipation corrections for advanced turbulence models

NASA Technical Reports Server (NTRS)

Wilcox, David C.

1992-01-01

This paper analyzes dilatation-dissipation based compressibility corrections for advanced turbulence models. Numerical computations verify that the dilatation-dissipation corrections devised by Sarkar and Zeman greatly improve both the k-omega and k-epsilon model predicted effect of Mach number on spreading rate. However, computations with the k-gamma model also show that the Sarkar/Zeman terms cause an undesired reduction in skin friction for the compressible flat-plate boundary layer. A perturbation solution for the compressible wall layer shows that the Sarkar and Zeman terms reduce the effective von Karman constant in the law of the wall. This is the source of the inaccurate k-gamma model skin-friction predictions for the flat-plate boundary layer. The perturbation solution also shows that the k-epsilon model has an inherent flaw for compressible boundary layers that is not compensated for by the dilatation-dissipation corrections. A compressibility modification for k-gamma and k-epsilon models is proposed that is similar to those of Sarkar and Zeman. The new compressibility term permits accurate predictions for the compressible mixing layer, flat-plate boundary layer, and a shock separated flow with the same values for all closure coefficients.

Valuing hydrological forecasts for a pumped storage assisted hydro facility

NASA Astrophysics Data System (ADS)

Zhao, Guangzhi; Davison, Matt

2009-07-01

SummaryThis paper estimates the value of a perfectly accurate short-term hydrological forecast to the operator of a hydro electricity generating facility which can sell its power at time varying but predictable prices. The expected value of a less accurate forecast will be smaller. We assume a simple random model for water inflows and that the costs of operating the facility, including water charges, will be the same whether or not its operator has inflow forecasts. Thus, the improvement in value from better hydrological prediction results from the increased ability of the forecast using facility to sell its power at high prices. The value of the forecast is therefore the difference between the sales of a facility operated over some time horizon with a perfect forecast, and the sales of a similar facility operated over the same time horizon with similar water inflows which, though governed by the same random model, cannot be forecast. This paper shows that the value of the forecast is an increasing function of the inflow process variance and quantifies how much the value of this perfect forecast increases with the variance of the water inflow process. Because the lifetime of hydroelectric facilities is long, the small increase observed here can lead to an increase in the profitability of hydropower investments.

Multiplier method may be unreliable to predict the timing of temporary hemiepiphysiodesis for coronal angular deformity.

PubMed

Wu, Zhenkai; Ding, Jing; Zhao, Dahang; Zhao, Li; Li, Hai; Liu, Jianlin

2017-07-10

The multiplier method was introduced by Paley to calculate the timing for temporary hemiepiphysiodesis. However, this method has not been verified in terms of clinical outcome measure. We aimed to (1) predict the rate of angular correction per year (ACPY) at the various corresponding ages by means of multiplier method and verify the reliability based on the data from the published studies and (2) screen out risk factors for deviation of prediction. A comprehensive search was performed in the following electronic databases: Cochrane, PubMed, and EMBASE™. A total of 22 studies met the inclusion criteria. If the actual value of ACPY from the collected date was located out of the range of the predicted value based on the multiplier method, it was considered as the deviation of prediction (DOP). The associations of patient characteristics with DOP were assessed with the use of univariate logistic regression. Only one article was evaluated as moderate evidence; the remaining articles were evaluated as poor quality. The rate of DOP was 31.82%. In the detailed individual data of included studies, the rate of DOP was 55.44%. The multiplier method is not reliable in predicting the timing for temporary hemiepiphysiodesis, even though it is prone to be more reliable for the younger patients with idiopathic genu coronal deformity.

Assessing the value of post-processed state-of-the-art long-term weather forecast ensembles for agricultural water management mediated by farmers' behaviours

NASA Astrophysics Data System (ADS)

Li, Yu; Giuliani, Matteo; Castelletti, Andrea

2016-04-01

Recent advances in modelling of coupled ocean-atmosphere dynamics significantly improved skills of long-term climate forecast from global circulation models (GCMs). These more accurate weather predictions are supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping and watering time) and for more effectively coping with the adverse impacts of climate variability. Yet, assessing how actually valuable this information can be to a farmer is not straightforward and farmers' response must be taken into consideration. Indeed, in the context of agricultural systems potentially useful forecast information should alter stakeholders' expectation, modify their decisions, and ultimately produce an impact on their performance. Nevertheless, long-term forecast are mostly evaluated in terms of accuracy (i.e., forecast quality) by comparing hindcast and observed values and only few studies investigated the operational value of forecast looking at the gain of utility within the decision-making context, e.g. by considering the derivative of forecast information, such as simulated crop yields or simulated soil moisture, which are essential to farmers' decision-making process. In this study, we contribute a step further in the assessment of the operational value of long-term weather forecasts products by embedding these latter into farmers' behavioral models. This allows a more critical assessment of the forecast value mediated by the end-users' perspective, including farmers' risk attitudes and behavioral patterns. Specifically, we evaluate the operational value of thirteen state-of-the-art long-range forecast products against climatology forecast and empirical prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of the farmers' decision-making process. Raw ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and our model. For each product, the experiment is composed by two cascade simulations: 1) an ex-ante simulation using forecast data, and 2) an ex-post simulation with observations. Multi-year simulations are performed to account for climate variability, and the operational value of the different forecast products is evaluated against the perfect foresight on the basis of expected crop productivity as well as the final decisions under different decision-making criterions. Our results show that not all products generate beneficial effects to farmers' performance, and the forecast errors might be amplified due to farmers' decision-making process and risk attitudes, yielding little or even worse performance compared with the empirical approaches.

Pregnant human peripheral leukocyte migration during several late pregnancy clinical conditions: a cross-sectional observational study.

PubMed

Takeda, Jun; Fang, Xin; Olson, David M

2017-01-10

Parturition at term and preterm is characterized by sterile inflammatory processes occurring in the absence of infection whereby peripheral leukocytes infiltrate gestational tissues in response to chemotactic signals. In response to a homing signal, recruited leukocytes undergo diapedesis and extravasate through capillaries, migrating into stromal tissue. There they interact with resident immune and stromal cells to produce a mixture of matrix metalloproteinases, prostaglandins and cytokines including interleukin-1β (IL-1β) and IL-6 that in turn transform the uterus from pregnancy to parturition. Since migration is an early parturitional event our purpose was to study the migration of maternal peripheral blood leukocytes in response to a standard chemotactic signal during several different conditions of late pregnancy. We used a cross-sectional observational study design. Subjects were (sTL) spontaneous normal labour delivered vaginally at term, (TNL) elective caesarean section at term without labour, (PTL) preterm in labour, (PTNL) preterm not in labour, (TPTL) threatened preterm labour, and (pPROM) preterm with premature rupture of membranes. Leukocytes (100,000) obtained by venipuncture and chemotactic factor isolated from term labour fetal membranes were placed in the upper and lower halves, respectively, of a Boyden chamber separated by a filter with 3μm pores. Migrated leukocytes were assessed by flow cytometry. The number of leukocytes that migrated in 90 min was the primary outcome measure. Increased numbers of leukocytes from peripheral blood of women in labour (TL or PTL) or soon to go into labour (PPROM) migrated towards a chemotactic signal than did leukocytes from women not in labour (TNL, PTNL, or TPTL) (p < 0.0001). All pPROM delivered within 7d; TPTL delivered >30d. Receiver operating characteristic curve parameters indicated the cut-off point for delivery within 7d to be 37,082 leukocytes with sensitivity 78.1%, specificity 88.9%, positive predictive value 91.4%, negative predictive value 72.7%, and area under the curve 0.83. Leukocyte migration to a fetal membrane signal varies in a predictable fashion during various clinical situations of late gestation. This principle has the potential to be improved to become a clinical test to predict delivery.

Can we "predict" long-term outcome for ambulatory transcutaneous electrical nerve stimulation in patients with chronic pain?

PubMed

Köke, Albère J; Smeets, Rob J E M; Perez, Roberto S; Kessels, Alphons; Winkens, Bjorn; van Kleef, Maarten; Patijn, Jacob

2015-03-01

Evidence for effectiveness of transcutaneous electrical nerve stimulation (TENS) is still inconclusive. As heterogeneity of chronic pain patients might be an important factor for this lack of efficacy, identifying factors for a successful long-term outcome is of great importance. A prospective study was performed to identify variables with potential predictive value for 2 outcome measures on long term (6 months); (1) continuation of TENS, and (2) a minimally clinical important pain reduction of ≥ 33%. At baseline, a set of risk factors including pain-related variables, psychological factors, and disability was measured. In a multiple logistic regression analysis, higher patient's expectations, neuropathic pain, no severe pain (< 80 mm visual analogue scale [VAS]) were independently related to long-term continuation of TENS. For the outcome "minimally clinical important pain reduction," the multiple logistic regression analysis indicated that no multisited pain (> 2 pain locations) and intermittent pain were positively and independently associated with a minimally clinical important pain reduction of ≥ 33%. The results showed that factors associated with a successful outcome in the long term are dependent on definition of successful outcome. © 2014 World Institute of Pain.

Scale-relativity and quantization of exoplanet orbital semi-major axes

NASA Astrophysics Data System (ADS)

Nottale, L.; Schumacher, G.; Lefèvre, E. T.

2000-09-01

In a recent study (Nottale \\cite{xtrasol}), it was found that the distribution of the semi-major axes of the firstly discovered exoplanets was clustered around quantized values according to the law a/GM=(n/w02, in the same manner and in terms of the same constant w0=144 km/s as in our own inner Solar System. The ratio alpha g=w0/c actually stands out as a gravitational coupling constant. The number of exoplanets has now increased fivefold since this first study, including a full system of three planets around Ups And. In the present paper, we apply the same analysis to the new exoplanets and we find that their distribution agrees with this structuration law in a statistically significant way (probability ~ 10-4). Such a n2 law is predicted by the scale-relativity approach to planetary system formation, in which the evolution of planetesimals is described in terms of a generalized Schrödinger equation. In particular, one was able to predict from this model (Nottale \\cite{liwos}) the occurrence of preferential distances of planets at ~ 0.043 AU/Msun and ~ 0.17 AU/Msun from their parent stars. The observational data supports this theoretical prediction, since the semimajor axes of ~ 50% of the presently known exoplanets cluster around these values (51 Peg-type planets).

The chaotic regime of D-term inflation

NASA Astrophysics Data System (ADS)

Buchmüller, W.; Domcke, V.; Schmitz, K.

2014-11-01

We consider D-term inflation for small couplings of the inflaton to matter fields. Standard hybrid inflation then ends at a critical value of the inflaton field that exceeds the Planck mass. During the subsequent waterfall transition the inflaton continues its slow-roll motion, whereas the waterfall field rapidly grows by quantum fluctuations. Beyond the decoherence time, the waterfall field becomes classical and approaches a time-dependent minimum, which is determined by the value of the inflaton field and the self-interaction of the waterfall field. During the final stage of inflation, the effective inflaton potential is essentially quadratic, which leads to the standard predictions of chaotic inflation. The model illustrates how the decay of a false vacuum of GUT-scale energy density can end in a period of `chaotic inflation'.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring

PubMed Central

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D.; Larson, Timothy V.; Keller, Joshua P.; Kaufman, Joel D.

2016-01-01

Introduction: Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. Objectives: We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. Methods: We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children’s Health Study (CHS), and the Inhalable Particulate Network (IPN). Results: In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84–0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00–0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Conclusions: Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38–46; http://dx.doi.org/10.1289/EHP131 PMID:27340825

A Bayesian predictive two-stage design for phase II clinical trials.

PubMed

Sambucini, Valeria

2008-04-15

In this paper, we propose a Bayesian two-stage design for phase II clinical trials, which represents a predictive version of the single threshold design (STD) recently introduced by Tan and Machin. The STD two-stage sample sizes are determined specifying a minimum threshold for the posterior probability that the true response rate exceeds a pre-specified target value and assuming that the observed response rate is slightly higher than the target. Unlike the STD, we do not refer to a fixed experimental outcome, but take into account the uncertainty about future data. In both stages, the design aims to control the probability of getting a large posterior probability that the true response rate exceeds the target value. Such a probability is expressed in terms of prior predictive distributions of the data. The performance of the design is based on the distinction between analysis and design priors, recently introduced in the literature. The properties of the method are studied when all the design parameters vary.

The changing psychology of culture from 1800 through 2000.

PubMed

Greenfield, Patricia M

2013-09-01

The Google Books Ngram Viewer allows researchers to quantify culture across centuries by searching millions of books. This tool was used to test theory-based predictions about implications of an urbanizing population for the psychology of culture. Adaptation to rural environments prioritizes social obligation and duty, giving to other people, social belonging, religion in everyday life, authority relations, and physical activity. Adaptation to urban environments requires more individualistic and materialistic values; such adaptation prioritizes choice, personal possessions, and child-centered socialization in order to foster the development of psychological mindedness and the unique self. The Google Ngram Viewer generated relative frequencies of words indexing these values from the years 1800 to 2000 in American English books. As urban populations increased and rural populations declined, word frequencies moved in the predicted directions. Books published in the United Kingdom replicated this pattern. The analysis established long-term relationships between ecological change and cultural change, as predicted by the theory of social change and human development (Greenfield, 2009).

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

Radiative PQ breaking and the Higgs boson mass

NASA Astrophysics Data System (ADS)

D'Eramo, Francesco; Hall, Lawrence J.; Pappadopulo, Duccio

2015-06-01

The small and negative value of the Standard Model Higgs quartic coupling at high scales can be understood in terms of anthropic selection on a landscape where large and negative values are favored: most universes have a very short-lived electroweak vacuum and typical observers are in universes close to the corresponding metastability boundary. We provide a simple example of such a landscape with a Peccei-Quinn symmetry breaking scale generated through dimensional transmutation and supersymmetry softly broken at an intermediate scale. Large and negative contributions to the Higgs quartic are typically generated on integrating out the saxion field. Cancellations among these contributions are forced by the anthropic requirement of a sufficiently long-lived electroweak vacuum, determining the multiverse distribution for the Higgs quartic in a similar way to that of the cosmological constant. This leads to a statistical prediction of the Higgs boson mass that, for a wide range of parameters, yields the observed value within the 1σ statistical uncertainty of ˜ 5 GeV originating from the multiverse distribution. The strong CP problem is solved and single-component axion dark matter is predicted, with an abundance that can be understood from environmental selection. A more general setting for the Higgs mass prediction is discussed.

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data

PubMed Central

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Abstract Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density (d), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction. PMID:29707064

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data.

PubMed

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density ( d ), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction.

Lepton universality violation and right-handed currents in b → cτν

NASA Astrophysics Data System (ADS)

He, Xiao-Gang; Valencia, German

2018-04-01

We consider the recent LHCb result for Bc → J / ψτν in conjunction with the existing anomalies in R (D) and R (D⋆) within the framework of a right-handed current with enhanced couplings to the third generation. The model predicts a linear relation between the observables and their SM values in terms of two combinations of parameters. The strong constraints from b → sγ on W -W‧ mixing effectively remove one of the combinations of parameters resulting in an approximate proportionality between all three observables and their SM values. To accommodate the current averages for R (D) and R (D⋆), the W‧ mass should be near 1 TeV, and possibly accessible to direct searches at the LHC. In this scenario we find that R (J / ψ) is enhanced by about 20% with respect to its SM value and about 1.5σ below the central value of the LHCb measurement. The predicted dΓ / dq2 distribution for B → D (D⋆) τν is in agreement with the measurement and the model satisfies the constraint from the Bc lifetime.

Earthquake recurrence models fail when earthquakes fail to reset the stress field

USGS Publications Warehouse

Tormann, Thessa; Wiemer, Stefan; Hardebeck, Jeanne L.

2012-01-01

Parkfield's regularly occurring M6 mainshocks, about every 25 years, have over two decades stoked seismologists' hopes to successfully predict an earthquake of significant size. However, with the longest known inter-event time of 38 years, the latest M6 in the series (28 Sep 2004) did not conform to any of the applied forecast models, questioning once more the predictability of earthquakes in general. Our study investigates the spatial pattern of b-values along the Parkfield segment through the seismic cycle and documents a stably stressed structure. The forecasted rate of M6 earthquakes based on Parkfield's microseismicity b-values corresponds well to observed rates. We interpret the observed b-value stability in terms of the evolution of the stress field in that area: the M6 Parkfield earthquakes do not fully unload the stress on the fault, explaining why time recurrent models fail. We present the 1989 M6.9 Loma Prieta earthquake as counter example, which did release a significant portion of the stress along its fault segment and yields a substantial change in b-values.

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

PubMed

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value <0.05, from the biological and functional models). A combined model of 4 variables best predicted long-term functional outcome with explained variance of 49%: neurological impairment (National Institute of Health Stroke Scale; β = 0.402, p < 0.001), age (β = 0.233, p = 0.001), post-stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p < 0.001) and Figure Copy (β = -0.233, p = 0.002) raw scores at baseline explained 42% of the variance in mRS scores at follow-up. Early post-stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

Men still value physical attractiveness in a long-term mate more than women: rejoinder to Eastwick, Neff, Finkel, Luchies, and Hunt (2014).

PubMed

Meltzer, Andrea L; McNulty, James K; Jackson, Grace L; Karney, Benjamin R

2014-03-01

Sexual selection theory and parental investment theory suggest that partner physical attractiveness should more strongly affect men's relationship outcomes than women's relationship outcomes. Nevertheless, the contextual nature of this prediction makes serious methodological demands on studies designed to evaluate it. Given these theories suggest that men value observable aspects of partner attractiveness more than women do only in the context of long-term and reproductively viable relationships, they require that studies testing this sex difference involve (a) participants in long-term relationships, (b) women of child-bearing age, and (c) measures of physical attractiveness that assess observable aspects of appearance. In our original article (Meltzer, McNulty, Jackson, & Karney, 2014), we applied 7 methodological standards that allowed us to meet these 3 criteria and demonstrated that partner physical attractiveness is more strongly associated with men's long-term relationship satisfaction than women's long-term relationship satisfaction. Eastwick, Neff, Finkel, Luchies, and Hunt (2014), in contrast, described an unfocused meta-analysis, a refocused meta-analysis, and new data that all failed to meet these criteria and, not surprisingly, failed to demonstrate such a sex difference. We continue to believe that men value physical attractiveness more than women do, that such preferences have implications for their evaluations of long-term relationships, and that studies properly calibrated to detect such differences will do so. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Mini-Nutritional Assessment, Malnutrition Universal Screening Tool, and Nutrition Risk Screening Tool for the Nutritional Evaluation of Older Nursing Home Residents.

PubMed

Donini, Lorenzo M; Poggiogalle, Eleonora; Molfino, Alessio; Rosano, Aldo; Lenzi, Andrea; Rossi Fanelli, Filippo; Muscaritoli, Maurizio

2016-10-01

Malnutrition plays a major role in clinical and functional impairment in older adults. The use of validated, user-friendly and rapid screening tools for malnutrition in the elderly may improve the diagnosis and, possibly, the prognosis. The aim of this study was to assess the agreement between Mini-Nutritional Assessment (MNA), considered as a reference tool, MNA short form (MNA-SF), Malnutrition Universal Screening Tool (MUST), and Nutrition Risk Screening (NRS-2002) in elderly institutionalized participants. Participants were enrolled among nursing home residents and underwent a multidimensional evaluation. Predictive value and survival analysis were performed to compare the nutritional classifications obtained from the different tools. A total of 246 participants (164 women, age: 82.3 ± 9 years, and 82 men, age: 76.5 ± 11 years) were enrolled. Based on MNA, 22.6% of females and 17% of males were classified as malnourished; 56.7% of women and 61% of men were at risk of malnutrition. Agreement between MNA and MUST or NRS-2002 was classified as "fair" (k = 0.270 and 0.291, respectively; P < .001), whereas the agreement between MNA and MNA-SF was classified as "moderate" (k = 0.588; P < .001). Because of the high percentage of false negative participants, MUST and NRS-2002 presented a low overall predictive value compared with MNA and MNA-SF. Clinical parameters were significantly different in false negative participants with MUST or NRS-2002 from true negative and true positive individuals using the reference tool. For all screening tools, there was a significant association between malnutrition and mortality. MNA showed the best predictive value for survival among well-nourished participants. Functional, psychological, and cognitive parameters, not considered in MUST and NRS-2002 tools, are probably more important risk factors for malnutrition than acute illness in geriatric long-term care inpatient settings and may account for the low predictive value of these tests. MNA-SF seems to combine the predictive capacity of the full version of the MNA with a sufficiently short time of administration. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Role of 18F-FDG PET/CT in the Carcinoma of the Uterus: A Review of Literature

PubMed Central

Musto, Alessandra; Grassetto, Gaia; Marzola, Maria Cristina; Chondrogiannis, Sotirios; Maffione, Anna Margherita; Rampin, Lucia; Fuster, David; Giammarile, Francesco; Colletti, Patrick M.

2014-01-01

In the present review we reported the value of 18F-fluorodeoxyglucose (FDG) PET/CT in face of uterine cancer, in terms of sensitivity, specificity and accuracy. Moreover, we made a comparison with the other imaging techniques currently used to evacuate these tumors including contrast-enhanced CT, contrast enhanced-MRI and transvaginal ultrasonography. FDG PET/CT has been reported to be of particular value in detecting occult metastatic lesions, in prediction of response to treatment and as a pro-gnostic factor. PMID:25323881

Attitudes of Research and Development Professional Federal Employees Toward Value Systems and Operative Goals: A Study of Scientists, Engineers and Managers at a Federal Installation

DTIC Science & Technology

1977-01-01

performance . Vroom (196U) argues two major assumptions: (1) Performance of a person is to be understood in terms of motives (or needs or preferences...and the condition for their satisfaction in the work situation. The level of performance of the worker for a task or job is a direct function of...worker performance , one must include the study of per- sonal value systems as a fourth variable in the prediction of job satisfaction . In essence

Modeling of venturi scrubber efficiency

NASA Astrophysics Data System (ADS)

Crowder, Jerry W.; Noll, Kenneth E.; Davis, Wayne T.

The parameters affecting venturi scrubber performance have been rationally examined and modifications to the current modeling theory have been developed. The modified model has been validated with available experimental data for a range of throat gas velocities, liquid-to-gas ratios and particle diameters and is used to study the effect of some design parameters on collection efficiency. Most striking among the observations is the prediction of a new design parameter termed the minimum contactor length. Also noted is the prediction of little effect on collection efficiency with increasing liquid-to-gas ratio above about 2ℓ m-3. Indeed, for some cases a decrease in collection efficiency is predicted for liquid rates above this value.

The Surgical Apgar Score Predicts Not Only Short-Term Complications But Also Long-Term Prognosis After Esophagectomy.

PubMed

Nakagawa, Akio; Nakamura, Tetsu; Oshikiri, Taro; Hasegawa, Hiroshi; Yamamoto, Masashi; Kanaji, Shingo; Matsuda, Yoshiko; Yamashita, Kimihiro; Matsuda, Takeru; Sumi, Yasuo; Suzuki, Satoshi; Kakeji, Yoshihiro

2017-12-01

The surgical Apgar score (SAS) quantifies three intraoperative factors and predicts postoperative complications, but few reports describe its usefulness in esophagectomy, and no studies to date show its correlation with long-term prognosis after esophagectomy. This study investigated 400 cases in which esophagectomy was performed on esophageal malignant tumors at the authors' hospital from January 2007 to January 2017. In this study, SAS was defined as the sum of the scores of three parameters, namely, estimated blood loss, lowest mean arterial pressure, and lowest heart rate, with values extracted from medical records. Postoperative complications classified as Clavien-Dindo grade 3 or higher were also extracted. The study retrospectively compared the relationship of SAS to postoperative complications and survival. Univariate analysis showed that postoperative complications were significantly associated with hypertension (p = 0.017), thoracotomy (p = 0.012), and SAS ≤ 5 (p < 0.0001), and multivariate analysis showed that hypertension (p = 0.049) and SAS ≤ 5 (p < 0.0001) were significant predictive factors for complications. In the prognostic analysis, log-rank analysis showed that patients with an SAS ≤ 5 had a significantly poorer prognosis than those with a SAS > 5 (p = 0.043), especially for complications classified as clinical stage 2 or higher (p = 0.027). In the multivariate analysis, SAS ≤ 5 was identified as a significantly poor prognostic factor for complications classified as clinical stage 2 or higher (p = 0.029). In this study, SAS was useful not only for predicting short-term complications, but also as a long-term prognostic factor after esophagectomy.

The Apgar Score and Infant Mortality

PubMed Central

Lei, Xiaoping; Zhang, Hao; Mao, Meng; Zhang, Jun

2013-01-01

Objective To evaluate if the Apgar score remains pertinent in contemporary practice after more than 50 years of wide use, and to assess the value of the Apgar score in predicting infant survival, expanding from the neonatal to the post-neonatal period. Methods The U.S. linked live birth and infant death dataset was used, which included 25,168,052 singleton births and 768,305 twin births. The outcome of interest was infant death within 1 year after birth. Cox proportional hazard-model was used to estimate risk ratio of infant mortality with different Apgar scores. Results Among births with a very low Apgar score at five minutes (1–3), the neonatal and post-neonatal mortality rates remained high until term (≥ 37 weeks). On the other hand, among births with a high Apgar score (≥7), neonatal and post-neonatal mortality rate decreased progressively with gestational age. Non-Hispanic White had a consistently higher neonatal mortality than non-Hispanic Black in both preterm and term births. However, for post-neonatal mortality, Black had significantly higher rate than White. The pattern of changes in neonatal and post-neonatal mortality by Apgar score in twin births is essentially the same as that in singleton births. Conclusions The Apgar score system has continuing value for predicting neonatal and post-neonatal adverse outcomes in term as well as preterm infants, and is applicable to twins and in various race/ethnic groups. PMID:23922681

Invited commentary: the incremental value of customization in defining abnormal fetal growth status.

PubMed

Zhang, Jun; Sun, Kun

2013-10-15

Reference tools based on birth weight percentiles at a given gestational week have long been used to define fetuses or infants that are small or large for their gestational ages. However, important deficiencies of the birth weight reference are being increasingly recognized. Overwhelming evidence indicates that an ultrasonography-based fetal weight reference should be used to classify fetal and newborn sizes during pregnancy and at birth, respectively. Questions have been raised as to whether further adjustments for race/ethnicity, parity, sex, and maternal height and weight are helpful to improve the accuracy of the classification. In this issue of the Journal, Carberry et al. (Am J Epidemiol. 2013;178(8):1301-1308) show that adjustment for race/ethnicity is useful, but that additional fine tuning for other factors (i.e., full customization) in the classification may not further improve the ability to predict infant morbidity, mortality, and other fetal growth indicators. Thus, the theoretical advantage of full customization may have limited incremental value for pediatric outcomes, particularly in term births. Literature on the prediction of short-term maternal outcomes and very long-term outcomes (adult diseases) is too scarce to draw any conclusions. Given that each additional variable being incorporated in the classification scheme increases complexity and costs in practice, the clinical utility of full customization in obstetric practice requires further testing.

Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).

PubMed

Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2017-08-01

A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table. All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. The average performance of all algorithm increases due of the decreasing of dimensionality of the unique values of these elements (2697 platforms, 537 organisms, 454 labels, 9 molecules, and 5 types). Our work suggests that experimental metadata such as present in GEO can be accurately predicted using rule mining algorithms. Our work has implications for both prospective and retrospective augmentation of metadata quality, which are geared towards making data easier to find and reuse. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Validation of the cephalosporin intradermal skin test for predicting immediate hypersensitivity: a prospective study with drug challenge.

PubMed

Yoon, S-Y; Park, S Y; Kim, S; Lee, T; Lee, Y S; Kwon, H-S; Cho, Y S; Moon, H-B; Kim, T-B

2013-07-01

Cephalosporin is a major offending agent in terms of drug hypersensitivity along with penicillin. Cephalosporin intradermal skin tests (IDTs) have been widely used; however, their validity for predicting immediate hypersensitivity has not been studied. This study aimed to determine the predictive value of cephalosporin intradermal skin testing before administration of the drug. We prospectively conducted IDTs with four cephalosporins, one each of selected first-, second-, third-, or fourth-generation cephalosporins: ceftezol; cefotetan or cefamandole; ceftriaxone or cefotaxime; and flomoxef, respectively, as well as with penicillin G. After the skin test, whatever the result, one of the tested cephalosporins was administered intravenously and the patient was carefully observed. We recruited 1421 patients who required preoperative cephalosporins. Seventy-four patients (74/1421, 5.2%) were positive to at least one cephalosporin. However, none of responders had immediate hypersensitivity reactions after a challenge dose of the same or different cephalosporin, which were positive in the skin test. Four patients who suffered generalized urticaria and itching after challenge gave negative skin tests for the corresponding drug. The IDT for cephalosporin had a sensitivity of 0%, a specificity of 97.5%, a negative predictive value of 99.7%, and a positive predictive value (PPV) of 0%, when challenged with the same drugs that were positive in the skin test. Routine skin testing with a cephalosporin before its administration is not useful for predicting immediate hypersensitivity because of the extremely low sensitivity and PPV of the skin test (CRIS registration no. KCT0000455). © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Prediction of preterm deliveries from EHG signals using machine learning.

PubMed

Fergus, Paul; Cheung, Pauline; Hussain, Abir; Al-Jumeily, Dhiya; Dobbins, Chelsea; Iram, Shamaila

2013-01-01

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier.

Prediction of Helicobacter pylori status by conventional endoscopy, narrow-band imaging magnifying endoscopy in stomach after endoscopic resection of gastric cancer.

PubMed

Yagi, Kazuyoshi; Saka, Akiko; Nozawa, Yujiro; Nakamura, Atsuo

2014-04-01

To reduce the incidence of metachronous gastric carcinoma after endoscopic resection of early gastric cancer, Helicobacter pylori eradication therapy has been endorsed. It is not unusual for such patients to be H. pylori negative after eradication or for other reasons. If it were possible to predict H. pylori status using endoscopy alone, it would be very useful in clinical practice. To clarify the accuracy of endoscopic judgment of H. pylori status, we evaluated it in the stomach after endoscopic submucosal dissection (ESD) of gastric cancer. Fifty-six patients treated by ESD were enrolled. The diagnostic criteria for H. pylori status by conventional endoscopy and narrow-band imaging (NBI)-magnifying endoscopy were decided, and H. pylori status was judged by two endoscopists. Based on the H. pylori stool antigen test as a diagnostic gold standard, conventional endoscopy and NBI-magnifying endoscopy were compared for their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Interobserver agreement was assessed in terms of κ value. Interobserver agreement was moderate (0.56) for conventional endoscopy and substantial (0.77) for NBI-magnifying endoscopy. The sensitivity, specificity, PPV, and NPV were 0.79, 0.52, 0.70, and 0.63 for conventional endoscopy and 0.91, 0.83, 0.88, and 0.86 for NBI-magnifying endoscopy, respectively. Prediction of H. pylori status using NBI-magnifying endoscopy is practical, and interobserver agreement is substantial. © 2013 John Wiley & Sons Ltd.

Forecasting experiments of a dynamical-statistical model of the sea surface temperature anomaly field based on the improved self-memorization principle

NASA Astrophysics Data System (ADS)

Hong, Mei; Chen, Xi; Zhang, Ren; Wang, Dong; Shen, Shuanghe; Singh, Vijay P.

2018-04-01

With the objective of tackling the problem of inaccurate long-term El Niño-Southern Oscillation (ENSO) forecasts, this paper develops a new dynamical-statistical forecast model of the sea surface temperature anomaly (SSTA) field. To avoid single initial prediction values, a self-memorization principle is introduced to improve the dynamical reconstruction model, thus making the model more appropriate for describing such chaotic systems as ENSO events. The improved dynamical-statistical model of the SSTA field is used to predict SSTA in the equatorial eastern Pacific and during El Niño and La Niña events. The long-term step-by-step forecast results and cross-validated retroactive hindcast results of time series T1 and T2 are found to be satisfactory, with a Pearson correlation coefficient of approximately 0.80 and a mean absolute percentage error (MAPE) of less than 15 %. The corresponding forecast SSTA field is accurate in that not only is the forecast shape similar to the actual field but also the contour lines are essentially the same. This model can also be used to forecast the ENSO index. The temporal correlation coefficient is 0.8062, and the MAPE value of 19.55 % is small. The difference between forecast results in spring and those in autumn is not high, indicating that the improved model can overcome the spring predictability barrier to some extent. Compared with six mature models published previously, the present model has an advantage in prediction precision and length, and is a novel exploration of the ENSO forecast method.

RELATIVISTIC MEASUREMENTS FROM TIMING THE BINARY PULSAR PSR B1913+16

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weisberg, J. M.; Huang, Y., E-mail: jweisber@carleton.edu

2016-09-20

We present relativistic analyses of 9257 measurements of times-of-arrival from the first binary pulsar, PSR B1913+16, acquired over the last 35 years. The determination of the “Keplerian” orbital elements plus two relativistic terms completely characterizes the binary system, aside from an unknown rotation about the line of sight, leading to a determination of the masses of the pulsar and its companion: 1.438 ± 0.001 M {sub ☉} and 1.390 ± 0.001 M {sub ☉}, respectively. In addition, the complete system characterization allows for the creation of relativistic gravitation test by comparing measured and predicted sizes of various relativistic phenomena. Wemore » find that the ratio of the observed orbital period decrease caused by gravitational wave damping (corrected by a kinematic term) to the general relativistic prediction is 0.9983 ± 0.0016, thereby confirms the existence and strength of gravitational radiation as predicted by general relativity. For the first time in this system, we have also successfully measured the two parameters characterizing the Shapiro gravitational propagation delay, and found that their values are consistent with general relativistic predictions. For the first time in any system, we have also measured the relativistic shape correction to the elliptical orbit, δ {sub θ} , although its intrinsic value is obscured by currently unquantified pulsar emission beam aberration. We have also marginally measured the time derivative of the projected semimajor axis, which, when improved in combination with beam aberration modeling from geodetic precession observations, should ultimately constrain the pulsar’s moment of inertia.« less

A prospective observational study to evaluate the effect of social and personality factors on continuous positive airway pressure (CPAP) compliance in obstructive sleep apnoea syndrome.

PubMed

Gulati, Atul; Ali, Masood; Davies, Mike; Quinnell, Tim; Smith, Ian

2017-03-22

Compliance with CPAP treatment for OSAS is not reliably predicted by the severity of symptoms or physiological variables. We examined a range of factors which could be measured before CPAP initiation to look for predictors of compliance. This was a prospective cohort-study of CPAP treatment for OSAS, recording; socio-economic status, education, type D personality and clinician's prediction of compliance. We recruited 265 subjects, of whom 221 were still using CPAP at 6 months; median age 53 years, M: F, 3.4:1, ESS 15 and pre-treatment ODI 21/h. Median compliance at 6 months was 5.6 (3.4- 7.1) hours/night with 73.3% of subjects using CPAP ≥4 h/night. No association was found between compliance and different socio-economic classes for people in work, type D personality, education level, sex, age, baseline ESS or ODI. The clinician's initial impression could separate groups of good and poor compliers but had little predictive value for individual patients. Compared to subjects who were working, those who were long term unemployed had a lower CPAP usage and were more likely to use CPAP < 4 h a night (OR 4.6; p value 0.011). A high Beck Depression Index and self-reported anxiety also predicted poor compliance. In our practice there is no significant association between CPAP compliance with socio-economic status, education or personality type. Long term unemployed or depressed individuals may need more intensive support to gain the optimal benefit from CPAP.

The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making.

PubMed

Lindahl, Jonas; Danell, Rickard

The aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups-top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty into risk when we are choosing decision thresholds in bibliometricly informed decision making. The significance of our results are discussed from the point of view of a science policy and management.

Approaches for predicting long-term sickness absence. Re: Schouten et al. "Screening manual and office workers for risk of long-term sickness absence: cut-off points for the Work Ability Index".

PubMed

van Amelsvoort, Ludovic Gpm; Jansen, Nicole W H; Kant, I Jmert

2015-05-01

We read with much interest the article of Schouten et al (1) on identifying workers with a high risk for future long-term sickness absence using the Work Ability Index (WAI). The ability to identify high-risk workers might facilitate targeted interventions for such workers and, consequently, can reduce sickness absence levels and improve workers' health. Earlier studies by both Tamela et al (2), Kant et al (3), and Lexis et al (4) have demonstrated that such an approach, based on the identification of high-risk workers and a subsequent intervention, can be effectively applied in practice to reduce sickness absence significantly. The reason for our letter on Schouten et al's article is twofold. First, by including workers already on sick leave in a study predicting long-term sick leave will result in an overestimation of the predictive properties of the instrument and biased predictors, especially when also the outcome of interest is included as a factor in the prediction model. Second, we object to the use of the term "screening" when subjects with the condition screened for are included in the study. Reinforced by the inclusion of sickness absence in the prediction model, including workers already on sick leave will shift the focus of the study findings towards the prediction of (re)current sickness absence and workers with a below-average return-to-work rate, rather than the identification of workers at high risk for the onset of future long-term sickness absence. The possibilities for prevention will shift from pure secondary prevention to a mix of secondary and tertiary prevention. As a consequence, the predictors of the model presented in the Schouten et al article can be used as a basis for tailoring neither preventive measures nor interventions. Moreover, including the outcome (sickness absence) as a predictor in the model, especially in a mixed population including workers with and without the condition (on sick leave), will result in biased predictors and an overestimation of the predictive value. A methodological approach of related issues is provided in the works of Glymour et al (5) and Hamilton et al (6). This phenomenon is even more clearly illustrated by the predictive properties of the workability index, as described by Alavinia et al (7, page 328), which reported that "when adjusted for individual characteristics, lifestyle factors, and work characteristics, two dimensions of the WAI were significant predictors for both moderate and long durations of sickness absence: (i) the presence of sickness absence in the past 12 months prior to the medical examination and (ii) experienced limitations due to health problems." So, when applied to the study by Schouten et al (1), this means that most of the predictive value would be related to the factors "sickness absence in the past 12 months". In addition, we object to the use of the term "screening" in the Schouten et al study as it includes workers with the intended outcome (long-term sickness absence). One can identify three separate aims to study the longitudinal association between risk factors and subsequent long-term sickness absence: (i) to establish causal risk factors for long-term sickness absence, often to find clues for primary preventive strategies (beyond the scope here); (ii) to identify high-risk workers who are still at work and might benefit from an intervention before sickness absence occurs (secondary prevention); and (iii) to identify workers on sick leave who might suffer a below-average return-to-work rate or have a high risk for the recurrence of (long-term) sickness absence and might benefit from intensification or optimization of the return-to-work process (tertiary prevention). In this light, one needs to separate screening instruments from predictive instruments and reserve the term "screening" for the situation as defined by Wilson and Junger (8, page 7): "The object of screening for disease is to discover those among the apparently well who are in fact suffering from disease" (ie, situations of secondary prevention). This means that, when applying this definition on long-term sickness absence under the precondition that the individuals are still at work, screening enables the identification of high-risk individuals in the early "stages" of a "disease" that can progress into long-term sickness absence. In the case of the Schouten et al study, the population at risk, as derived from their predictive instrument, consists of workers with and without sickness absence, and as such excludes the use of the term "screening" in this case. To conclude, we have substantiated that, in addition to correct usage of the term "screening", careful selection of the study population, predictors and most importantly the aim of the predictive model are essential in the process of developing predictive instruments aimed at identifying workers at high risk of long-term sickness absence. Two fundamentally different approaches are possible. One approach aims at identifying workers on sick leave with either a below-average chance to return to work an/or a high risk for a successive episode of long-term sickness absence. From a methodological and practical point of view, such an instrument should be developed and validated among workers already on sick leave. A second approach aims at identifying workers who are still at work but at high risk for future long-term sickness absence. To develop and validate such an instrument, a study sample where workers already on sick leave are excluded is a prerequisite. Such instruments fit in a pro-active approach of preventing future sickness absence, where an early intervention can be offered to those workers with an increased risk for future sickness absence.

Excited heavy baryons and their symmetries III: Phenomenology

NASA Astrophysics Data System (ADS)

Baccouche, Z. Aziza; Chow, Chi-Keung; Cohen, Thomas D.; Gelman, Boris A.

2001-12-01

Phenomenological applications of an effective theory of low-lying excited states of charm and bottom isoscalar baryons are discussed at leading and next-to-leading order in the combined heavy-quark and large- Nc expansion. The combined expansion is formulated in terms of the counting parameter λ˜1/ mQ,1/ Nc; the combined expansion is in powers of λ1/2. We work up to next-to-leading order. We obtain model-independent predictions for the excitation energies, the semileptonic form factors and electromagnetic decay rates. At leading order in the combined expansion these observables are given in terms of one phenomenological constant which can be determined from the excitation energy of the first excited state of Λc baryon. At next-to-leading order an additional phenomenological constant is required. The spin-averaged mass of the doublet of the first orbitally excited state of Λb is predicted to be approximately 5920 MeV. It is shown that in the combined limit at leading and next-to-leading order there is only one independent form factor describing Λ b→Λ cℓ ν¯; similarly, Λ b→Λ c∗ℓ ν¯ and Λ b→Λ c1ℓ ν¯ decays are described by a single independent form factor. These form factors are calculated at leading and next-to-leading order in the combined expansion. The value of the Λ b→Λ cℓ ν¯ form factor at zero recoil is predicted to be 0.998 at leading order which is very close to HQET value of unity. The electromagnetic decay rates of the first excited states of Λc and Λb are determined at leading and next-to-leading order. The ratio of radiative decay rates Γ(Λ c∗→Λ cγ)/Γ(Λ b1→Λ bγ) is predicted to be approximately 0.2, greatly different from the heavy-quark effective theory value of unity.

Discriminatory power of common genetic variants in personalized breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Wu, Yirong; Abbey, Craig K.; Liu, Jie; Ong, Irene; Peissig, Peggy; Onitilo, Adedayo A.; Fan, Jun; Yuan, Ming; Burnside, Elizabeth S.

2016-03-01

Technology advances in genome-wide association studies (GWAS) has engendered optimism that we have entered a new age of precision medicine, in which the risk of breast cancer can be predicted on the basis of a person's genetic variants. The goal of this study is to evaluate the discriminatory power of common genetic variants in breast cancer risk estimation. We conducted a retrospective case-control study drawing from an existing personalized medicine data repository. We collected variables that predict breast cancer risk: 153 high-frequency/low-penetrance genetic variants, reflecting the state-of-the-art GWAS on breast cancer, mammography descriptors and BI-RADS assessment categories in the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We trained and tested naïve Bayes models by using these predictive variables. We generated ROC curves and used the area under the ROC curve (AUC) to quantify predictive performance. We found that genetic variants achieved comparable predictive performance to BI-RADS assessment categories in terms of AUC (0.650 vs. 0.659, p-value = 0.742), but significantly lower predictive performance than the combination of BI-RADS assessment categories and mammography descriptors (0.650 vs. 0.751, p-value < 0.001). A better understanding of relative predictive capability of genetic variants and mammography data may benefit clinicians and patients to make appropriate decisions about breast cancer screening, prevention, and treatment in the era of precision medicine.

Comment on "The Predicted Size of Cycle 23 Based on the Inferred three-cycle Quasiperiodicity of the Planetary Index Ap"

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

1999-01-01

Recently, Ahluwalia reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasiperiodicity in them." Furthermore, on the basis of this inferred quasiperiodicity, he asserted that cycle 23 represents the initial cycle in a new three-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum", a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselin et al. and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be readdressed, and these issues form the basis of this comment. First, Ahluwalia appears to have based his analysis on a data set of Ap index values that is erroneous. For example, he depicts for the interval of 1932-1997 the variation of the Ap index in terms of annual averages, contrasting them against annual averages of sunspot number (SSN), and he lists for cycles 17-23 the minimum and maximum value of each, as well as the years in which they occur and a quantity which he calls "Amplitude" (defined as the numeric difference between the maximum and minimum values). In particular, he identifies the minimum Ap index (i.e., the minimum value of the Ap index in the vicinity of sunspot cycle minimum, which usually occurs in the year following sunspot minimum and which will be called hereafter, simply, Ap min) and the year in which it occur for cycles 17 - 23 respectively.

Experimental test of the PCAC-hypothesis in charged current neutrino and antineutrino interactions on protons

NASA Astrophysics Data System (ADS)

Jones, G. T.; Jones, R. W. L.; Kennedy, B. W.; O'Neale, S. W.; Klein, H.; Morrison, D. R. O.; Schmid, P.; Wachsmuth, H.; Miller, D. B.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hoffmann, E.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Allport, P.; Myatt, G.; Radojicic, D.; Bullock, F. W.; Burke, S.

1987-03-01

Data obtained with the bubble chamber BEBC at CERN are used for the first significant test of Adler's prediction for the neutrino and antineutrino-proton scattering cross sections at vanishing four-momentum transfer squared Q 2. An Extended Vector Meson Dominance Model (EVDM) is applied to extrapolate Adler's prediction to experimentally accessible values of Q 2. The data show good agreement with Adler's prediction for Q 2→0 thus confirming the PCAC hypothesis in the kinematical region of high leptonic energy transfer ν>2 GeV. The good agreement of the data with the theoretical predictions also at higher Q 2, where the EVDM terms are dominant, also supports this model. However, an EVDM calculation without PCAC is clearly ruled out by the data.

Ex Vivo Perfusion Characteristics of Donation After Cardiac Death Kidneys Predict Long-Term Graft Survival.

PubMed

Sevinc, M; Stamp, S; Ling, J; Carter, N; Talbot, D; Sheerin, N

2016-12-01

Ex vivo perfusion is used in our unit for kidneys donated after cardiac death (DCD). Perfusion flow index (PFI), resistance, and perfusate glutathione S-transferase (GST) can be measured to assess graft viability. We assessed whether measurements taken during perfusion could predict long-term outcome after transplantation. All DCD kidney transplants performed from 2002 to 2014 were included in this study. The exclusion criteria were: incomplete data, kidneys not machine perfused, kidneys perfused in continuous mode, and dual transplantation. There were 155 kidney transplantations included in the final analysis. Demographic data, ischemia times, donor hypertension, graft function, survival and machine perfusion parameters after 3 hours were analyzed. Each perfusion parameter was divided into 3 groups as high, medium, and low. Estimated glomerular filtration rate was calculated at 12 months and then yearly after transplantation. There was a significant association between graft survival and PFI and GST (P values, .020 and .022, respectively). PFI was the only independent parameter to predict graft survival. A low PFI during ex vivo hypothermic perfusion is associated with inferior graft survival after DCD kidney transplantation. We propose that PFI is a measure of the health of the graft vasculature and that a low PFI indicates vascular disease and therefore predicts a worse long-term outcome. Copyright © 2016 Elsevier Inc. All rights reserved.

Value of imaging studies after a first febrile urinary tract infection in young children: data from Italian renal infection study 1.

PubMed

Montini, Giovanni; Zucchetta, Pietro; Tomasi, Lisanna; Talenti, Enrico; Rigamonti, Waifro; Picco, Giorgio; Ballan, Alberto; Zucchini, Andrea; Serra, Laura; Canella, Vanna; Gheno, Marta; Venturoli, Andrea; Ranieri, Marco; Caddia, Valeria; Carasi, Carla; Dall'amico, Roberto; Hewitt, Ian

2009-02-01

We examined the diagnostic accuracy of routine imaging studies (ultrasonography and micturating cystography) for predicting long-term parenchymal renal damage after a first febrile urinary tract infection. This study addressed the secondary objective of a prospective trial evaluating different antibiotic regimens for the treatment of acute pyelonephritis. Data for 300 children < or =2 years of age, with normal prenatal ultrasound results, who completed the diagnostic follow-up evaluation (ultrasonography and technetium-99m-dimercaptosuccinic acid scanning within 10 days, cystography within 2 months, and repeat technetium-99m-dimercaptosuccinic acid scanning at 12 months to detect scarring) were analyzed. Outcome measures were sensitivity, specificity, and negative and positive predictive values for ultrasonography and cystography in predicting parenchymal renal damage on the 12-month technetium-99m-dimercaptosuccinic acid scans. The kidneys and urinary tracts were mostly normal. The acute technetium-99m-dimercaptosuccinic acid scans showed pyelonephritis in 54% of cases. Renal scarring developed in 15% of cases. The ultrasonographic and cystographic findings were poor predictors of long-term damage, showing minor sonographic abnormalities for 12 and reflux for 23 of the 45 children who subsequently developed scarring. The benefit of performing ultrasonography and scintigraphy in the acute phase or cystourethrography is minimal. Our findings support (1) technetium-99m-dimercaptosuccinic acid scintigraphy 6 months after infection to detect scarring that may be related to long-term hypertension, proteinuria, and renal function impairment (although the degree of scarring was generally minor and did not impair renal function) and (2) continued surveillance to identify recurrent urinary tract infections that may warrant further investigation.

Adenosine Diphosphate-Induced Platelet-Fibrin Clot Strength: A New Thrombelastographic Indicator of Long-Term Post-Stenting Ischemic Events

PubMed Central

Gurbel, Paul A.; Bliden, Kevin P.; Navickas, Irene A.; Mahla, Elizabeth; Dichiara, Joseph; Suarez, Thomas A.; Antonino, Mark J.; Tantry, Udaya S.; Cohen, Eli

2010-01-01

Background Post-stenting ischemic events occur despite dual antiplatelet therapy suggesting that a “one size fits all” antithrombotic strategy has significant limitations. Ex vivo platelet function measurements may facilitate risk stratification and personalized antiplatelet therapy. Methods We investigated the prognostic utility of the strength of ADP-induced (MAADP) and thrombin-induced (MATHROMBIN) platelet-fibrin clots measured by thrombelastography and ADP-induced light transmittance aggregation (LTAADP) in 225 serial patients following elective stenting treated with aspirin and clopidogrel. Ischemic and bleeding events were assessed over three-years. Results Overall, 59 (26 %) first ischemic events occurred. Patients with ischemic events had higher MAADP, MATHROMBIN, and LTAADP (p<0.0001 for all comparisons). By receiver operating characteristic curve analysis, MAADP > 47mm had the best predictive value of long-term ischemic events compared to other measurements (p<0.0001) with an area under the curve = 0.84 [95% CI 0.78 – 0.89, p < 0.0001]. The univariate Cox proportional hazards model identified MAADP >47mm, MATHROMBIN >69mm, and LTA ADP >34% as significant independent predictors of first ischemic events at the three-year time point, with hazard ratios of 10.3 (p<0.0001), 3.8 (p<0.0001), and 4.8 (p<0.0001) respectively. Fifteen bleeding events occurred. Receiver operator characteristic curve and quartile analysis suggest MAADP ≤ 31 as a predictive value for bleeding. Conclusion This study is the first demonstration of the prognostic utility of MAADP in predicting long term event occurrence following stenting. The quantitative assessment of ADP-stimulated platelet-fibrin clot strength measured by thrombelastography can serve as a future tool in investigations of personalized antiplatelet treatment designed to reduce ischemic events and bleeding. PMID:20691842

Adenosine diphosphate-induced platelet-fibrin clot strength: a new thrombelastographic indicator of long-term poststenting ischemic events.

PubMed

Gurbel, Paul A; Bliden, Kevin P; Navickas, Irene A; Mahla, Elizabeth; Dichiara, Joseph; Suarez, Thomas A; Antonino, Mark J; Tantry, Udaya S; Cohen, Eli

2010-08-01

Poststenting ischemic events occur despite dual-antiplatelet therapy, suggesting that a "one size fits all" antithrombotic strategy has significant limitations. Ex vivo platelet function measurements may facilitate risk stratification and personalized antiplatelet therapy. We investigated the prognostic utility of the strength of adenosine diphosphate (ADP)-induced (MA(ADP)) and thrombin-induced (MA(THROMBIN)) platelet-fibrin clots measured by thrombelastography and ADP-induced light transmittance aggregation (LTA(ADP)) in 225 serial patients after elective stenting treated with aspirin and clopidogrel. Ischemic and bleeding events were assessed over 3 years. Overall, 59 (26%) first ischemic events occurred. Patients with ischemic events had higher MA(ADP), MA(THROMBIN), and LTA(ADP) (P < .0001 for all comparisons). By receiver operating characteristic curve analysis, MA(ADP) >47 mm had the best predictive value of long-term ischemic events compared with other measurements (P < .0001), with an area under the curve = 0.84 (95% CI 0.78-0.89, P < .0001). The univariate Cox proportional hazards model identified MA(ADP) >47 mm, MA(THROMBIN) >69 mm, and LTA(ADP) >34% as significant independent predictors of first ischemic events at the 3-year time point, with hazard ratios of 10.3 (P < .0001), 3.8 (P < .0001), and 4.8 (P < .0001), respectively. Fifteen bleeding events occurred. Receiver operating characteristic curve and quartile analysis suggests MA(ADP)

Early relations between language development and the quality of mother-child interaction in very-low-birth-weight children.

PubMed

Stolt, S; Korja, R; Matomäki, J; Lapinleimu, H; Haataja, L; Lehtonen, L

2014-05-01

It is not clearly understood how the quality of early mother-child interaction influences language development in very-low-birth-weight children (VLBW). We aim to analyze associations between early language and the quality of mother-child interaction, and, the predictive value of the features of early mother-child interaction on language development at 24 months of corrected age in VLBW children. A longitudinal prospective follow-up study design was used. The participants were 28 VLBW children and 34 full-term controls. Language development was measured using different methods at 6, 12 and at 24 months of age. The quality of mother-child interaction was assessed using PC-ERA method at 6 and at 12 months of age. Associations between the features of early interaction and language development were different in the groups of VLBW and full-term children. There were no significant correlations between the features of mother-child interaction and language skills when measured at the same age in the VLBW group. Significant longitudinal correlations were detected in the VLBW group especially if the quality of early interactions was measured at six months and language skills at 2 years of age. However, when the predictive value of the features of early interactions for later poor language performance was analyzed separately, the features of early interaction predicted language skills in the VLBW group only weakly. The biological factors may influence on the language development more in the VLBW children than in the full-term children. The results also underline the role of maternal and dyadic factors in early interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

YKL-40, CCL18 and SP-D predict mortality in patients hospitalized with community-acquired pneumonia.

PubMed

Spoorenberg, Simone M C; Vestjens, Stefan M T; Rijkers, Ger T; Meek, Bob; van Moorsel, Coline H M; Grutters, Jan C; Bos, Willem Jan W

2017-04-01

The aim of this study was to investigate the prognostic value of four biomarkers, YKL-40, chemokine (C-C motif) ligand 18 (CCL18), surfactant protein-D (SP-D) and CA 15-3, in patients admitted with community-acquired pneumonia (CAP). These markers have been studied extensively in chronic pulmonary disease, but in acute pulmonary disease their prognostic value is unknown. A total of 289 adult patients who were hospitalized with CAP and participated in a randomized controlled trial were enrolled. Biomarker levels were measured on the day of admission. Intensive care unit admission, 30-day, 1-year and long-term mortality (median follow-up of 5.4 years, interquartile range (IQR): 4.7-6.1) were recorded as outcomes. Median YKL-40 and CCL18 levels were significantly higher and levels of SP-D were significantly lower in CAP patients compared to healthy controls. Significantly higher YKL-40, CCL18 and SP-D levels were found in patients classified in pneumonia severity index classes 4-5 and with a CURB-65 score ≥2 compared to patients with less severe pneumonia. Furthermore, these three markers were significant predictors for long-term mortality in multivariate analysis and compared with C-reactive protein and procalcitonin level on admission, area under the curves were higher for 30-day, 1-year and long-term mortality. CA 15-3 levels were less predictive. YKL-40, CCL18 and SP-D levels were higher in patients with more severe pneumonia, possibly reflecting the extent of pulmonary inflammation. Of these, YKL-40 most significantly predicts mortality for CAP. © 2016 Asian Pacific Society of Respirology.

A Blueprint for the Ecological Monitoring of Australia's Oceans.

NASA Astrophysics Data System (ADS)

Bax, N. J.; Hayes, K. R.; Dambacher, J. M.; Hosack, G. R.; Dunstan, P. K.; Fulton, E.; Thompson, P. A.; Hartog, J. R.; Hobday, A. J.; Bradford, R.; Foster, S.; Hedge, P.; Smith, D.; Marshall, C. M.

2016-02-01

Monitoring Australia's marine area is fundamental to understanding and documenting how the ocean is changing in response to human pressures. Fifty-four key ecological features (KEFs) were identified as areas of particular value to the Australian Government over the last 8 years. These were divided into six reporting groups: areas of enhanced pelagic productivity, canyons, deep seabeds, seamounts, shelf reefs and seabeds. Ecosystem models were built for 33 KEF systems that have the strongest datasets, based on a theoretical understanding of how they function. Human pressures were identified by regional specialists and combined with the KEF models to create a set of medium-term pressure scenarios for each KEF. Between four and 25 pressure scenarios were identified for each KEF. Examples of human pressures include the strengthening of the East Australian Current and shifts in ocean upwelling due to climate change, major fluctuations in pelagic fish and fur seal populations, and fishing, shipping and oil and gas activities. KEF models encompass parts of the ecosystem that have potential to be monitored as long-term indicators that increase, decrease, or remain unchanged under each pressure scenario. Suitable indicators are those that respond in predictable ways across all pressure scenarios for a KEF. Results from pressure scenarios developed to test indicators for Australia's nine enhanced pelagic productivity KEFs will be presented. Satellite observations were analysed to tease out the long-term trend in phytoplankton and ocean upwelling. The comparison of predicted and observed trends in indicators leads to an improved understanding of KEF systems and the utility of the indicators. A change in indicator is a signal that something was happening to a valued system. The prediction-observation process would explain why. This process is repeatable and can be updated as new information comes available.

A three-part geometric model to predict the radar backscatter from wheat, corn, and sorghum

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Eger, G. W., III; Kanemasu, E. T.

1982-01-01

A model to predict the radar backscattering coefficient from crops must include the geometry of the canopy. Radar and ground-truth data taken on wheat in 1979 indicate that the model must include contributions from the leaves, from the wheat head, and from the soil moisture. For sorghum and corn, radar and ground-truth data obtained in 1979 and 1980 support the necessity of a soil moisture term and a leaf water term. The Leaf Area Index (LAI) is an appropriate input for the leaf contribution to the radar response for wheat and sorghum, however the LAI generates less accurate values for the backscattering coefficient for corn. Also, the data for corn and sorghum illustrate the importance of the water contained in the stalks in estimating the radar response.

Neonatal heart rate prediction.

PubMed

Abdel-Rahman, Yumna; Jeremic, Aleksander; Tan, Kenneth

2009-01-01

Technological advances have caused a decrease in the number of infant deaths. Pre-term infants now have a substantially increased chance of survival. One of the mechanisms that is vital to saving the lives of these infants is continuous monitoring and early diagnosis. With continuous monitoring huge amounts of data are collected with so much information embedded in them. By using statistical analysis this information can be extracted and used to aid diagnosis and to understand development. In this study we have a large dataset containing over 180 pre-term infants whose heart rates were recorded over the length of their stay in the Neonatal Intensive Care Unit (NICU). We test two types of models, empirical bayesian and autoregressive moving average. We then attempt to predict future values. The autoregressive moving average model showed better results but required more computation.

Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 3. The large catchment model

NASA Astrophysics Data System (ADS)

Sivapalan, Murugesu; Viney, Neil R.; Jeevaraj, Charles G.

1996-03-01

This paper presents an application of a long-term, large catchment-scale, water balance model developed to predict the effects of forest clearing in the south-west of Western Australia. The conceptual model simulates the basic daily water balance fluxes in forested catchments before and after clearing. The large catchment is divided into a number of sub-catchments (1-5 km2 in area), which are taken as the fundamental building blocks of the large catchment model. The responses of the individual subcatchments to rainfall and pan evaporation are conceptualized in terms of three inter-dependent subsurface stores A, B and F, which are considered to represent the moisture states of the subcatchments. Details of the subcatchment-scale water balance model have been presented earlier in Part 1 of this series of papers. The response of any subcatchment is a function of its local moisture state, as measured by the local values of the stores. The variations of the initial values of the stores among the subcatchments are described in the large catchment model through simple, linear equations involving a number of similarity indices representing topography, mean annual rainfall and level of forest clearing.The model is applied to the Conjurunup catchment, a medium-sized (39·6 km2) catchment in the south-west of Western Australia. The catchment has been heterogeneously (in space and time) cleared for bauxite mining and subsequently rehabilitated. For this application, the catchment is divided into 11 subcatchments. The model parameters are estimated by calibration, by comparing observed and predicted runoff values, over a 18 year period, for the large catchment and two of the subcatchments. Excellent fits are obtained.

Prognostic value of tumour regression grade in locally advanced rectal cancer: a systematic review and meta-analysis.

PubMed

Kong, J C; Guerra, G R; Warrier, S K; Lynch, A Craig; Michael, M; Ngan, S Y; Phillips, W; Ramsay, G; Heriot, A G

2018-03-27

The current standard of care for locally advanced rectal cancer involves neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision. There is a spectrum of response to neoadjuvant therapy; however, the prognostic value of tumour regression grade (TRG) in predicting disease-free survival (DFS) or overall survival (OS) is inconsistent in the literature. This study was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search was undertaken using Ovid MEDLINE, Embase and Google Scholar. Inclusion criteria were Stage II and III locally advanced rectal cancer treated with long-course CRT followed by radical surgery. The aim of the meta-analysis was to assess the prognostic implication of each TRG for rectal cancer following neoadjuvant CRT. Long-term prognosis was assessed. The main outcome measures were DFS and OS. A random effects model was performed to pool the hazard ratio (HR) from all included studies. There were 4875 patients from 17 studies, with 775 (15.9%) attaining a pathological complete response (pCR) and 719 (29.9%) with no response. A significant association with OS was identified from a pooled-estimated HR for pCR (HR = 0.47, P = 0.002) and nonresponding tumours (HR = 2.97; P < 0.001). Previously known tumour characteristics, such as ypN, lymphovascular invasion and perineural invasion, were also significantly associated with DFS and OS, with estimated pooled HRs of 2.2, 1.4 and 2.3, respectively. In conclusion, the degree of TRG was of prognostic value in predicting long-term outcomes. The current challenge is the development of a high-validity tests to predict pCR. Colorectal Disease © 2018 The Association of Coloproctology of Great Britain and Ireland.

[Surgical revascularisation of the heart in patients with chronic ischaemic cardiomyopathy and leftventricular ejection fraction of less than 30%].

PubMed

Velinović, Milos; Kocica, Mladen; Vranes, Mile; Mikić, Aleksandar; Vukomanović, Vlada; Davidović, Lazar; Obrenović-Krićanski, Biljana; Cvetkovic, Slobodan; Soski, Ljiljana; Ristić, Arsen D

2005-01-01

Patients suffering from chronic ischaemic cardiomyopathy and left ventricular ejection fraction (LVEF) lower than 30% represent a difficult and controversial population for surgical treatment. The aim of this study was to evaluate the effects of surgical treatment on the early and long-term outcome of these patients. The patient population comprised 50 patients with LVEF < 30% (78% male, mean age: 58.3 years, range: 42-75 years) who underwent surgical myocardial revascularisation during the period 1995-2000. Patients with left ventricular aneurysms or mitral valve insufficiency were excluded from the study. The following echocardiography parameters were evaluated as possible prognostic indicators: LVEF, fraction of shortening (FS), left ventricular systolic and diastolic diameters (LVEDD, LVESD) and volumes (LVEDV, LVESV), as well as their indexed values (LVESVI). Fifteen patients (30%) died during the follow-up, 2/50 intraoperatively (4%). The presence of diabetes mellitus, previous myocardial infarction, main left coronary artery disease, and three-vessel disease, correlated significantly with the surgical outcomes. The patient's age, family history, smoking habits, hypertension, hyperlipidaemia, history of stroke, peripheral vascular disease, and renal failure, did not correlate with the mortality rate. A comparison of preoperative echocardiography parameters between survivors and non-survivors revealed significantly divergent LVEF, LVEDD, LVESD, LVEDV, LVESV, and LVESVI values. Preoperative LVESVI offered the highest predictive value (R = 0.595). Diabetes mellitus, history of myocardial infarction, stenosis of the main branch, and three-vessel disease, significantly affected the perioperative and long-term outcome of surgical revascularisation in patients with ischaemic cardiomyopathy and LVEF < 30%. In survivors, LVEF, FS, and systolic and diastolic echocardiography parameters, as well as their indexed values, significantly improved after surgical revascularisation. LVESVI provided the highest predictive value for mortality.

A clinical study of ischaemic strokes with micro-albuminuria for risk stratification, short-term predictive value and outcome.

PubMed

Das, Sukdeb; Yadav, Ujjal; Ghosh, Kartik Chandra; Panchadhyayee, Sujoy; Kundu, Shib Shankar; Ganguly, Prasanta Kumar

2012-12-01

Stroke results more than 4.3 million deaths worldwide per annum and 85% of all strokes are ischaemic in nature. Besides numerous modifiable and non-modifiable known risk factors, microalbuminuria is thought to be an important marker of global endothelial dysfunction and associated with cardiovascular disease including stroke. Fifty ischaemic stroke cases and 50 (age, sex matched) control subjects were subjected to study to compare and evaluate risk stratification of micro-albuminuria, its predictive value and outcome on day 1 and day 7 among admitted ischaemic stroke cases.The result was found that micro-albuminuria was present in 66% of ischaemic stroke cases compared to only 8% of control group (p < 0.001). Most validated National Institute of Health Stroke Scale (NIHSS) score was used for evaluation and calculation of predictive value and outcome of micro-albuminuria positive patient where higher value indicates poor prognosis, and the result was mean NIHSS score 29.12 versus 18.88 between two groups of strokes ie, with and without micro-albuminuria. Out of 50 ischaemic stroke patients 33 (66%) had micro-albuminuria. Among 11 patients who died, 10 (90.9%) had micro-albuminuria and NIHSS score was 33.64 and 25.0 on day 1 and day 7. Among 39 patients who were discharged, 23 patients (58.97%) were MA positive and NIHSS score was much less than death group ie, 23.38 and 16.38 on day 1 and day 7 respectively. So this study reveals micro-albuminuria itself results higher risk for ischaemic stroke compared to control group and it shows good predictive value for early assessment of clinical severity and subsequent fatal outcome. This is also simple, cost effective and affordable.

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

2013-12-15

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Normalization and extension of single-collector efficiency correlation equation

NASA Astrophysics Data System (ADS)

Messina, Francesca; Marchisio, Daniele; Sethi, Rajandrea

2015-04-01

The colloidal transport and deposition are important phenomena involved in many engineering problems. In the environmental engineering field the use of micro- and nano-scale zerovalent iron (M-NZVI) is one of the most promising technologies for groundwater remediation. Colloid deposition is normally studied from a micro scale point of view and the results are then implemented in macro scale models that are used to design field-scale applications. The single collector efficiency concept predicts particles deposition onto a single grain of a complex porous medium in terms of probability that an approaching particle would be retained on the solid grain. In literature, many different approaches and equations exist to predict it, but most of them fail under specific conditions (e.g. very small or very big particle size and very low fluid velocity) because they predict efficiency values exceeding unity. By analysing particle fluxes and deposition mechanisms and performing a mass balance on the entire domain, the traditional definition of efficiency was reformulated and a novel total flux normalized correlation equation is proposed for predicting single-collector efficiency under a broad range of parameters. It has been formulated starting from a combination of Eulerian and Lagrangian numerical simulations, performed under Smoluchowski-Levich conditions, in a geometry which consists of a sphere enveloped by a control volume. In order to guarantee the independence of each term, the correlation equation is derived through a rigorous hierarchical parameter estimation process, accounting for single and mutual interacting transport mechanisms. The correlation equation provides efficiency values lower than one over a wide range of parameters and is valid both for point and finite-size particles. A reduced form is also proposed by elimination of the less relevant terms. References 1. Yao, K. M.; Habibian, M. M.; Omelia, C. R., Water and Waste Water Filtration - Concepts and Applications. Environ Sci Technol 1971, 5, (11), 1105-&. 2. Tufenkji, N., and M. Elimelech, Correlation equation for predicting single-collector efficiency in physicochemical filtration in saturated porous media. Environmental Science & Technology 2004 38(2):529-536. 3. Boccardo, G.; Marchisio, D. L.; Sethi, R., Microscale simulation of particle deposition in porous media. J Colloid Interface Sci 2014, 417, 227-37

Predicting short-term mortality and long-term survival for hospitalized US patients with alcoholic hepatitis.

PubMed

Cuthbert, Jennifer A; Arslanlar, Sami; Yepuri, Jay; Montrose, Marc; Ahn, Chul W; Shah, Jessica P

2014-07-01

No study has evaluated current scoring systems for their accuracy in predicting short and long-term outcome of alcoholic hepatitis in a US population. We reviewed electronic records for patients with alcoholic liver disease (ALD) admitted to Parkland Memorial Hospital between January 2002 and August 2005. Data and outcomes for 148 of 1,761 admissions meeting pre-defined criteria were collected. The discriminant function (DF) was revised (INRdf) to account for changes in prothrombin time reagents that could potentially affect identification of risk using the previous DF threshold of >32. Admission and theoretical peak scores were calculated by use of the Model for End-stage Liver Disease (MELD). Analysis models compared five different scoring systems. INRdf was closely correlated with the old DF (r (2) = 0.95). Multivariate analysis of the data showed that survival for 28 days was significantly associated with a scoring system using a combination of age, bilirubin, coagulation status, and creatinine (p < 0.001), and an elevated ammonia result within two days of admission (p = 0.012). When peak values for MELD were included, they were the most significant predictor of short-term mortality (p < 0.001), followed by INRdf (p = 0.006). On admission, two scoring systems that identify a subset of patients with severe alcoholic liver disease are able to predict >50 % mortality at four weeks and >80 % mortality at six months without specific treatment.

The Quality of Preterm Infants' Spontaneous Movements: An Early Indicator of Intelligence and Behaviour at School Age

ERIC Educational Resources Information Center

Butcher, Phillipa R.; van Braeckel, Koen; Bouma, Anke; Einspieler, Christa; Stremmelaar, Elisabeth F.; Bos, Arend F.

2009-01-01

Background: The quality of very preterm infants' spontaneous movements at 11 to 16 weeks post-term age is a powerful predictor of their later neurological status. This study investigated whether early spontaneous movements also have predictive value for the intellectual and behavioural problems that children born very preterm often experience.…

Observations on the predictive value of short-term stake tests

Treesearch

Stan Lebow; Bessie Woodward; Patricia Lebow

2008-01-01

This paper compares average ratings of test stakes after 3, 4, 5, and 7 years exposure to their subsequent ratings after 11 years. Average ratings from over 200 treatment groups exposed in plots in southern Mississippi were compared to average ratings of a reference preservative. The analysis revealed that even perfect ratings after three years were not a reliable...

Confidence intervals for predicting lumber strength properties based on ratios of percentiles from two Weibull populations.

Treesearch

Richard A. Johnson; James W. Evans; David W. Green

2003-01-01

Ratios of strength properties of lumber are commonly used to calculate property values for standards. Although originally proposed in terms of means, ratios are being applied without regard to position in the distribution. It is now known that lumber strength properties are generally not normally distributed. Therefore, nonparametric methods are often used to derive...

Longitudinal Trajectories of Gestural and Linguistic Abilities in Very Preterm Infants in the Second Year of Life

ERIC Educational Resources Information Center

Sansavini, Alessandra; Guarini, Annalisa; Savini, Silvia; Broccoli, Serena; Justice, Laura; Alessandroni, Rosina; Faldella, Giacomo

2011-01-01

The present study involved a systematic longitudinal analysis, with three points of assessment in the second year of life, of gestures/actions, word comprehension, and word production in a sample of very preterm infants compared to a sample of full-term infants. The relationships among these competencies as well as their predictive value on…

Ammonia-hydrogen bromide and ammonia-hydrogen iodide complexes: anion photoelectron and ab initio studies.

PubMed

Eustis, S N; Whiteside, A; Wang, D; Gutowski, M; Bowen, K H

2010-01-28

The ammonia-hydrogen bromide and ammonia-hydrogen iodide, anionic heterodimers were studied by anion photoelectron spectroscopy. In complementary studies, these anions and their neutral counterparts were also investigated via ab initio theory at the coupled cluster level. In both systems, neutral NH(3)...HX dimers were predicted to be linear, hydrogen-bonded complexes, whereas their anionic dimers were found to be proton-transferred species of the form, (NH(4)(+)X(-))(-). Both experimentally measured and theoretically predicted vertical detachment energies (VDE) are in excellent agreement for both systems, with values for (NH(4)(+)Br(-))(-) being 0.65 and 0.67 eV, respectively, and values for (NH(4)(+)I(-))(-) being 0.77 and 0.81 eV, respectively. These systems are discussed in terms of our previous study of (NH(4)(+)Cl(-))(-).

How the flow affects the phase behaviour and microstructure of polymer nanocomposites.

PubMed

Stephanou, Pavlos S

2015-02-14

We address the issue of flow effects on the phase behaviour of polymer nanocomposite melts by making use of a recently reported Hamiltonian set of evolution equations developed on principles of non-equilibrium thermodynamics. To this end, we calculate the spinodal curve, by computing values for the nanoparticle radius as a function of the polymer radius-of-gyration for which the second derivative of the generalized free energy of the system becomes zero. Under equilibrium conditions, we recover the phase diagram predicted by Mackay et al. [Science 311, 1740 (2006)]. Under non-equilibrium conditions, we account for the extra terms in the free energy due to changes in the conformations of polymer chains by the shear flow. Overall, our model predicts that flow enhances miscibility, since the corresponding miscibility window opens up for non-zero shear rate values.

Bullying and cyberbullying: overlapping and predictive value of the co-occurrence.

PubMed

del Rey, Rosario; Elipe, Paz; Ortega-Ruiz, Rosario

2012-11-01

Several studies show certain co-occurrence of the traditional bullying and the cyberbullying. However, the results about relation and homogeneity among the roles of each of them are not unanimous. The present study intends to advance in the knowledge about the above-mentioned co-occurrence by exploring the dimensions of victimization and traditional aggression and cyber-victimization and cyber-aggression and by identifying its eventual directionality. A short-term longitudinal design was developed. The sample was formed by 274 adolescents, aging 12 to 18 years-old, belonging to 2 schools of Andalusia (South of Spain). In order to value the impact of bullying and cyberbullying the European Cyberbullying Intervention Project Questionnaire (ECIPQ) and the European Bullying Intervention Project Questionnaire (EBIPQ) were used. The results show important simultaneity among both phenomena and suggest that although in cyberbullying -cyber-victimization and cyber-aggression- may be predicted because of previous involvement of the subject in traditional bullying, on the contrary it does not happen. In addition, previous victimization is a risk factor for traditional bullying and for cyberbullying. Results are discussed in relation to the process and socio-group dynamics arising from the bullying and cyberbullying phenomena, and in terms of their prevention.

Development of a near-infrared spectroscopic system for monitoring urine glucose level for the use of long-term home healthcare

NASA Astrophysics Data System (ADS)

Tanaka, Shinobu; Hayakawa, Yuuto; Ogawa, Mitsuhiro; Yamakoshi, Ken-ichi

2010-08-01

We have been developing a new technique for measuring urine glucose concentration using near infrared spectroscopy (NIRS) in conjunction with the Partial Least Square (PLS) method. In the previous study, we reported some results of preliminary experiments for assessing feasibility of this method using a FT-IR spectrometer. In this study, considering practicability of the system, a flow-through cell with the optical path length of 10 mm was newly introduced. Accuracy of the system was verified by the preliminary experiments using urine samples. From the results obtained, it was clearly demonstrated that the present method had a capability of predicting individual urine glucose level with reasonable accuracy (the minimum value of standard error of prediction: SEP = 22.3 mg/dl) and appeared to be a useful means for long-term home health care. However, mean value of SEP obtained by the urine samples from ten subjects was not satisfactorily low (53.7 mg/dl). For improving the accuracy, (1) mechanical stability of the optical system should be improved, (2) the method for normalizing the spectrum should be reconsidered, and (3) the number of subject should be increased.

The reliability of fine-needle aspiration biopsy in terms of malignancy in patients with Hashimoto thyroiditis.

PubMed

Kapan, Murat; Onder, Akin; Girgin, Sadullah; Ulger, Burak Veli; Firat, Ugur; Uslukaya, Omer; Oguz, Abdullah

2015-02-01

The aim of this study was to analyze the presence of malignancy in patients with Hashimoto's thyroiditis and to investigate the reliability of preoperative fine-needle aspiration biopsy (FNAB). The retrospective study included 44 patients who were operated on for nodular goiter between December 2010 and October 2011. The patients underwent thyroidectomy following a cytologic analysis plus FNAB. Hashimoto's thyroiditis was confirmed on histopathology in all patients. FNAB results were defined as benign in 14 (31.8%), suspicion for malignancy in 17 (38.6%), malignant in 9 (20.5%), and inadequate in 4 (9.1%). Following the thyroidectomy, presence of papillary thyroid carcinoma and follicular variant of papillary thyroid carcinoma were detected in 10 patients (22.7%) and 1 (2.3%) patient, respectively. The FNAB results were interpreted in terms of malignancy, which revealed the sensitivity as 80%; specificity, 40%; false positives, 69.2%; false negatives, 14.3%; positive predictive value, 31.8%; negative predictive value, 85.7%; and diagnostic accuracy, 50%. The coexistence of Hashimoto's thyroiditis with papillary thyroid carcinoma is quite common. The FNAB results for such cases are hard to evaluate, and they are likely to increase the number of false positives.

Aberrant GSTP1 promoter methylation predicts short-term prognosis in acute-on-chronic hepatitis B liver failure.

PubMed

Gao, S; Sun, F-K; Fan, Y-C; Shi, C-H; Zhang, Z-H; Wang, L-Y; Wang, K

2015-08-01

Glutathione-S-transferase P1 (GSTP1) methylation has been demonstrated to be associated with oxidative stress induced liver damage in acute-on-chronic hepatitis B liver failure (ACHBLF). To evaluate the methylation level of GSTP1 promoter in acute-on-chronic hepatitis B liver failure and determine its predictive value for prognosis. One hundred and five patients with acute-on-chronic hepatitis B liver failure, 86 with chronic hepatitis B (CHB) and 30 healthy controls (HC) were retrospectively enrolled. GSTP1 methylation level in peripheral mononuclear cells (PBMC) was detected by MethyLight. Clinical and laboratory parameters were obtained. GSTP1 methylation levels were significantly higher in patients with acute-on-chronic hepatitis B liver failure (median 16.84%, interquartile range 1.83-59.05%) than those with CHB (median 1.25%, interquartile range 0.48-2.47%; P < 0.01) and HC (median 0.80%, interquartile range 0.67-1.27%; P < 0.01). In acute-on-chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P < 0.05) than survivors. GSTP1 methylation level was significantly correlated with total bilirubin (r = 0.29, P < 0.01), prothrombin time activity (r = -0.24, P = 0.01) and model for end-stage liver disease (MELD) score (r = 0.26, P = 0.01). When used to predict 1- or 2-month mortality of acute-on-chronic hepatitis B liver failure, GSTP1 methylation showed significantly better predictive value than MELD score [area under the receiver operating characteristic curve (AUC) 0.89 vs. 0.72, P < 0.01; AUC 0.83 vs. 0.70, P < 0.05 respectively]. Meanwhile, patients with GSTP1 methylation levels above the cut-off points showed significantly poorer survival than those below (P < 0.05). Aberrant GSTP1 promoter methylation exists in acute-on-chronic hepatitis B liver failure and shows high predictive value for short-term mortality. It might serve as a potential prognostic marker for acute-on-chronic hepatitis B liver failure. © 2015 John Wiley & Sons Ltd.

An evaluation of computer-aided disproportionality analysis for post-marketing signal detection.

PubMed

Lehman, H P; Chen, J; Gould, A L; Kassekert, R; Beninger, P R; Carney, R; Goldberg, M; Goss, M A; Kidos, K; Sharrar, R G; Shields, K; Sweet, A; Wiholm, B E; Honig, P K

2007-08-01

To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.

Higher integrity of the motor and visual pathways in long-term video game players.

PubMed

Zhang, Yang; Du, Guijin; Yang, Yongxin; Qin, Wen; Li, Xiaodong; Zhang, Quan

2015-01-01

Long term video game players (VGPs) exhibit superior visual and motor skills compared with non-video game control subjects (NVGCs). However, the neural basis underlying the enhanced behavioral performance remains largely unknown. To clarify this issue, the present study compared the whiter matter integrity within the corticospinal tracts (CST), the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF) between the VGPs and the NVGCs using diffusion tensor imaging. Compared with the NVGCs, voxel-wise comparisons revealed significantly higher fractional anisotropy (FA) values in some regions within the left CST, left SLF, bilateral ILF, and IFOF in VGPs. Furthermore, higher FA values in the left CST at the level of cerebral peduncle predicted a faster response in visual attention tasks. These results suggest that higher white matter integrity in the motor and higher-tier visual pathways is associated with long-term video game playing, which may contribute to the understanding on how video game play influences motor and visual performance.

Higher integrity of the motor and visual pathways in long-term video game players

PubMed Central

Du, Guijin; Yang, Yongxin; Qin, Wen; Li, Xiaodong; Zhang, Quan

2015-01-01

Long term video game players (VGPs) exhibit superior visual and motor skills compared with non-video game control subjects (NVGCs). However, the neural basis underlying the enhanced behavioral performance remains largely unknown. To clarify this issue, the present study compared the whiter matter integrity within the corticospinal tracts (CST), the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF) between the VGPs and the NVGCs using diffusion tensor imaging. Compared with the NVGCs, voxel-wise comparisons revealed significantly higher fractional anisotropy (FA) values in some regions within the left CST, left SLF, bilateral ILF, and IFOF in VGPs. Furthermore, higher FA values in the left CST at the level of cerebral peduncle predicted a faster response in visual attention tasks. These results suggest that higher white matter integrity in the motor and higher-tier visual pathways is associated with long-term video game playing, which may contribute to the understanding on how video game play influences motor and visual performance. PMID:25805981

Linear solvation energy relationships (LSER) for adsorption of organic compounds by carbon nanotubes.

PubMed

Ersan, Gamze; Apul, Onur G; Karanfil, Tanju

2016-07-01

The objective of this paper was to create a comprehensive database for the adsorption of organic compounds by carbon nanotubes (CNTs) and to use the Linear Solvation Energy Relationship (LSER) technique for developing predictive adsorption models of organic compounds (OCs) by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Adsorption data for 123 OCs by MWCNTs and 48 OCs by SWCNTs were compiled from the literature, including some experimental results obtained in our laboratory. The roles of selected OCs properties and CNT types were examined with LSER models. The results showed that the r(2) values of the LSER models displayed small variability for aromatic compounds smaller than 220 g/mol, after which a decreasing trend was observed. The data available for aliphatics was mainly for molecular weights smaller than 250 g/mol, which showed a similar trend to that of aromatics. The r(2) values for the LSER model on the adsorption of aromatic and aliphatic OCs by SWCNTs and MWCNTs were relatively similar indicating the linearity of LSER models did not depend on the CNT types. Among all LSER model descriptors, V term (molecular volume) for aromatic OCs and B term (basicity) for aliphatic OCs were the most predominant descriptors on both type of CNTs. The presence of R term (excess molar refractivity) in LSER model equations resulted in decreases for both V and P (polarizability) parameters without affecting the r(2) values. Overall, the results demonstrate that successful predictive models can be developed for the adsorption of OCs by MWCNTs and SWCNTs with LSER techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Punishment in public goods games leads to meta-stable phase transitions and hysteresis

NASA Astrophysics Data System (ADS)

Hintze, Arend; Adami, Christoph

2015-07-01

The evolution of cooperation has been a perennial problem in evolutionary biology because cooperation can be undermined by selfish cheaters who gain an advantage in the short run, while compromising the long-term viability of the population. Evolutionary game theory has shown that under certain conditions, cooperation nonetheless evolves stably, for example if players have the opportunity to punish cheaters that benefit from a public good yet refuse to pay into the common pool. However, punishment has remained enigmatic because it is costly and difficult to maintain. On the other hand, cooperation emerges naturally in the public goods game if the synergy of the public good (the factor multiplying the public good investment) is sufficiently high. In terms of this synergy parameter, the transition from defection to cooperation can be viewed as a phase transition with the synergy as the critical parameter. We show here that punishment reduces the critical value at which cooperation occurs, but also creates the possibility of meta-stable phase transitions, where populations can ‘tunnel’ into the cooperating phase below the critical value. At the same time, cooperating populations are unstable even above the critical value, because a group of defectors that are large enough can ‘nucleate’ such a transition. We study the mean-field theoretical predictions via agent-based simulations of finite populations using an evolutionary approach where the decisions to cooperate or to punish are encoded genetically in terms of evolvable probabilities. We recover the theoretical predictions and demonstrate that the population shows hysteresis, as expected in systems that exhibit super-heating and super-cooling. We conclude that punishment can stabilize populations of cooperators below the critical point, but it is a two-edged sword: it can also stabilize defectors above the critical point.

Chesapeake Bay Forecast System: Oxygen Prediction for the Sustainable Ecosystem Management

NASA Astrophysics Data System (ADS)

Mathukumalli, B.; Long, W.; Zhang, X.; Wood, R.; Murtugudde, R. G.

2010-12-01

The Chesapeake Bay Forecast System (CBFS) is a flexible, end-to-end expert prediction tool for decision makers that will provide customizable, user-specified predictions and projections of the region’s climate, air and water quality, local chemistry, and ecosystems at days to decades. As a part of CBFS, the long-term water quality data were collected and assembled to develop ecological models for the sustainable management of the Chesapeake Bay. Cultural eutrophication depletes oxygen levels in this ecosystem particularly in summer which has several negative implications on the structure and function of ecosystem. In order to understand dynamics and prediction of spatially-explicit oxygen levels in the Bay, an empirical process based ecological model is developed with long-term control variables (water temperature, salinity, nitrogen and phosphorus). Statistical validation methods were employed to demonstrate usability of predictions for management purposes and the predicted oxygen levels are quite faithful to observations. The predicted oxygen values and other physical outputs from downscaling of regional weather and climate predictions, or forecasts from hydrodynamic models can be used to forecast various ecological components. Such forecasts would be useful for both recreational and commercial users of the bay (for example, bass fishing). Furthermore, this work can also be used to predict extent of hypoxia/anoxia not only from anthropogenic nutrient pollution, but also from global warming. Some hindcasts and forecasts are discussed along with the ongoing efforts at a mechanistic ecosystem model to provide prognostic oxygen predictions and projections and upper trophic modeling using an energetics approach.

Tumor Metabolism and Perfusion in Head and Neck Squamous Cell Carcinoma: Pretreatment Multimodality Imaging With {sup 1}H Magnetic Resonance Spectroscopy, Dynamic Contrast-Enhanced MRI, and [{sup 18}F]FDG-PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jansen, Jacobus F.A.; Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, New York; Department of Radiology, Maastricht University Medical Center, Maastricht

2012-01-01

Purpose: To correlate proton magnetic resonance spectroscopy ({sup 1}H-MRS), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and {sup 18}F-labeled fluorodeoxyglucose positron emission tomography ([{sup 18}F]FDG PET) of nodal metastases in patients with head and neck squamous cell carcinoma (HNSCC) for assessment of tumor biology. Additionally, pretreatment multimodality imaging was evaluated for its efficacy in predicting short-term response to treatment. Methods and Materials: Metastatic neck nodes were imaged with {sup 1}H-MRS, DCE-MRI, and [{sup 18}F]FDG PET in 16 patients with newly diagnosed HNSCC, before treatment. Short-term patient radiological response was evaluated at 3 to 4 months. Correlations among {sup 1}H-MRS (choline concentrationmore » relative to water [Cho/W]), DCE-MRI (volume transfer constant [K{sup trans}]; volume fraction of the extravascular extracellular space [v{sub e}]; and redistribution rate constant [k{sub ep}]), and [{sup 18}F]FDG PET (standard uptake value [SUV] and total lesion glycolysis [TLG]) were calculated using nonparametric Spearman rank correlation. To predict short-term responses, logistic regression analysis was performed. Results: A significant positive correlation was found between Cho/W and TLG ({rho} = 0.599; p = 0.031). Cho/W correlated negatively with heterogeneity measures of standard deviation std(v{sub e}) ({rho} = -0.691; p = 0.004) and std(k{sub ep}) ({rho} = -0.704; p = 0.003). Maximum SUV (SUVmax) values correlated strongly with MRI tumor volume ({rho} = 0.643; p = 0.007). Logistic regression indicated that std(K{sup trans}) and SUVmean were significant predictors of short-term response (p < 0.07). Conclusion: Pretreatment multimodality imaging using {sup 1}H-MRS, DCE-MRI, and [{sup 18}F]FDG PET is feasible in HNSCC patients with nodal metastases. Additionally, combined DCE-MRI and [{sup 18}F]FDG PET parameters were predictive of short-term response to treatment.« less

Travel-related schistosomiasis, strongyloidiasis, filariasis, and toxocariasis: the risk of infection and the diagnostic relevance of blood eosinophilia.

PubMed

Baaten, Gijs G; Sonder, Gerard J; van Gool, Tom; Kint, Joan A; van den Hoek, Anneke

2011-04-05

This study prospectively assessed the occurrence of clinical and subclinical schistosomiasis, strongyloidiasis, filariasis, and toxocariasis, and the screening value of eosinophilia in adult short-term travelers to helminth-endemic countries. Visitors of a pre-travel health advice centre donated blood samples for serology and blood cell count before and after travel. Samples were tested for eosinophilia, and for antibodies against schistosomiasis, strongyloidiasis, filariasis, and toxocariasis. Previous infection was defined as seropositivity in pre- and post-travel samples. Recent infection was defined as a seroconversion. Symptoms of parasitic disease were recorded in a structured diary. Previous infection was found in 112 of 1207 subjects: schistosomiasis in 2.7%, strongyloidiasis in 2.4%, filariasis in 3.4%, and toxocariasis in 1.8%. Recent schistosomiasis was found in 0.51% of susceptible subjects at risk, strongyloidiasis in 0.25%, filariasis in 0.09%, and toxocariasis in 0.08%. The incidence rate per 1000 person-months was 6.4, 3.2, 1.1, and 1.1, respectively. Recent infections were largely contracted in Asia. The positive predictive value of eosinophilia for diagnosis was 15% for previous infection and 0% for recent infection. None of the symptoms studied had any positive predictive value. The chance of infection with schistosomiasis, strongyloidiasis, filariasis, and toxocariasis during one short-term journey to an endemic area is low. However, previous stay leads to a cumulative risk of infection. Testing for eosinophilia appeared to be of no value in routine screening of asymptomatic travelers for the four helminthic infections. Findings need to be replicated in larger prospective studies.

Stable Water Use Efficiency of Tibetan Alpine Meadows in Past Half Century: Evidence from Wool δ13C Values

PubMed Central

Yang, Hao; He, Nianpeng; He, Yongtao; Li, Shenggong; Shi, Peili; Zhang, Xianzhou

2015-01-01

Understanding the influences of climatic changes on water use efficiency (WUE) of Tibetan alpine meadows is important for predicting their long-term net primary productivity (NPP) because they are considered very sensitive to climate change. Here, we collected wool materials produced from 1962 to 2010 and investigated the long-term WUE of an alpine meadow in Tibet on basis of the carbon isotope values of vegetation (δ 13Cveg). The values of δ 13Cveg decreased by 1.34‰ during 1962–2010, similar to changes in δ 13C values of atmospheric CO2. Carbon isotope discrimination was highly variable and no trend was apparent in the past half century. Intrinsic water use efficiency (W i) increased by 18 μmol·mol–1 (approximately 23.5%) during 1962–2010 because the increase in the intercellular CO2 concentration (46 μmol·mol–1) was less than that in the atmospheric CO2 concentration (C a, 73 μmol·mol–1). In addition, W i increased significantly with increasing growing season temperature and C a. However, effective water use efficiency (W e) remained relatively stable, because of increasing vapor pressure deficit. C a, precipitation, and growing season temperature collectively explained 45% of the variation of W e. Our findings indicate that the W e of alpine meadows in the Tibetan Plateau remained relatively stable by physiological adjustment to elevated C a and growing season temperature. These findings improve our understanding and the capacity to predict NPP of these ecosystems under global change scenarios. PMID:26660306

Symbolic Numerical Distance Effect Does Not Reflect the Difference between Numbers.

PubMed

Krajcsi, Attila; Kojouharova, Petia

2017-01-01

In a comparison task, the larger the distance between the two numbers to be compared, the better the performance-a phenomenon termed as the numerical distance effect. According to the dominant explanation, the distance effect is rooted in a noisy representation, and performance is proportional to the size of the overlap between the noisy representations of the two values. According to alternative explanations, the distance effect may be rooted in the association between the numbers and the small-large categories, and performance is better when the numbers show relatively high differences in their strength of association with the small-large properties. In everyday number use, the value of the numbers and the association between the numbers and the small-large categories strongly correlate; thus, the two explanations have the same predictions for the distance effect. To dissociate the two potential sources of the distance effect, in the present study, participants learned new artificial number digits only for the values between 1 and 3, and between 7 and 9, thus, leaving out the numbers between 4 and 6. It was found that the omitted number range (the distance between 3 and 7) was considered in the distance effect as 1, and not as 4, suggesting that the distance effect does not follow the values of the numbers predicted by the dominant explanation, but it follows the small-large property association predicted by the alternative explanations.

Comparison of ground motions from hybrid simulations to nga prediction equations

USGS Publications Warehouse

Star, L.M.; Stewart, J.P.; Graves, R.W.

2011-01-01

We compare simulated motions for a Mw 7.8 rupture scenario on the San Andreas Fault known as the ShakeOut event, two permutations with different hypocenter locations, and a Mw 7.15 Puente Hills blind thrust scenario, to median and dispersion predictions from empirical NGA ground motion prediction equations. We find the simulated motions attenuate faster with distance than is predicted by the NGA models for periods less than about 5.0 s After removing this distance attenuation bias, the average residuals of the simulated events (i.e., event terms) are generally within the scatter of empirical event terms, although the ShakeOut simulation appears to be a high static stress drop event. The intraevent dispersion in the simulations is lower than NGA values at short periods and abruptly increases at 1.0 s due to different simulation procedures at short and long periods. The simulated motions have a depth-dependent basin response similar to the NGA models, and also show complex effects in which stronger basin response occurs when the fault rupture transmits energy into a basin at low angle, which is not predicted by the NGA models. Rupture directivity effects are found to scale with the isochrone parameter ?? 2011, Earthquake Engineering Research Institute.

Within-and among-year germination in Sonoran Desert winter annuals: bet hedging and predictive germination in a variable environment.

PubMed

Gremer, Jennifer R; Kimball, Sarah; Venable, D Lawrence

2016-10-01

In variable environments, organisms must have strategies to ensure fitness as conditions change. For plants, germination can time emergence with favourable conditions for later growth and reproduction (predictive germination), spread the risk of unfavourable conditions (bet hedging) or both (integrated strategies). Here we explored the adaptive value of within- and among-year germination timing for 12 species of Sonoran Desert winter annual plants. We parameterised models with long-term demographic data to predict optimal germination fractions and compared them to observed germination. At both temporal scales we found that bet hedging is beneficial and that predicted optimal strategies corresponded well with observed germination. We also found substantial fitness benefits to varying germination timing, suggesting some degree of predictive germination in nature. However, predictive germination was imperfect, calling for some degree of bet hedging. Together, our results suggest that desert winter annuals have integrated strategies combining both predictive plasticity and bet hedging. © 2016 John Wiley & Sons Ltd/CNRS.

Genome sequence analysis of predicted polyprenol reductase gene from mangrove plant kandelia obovata

NASA Astrophysics Data System (ADS)

Basyuni, M.; Sagami, H.; Baba, S.; Oku, H.

2018-03-01

It has been previously reported that dolichols but not polyprenols were predominated in mangrove leaves and roots. Therefore, the occurrence of larger amounts of dolichol in leaves of mangrove plants implies that polyprenol reductase is responsible for the conversion of polyprenol to dolichol may be active in mangrove leaves. Here we report the early assessment of probably polyprenol reductase gene from genome sequence of mangrove plant Kandelia obovata. The functional assignment of the gene was based on a homology search of the sequences against the non-redundant (nr) peptide database of NCBI using Blastx. The degree of sequence identity between DNA sequence and known polyprenol reductase was confirmed using the Blastx probability E-value, total score, and identity. The genome sequence data resulted in three partial sequences, termed c23157 (700 bp), c23901 (960 bp), and c24171 (531 bp). The c23157 gene showed the highest similarity (61%) to predicted polyprenol reductase 2- like from Gossypium raimondii with E-value 2e-100. The second gene was c23901 to exhibit high similarity (78%) to the steroid 5-alpha-reductase Det2 from J. curcas with E-value 2e-140. Furthermore, the c24171 gene depicted highest similarity (79%) to the polyprenol reductase 2 isoform X1 from Jatropha curcas with E- value 7e-21.The present study suggested that the c23157, c23901, and c24171, genes may encode predicted polyprenol reductase. The c23157, c23901, c24171 are therefore the new type of predicted polyprenol reductase from K. obovata.

Added prognostic value of ischaemic threshold in radionuclide myocardial perfusion imaging: a common-sense integration of exercise tolerance and ischaemia severity.

PubMed

Marini, Cecilia; Acampa, Wanda; Bauckneht, Matteo; Daniele, Stefania; Capitanio, Selene; Cantoni, Valeria; Fiz, Francesco; Zampella, Emilia; Dib, Bassam; Assante, Roberta; Bruzzi, Paolo; Sambuceti, Gianmario; Cuocolo, Alberto

2015-04-01

Reversible ischaemia at radionuclide myocardial perfusion imaging (MPI) accurately predicts risk of cardiac death and nonfatal myocardial infarction (major adverse cardiac events, MACE). This prognostic penetrance might be empowered by accounting for exercise tolerance as an indirect index of ischaemia severity. The present study aimed to verify this hypothesis integrating imaging assessment of ischaemia severity with exercise maximal rate pressure product (RPP) in a large cohort of patients with suspected or known coronary artery disease (CAD). We analysed 1,502 consecutive patients (1,014 men aged 59 ± 10 years) submitted to exercise stress/rest MPI. To account for exercise tolerance, the summed difference score (SDS) was divided by RPP at tracer injection providing a clinical prognostic index (CPI). Reversible ischaemia was documented in 357 patients (24 %) and was classified by SDS as mild (SDS 2-4) in 180, moderate (SDS 5-7) in 118 and severe (SDS >7) in 59. CPI values of ischaemic patients were clustered into tertiles with lowest and highest values indicating low and high risk, respectively. CPI modified SDS risk prediction in 119/357 (33 %) patients. During a 60-month follow-up, MACE occurred in 68 patients. Kaplan-Meier analysis revealed that CPI significantly improved predictive power for MACE incidence with respect to SDS alone. Multivariate Cox analysis confirmed the additive independent value of CPI-derived information. Integration of ischaemic threshold and ischaemia extension and severity can improve accuracy of exercise MPI in predicting long-term outcome in a large cohort of patients with suspected or known CAD.

Validation of the Hospital Anxiety and Depression Scale in patients with epilepsy.

PubMed

Wiglusz, Mariusz S; Landowski, Jerzy; Michalak, Lidia; Cubała, Wiesław J

2016-05-01

Despite the fact that depressive disorders are the most common comorbidities among patients with epilepsy (PWEs), they often go unrecognized and untreated. The availability of validated screening instruments to detect depression in PWEs is limited. The aim of the present study was to validate the Hospital Anxiety and Depression Scale (HADS) in adult PWEs. A consecutive group of 118 outpatient PWEs was invited to participate in the study. Ninety-six patients met inclusion criteria, completed HADS, and were examined by a trained psychiatrist using Structured Clinical Interview (SCID-I) for DSM-IV-TR. Receiver operating characteristic (ROC) curves were used to determine the optimal threshold scores for the HADS depression subscale (HADS-D). Receiver operating characteristic analyses showed areas under the curve at approximately 84%. For diagnoses of MDD, the HADS-D demonstrated the best psychometric properties for a cutoff score ≥7 with sensitivity of 90.5%, specificity of 70.7%, positive predictive value of 46.3%, and negative predictive value of 96.4%. In the case of the group with 'any depressive disorder', the HADS-D optimum cutoff score was ≥6 with sensitivity of 82.5%, specificity of 73.2%, positive predictive value of 68.8%, and negative predictive value of 85.4%. The HADS-D proved to be a valid and reliable psychometric instrument in terms of screening for depressive disorders in PWEs. In the epilepsy setting, HADS-D maintains adequate sensitivity, acceptable specificity, and high NPV but low PPV for diagnosing MDD with an optimum cutoff score ≥7. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimation of Handling Qualities Parameters of the Tu-144 Supersonic Transport Aircraft from Flight Test Data

NASA Technical Reports Server (NTRS)

Curry, Timothy J.; Batterson, James G. (Technical Monitor)

2000-01-01

Low order equivalent system (LOES) models for the Tu-144 supersonic transport aircraft were identified from flight test data. The mathematical models were given in terms of transfer functions with a time delay by the military standard MIL-STD-1797A, "Flying Qualities of Piloted Aircraft," and the handling qualities were predicted from the estimated transfer function coefficients. The coefficients and the time delay in the transfer functions were estimated using a nonlinear equation error formulation in the frequency domain. Flight test data from pitch, roll, and yaw frequency sweeps at various flight conditions were used for parameter estimation. Flight test results are presented in terms of the estimated parameter values, their standard errors, and output fits in the time domain. Data from doublet maneuvers at the same flight conditions were used to assess the predictive capabilities of the identified models. The identified transfer function models fit the measured data well and demonstrated good prediction capabilities. The Tu-144 was predicted to be between level 2 and 3 for all longitudinal maneuvers and level I for all lateral maneuvers. High estimates of the equivalent time delay in the transfer function model caused the poor longitudinal rating.

An Improved Method of Predicting Extinction Coefficients for the Determination of Protein Concentration.

PubMed

Hilario, Eric C; Stern, Alan; Wang, Charlie H; Vargas, Yenny W; Morgan, Charles J; Swartz, Trevor E; Patapoff, Thomas W

2017-01-01

Concentration determination is an important method of protein characterization required in the development of protein therapeutics. There are many known methods for determining the concentration of a protein solution, but the easiest to implement in a manufacturing setting is absorption spectroscopy in the ultraviolet region. For typical proteins composed of the standard amino acids, absorption at wavelengths near 280 nm is due to the three amino acid chromophores tryptophan, tyrosine, and phenylalanine in addition to a contribution from disulfide bonds. According to the Beer-Lambert law, absorbance is proportional to concentration and path length, with the proportionality constant being the extinction coefficient. Typically the extinction coefficient of proteins is experimentally determined by measuring a solution absorbance then experimentally determining the concentration, a measurement with some inherent variability depending on the method used. In this study, extinction coefficients were calculated based on the measured absorbance of model compounds of the four amino acid chromophores. These calculated values for an unfolded protein were then compared with an experimental concentration determination based on enzymatic digestion of proteins. The experimentally determined extinction coefficient for the native proteins was consistently found to be 1.05 times the calculated value for the unfolded proteins for a wide range of proteins with good accuracy and precision under well-controlled experimental conditions. The value of 1.05 times the calculated value was termed the predicted extinction coefficient. Statistical analysis shows that the differences between predicted and experimentally determined coefficients are scattered randomly, indicating no systematic bias between the values among the proteins measured. The predicted extinction coefficient was found to be accurate and not subject to the inherent variability of experimental methods. We propose the use of a predicted extinction coefficient for determining the protein concentration of therapeutic proteins starting from early development through the lifecycle of the product. LAY ABSTRACT: Knowing the concentration of a protein in a pharmaceutical solution is important to the drug's development and posology. There are many ways to determine the concentration, but the easiest one to use in a testing lab employs absorption spectroscopy. Absorbance of ultraviolet light by a protein solution is proportional to its concentration and path length; the proportionality constant is the extinction coefficient. The extinction coefficient of a protein therapeutic is usually determined experimentally during early product development and has some inherent method variability. In this study, extinction coefficients of several proteins were calculated based on the measured absorbance of model compounds. These calculated values for an unfolded protein were then compared with experimental concentration determinations based on enzymatic digestion of the proteins. The experimentally determined extinction coefficient for the native protein was 1.05 times the calculated value for the unfolded protein with good accuracy and precision under controlled experimental conditions, so the value of 1.05 times the calculated coefficient was called the predicted extinction coefficient. Comparison of predicted and measured extinction coefficients indicated that the predicted value was very close to the experimentally determined values for the proteins. The predicted extinction coefficient was accurate and removed the variability inherent in experimental methods. © PDA, Inc. 2017.

Velocity and bottom-stress measurements in the bottom boundary layer, outer Norton Sound, Alaska.

USGS Publications Warehouse

Cacchione, D.A.; Drake, D.E.; Wiberg, P.

1982-01-01

We have used long-term measurements of near-bottom velocities at four heights above the sea floor in Norton Sound, Alaska, to compute hourly values of shear velocity u., roughness and bottom-drag coefficient. Maximum sediment resuspension and transport, predicted for periods when the computed value of u. exceeds a critical level, occur during peak tidal currents associated with spring tides. The fortnightly variation in u. is correlated with a distinct nepheloid layer that intensifies and thickens during spring tides and diminishes and thins during neap tides. The passage of a storm near the end of the experiment caused significantly higher u. values than those found during fair weather.-from Authros

Predictive Performance of Echocardiographic Parameters for Cardiovascular Events Among Elderly Treated Hypertensive Patients.

PubMed

Chowdhury, Enayet K; Jennings, Garry L R; Dewar, Elizabeth; Wing, Lindon M H; Reid, Christopher M

2016-07-01

Hypertension leads to cardiac structural and functional changes, commonly assessed by echocardiography. In this study, we assessed the predictive performance of different echocardiographic parameters including left ventricular hypertrophy (LVH) on future cardiovascular outcomes in elderly hypertensive patients without heart failure. Data from LVH substudy of the Second Australian National Blood Pressure trial were used. Echocardiograms were performed at entry into the study. Cardiovascular outcomes were identified over short term (median 4.2 years) and long term (median 10.9 years). LVH was defined using threshold values of LV mass (LVM) indexed to either body surface area (BSA) or height(2.7): >115/95g/m(2) (LVH-BSA(115/95)) or ≥49/45g/m(2.7) (LVH-ht(49/45)) in males/females, respectively, and ≥125g/m(2) (LVH-BSA(125)) or ≥51g/m(2.7) (LVH-ht(51)) for both sexes. In the 666 participants aged ≥65 years in this analysis, LVH prevalence at baseline was 33%-70% depending on definition; and after adjusting for potential risk factors, only LVH-BSA(115/95) predicted both short- and long-term cardiovascular outcomes. Participants having LVH-BSA(115/95) (69%) at baseline had twice the risk of having any first cardiovascular event over the short term (hazard ratio, 95% confidence interval: 2.00, 1.12-3.57, P = 0.02) and any fatal cardiovascular events (2.11, 1.21-3.68, P = 0.01) over the longer term. Among other echocardiographic parameters, LVM and LVM indexed to either BSA or height(2.7) predicted cardiovascular events over both short and longer term. In elderly treated hypertensive patients without heart failure, determining LVH by echocardiography is highly dependent on the methodology adopted. LVH-BSA(115/95) is a reliable predictor of future cardiovascular outcomes in the elderly. © American Journal of Hypertension, Ltd 2016. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Linear regression models for solvent accessibility prediction in proteins.

PubMed

Wagner, Michael; Adamczak, Rafał; Porollo, Aleksey; Meller, Jarosław

2005-04-01

The relative solvent accessibility (RSA) of an amino acid residue in a protein structure is a real number that represents the solvent exposed surface area of this residue in relative terms. The problem of predicting the RSA from the primary amino acid sequence can therefore be cast as a regression problem. Nevertheless, RSA prediction has so far typically been cast as a classification problem. Consequently, various machine learning techniques have been used within the classification framework to predict whether a given amino acid exceeds some (arbitrary) RSA threshold and would thus be predicted to be "exposed," as opposed to "buried." We have recently developed novel methods for RSA prediction using nonlinear regression techniques which provide accurate estimates of the real-valued RSA and outperform classification-based approaches with respect to commonly used two-class projections. However, while their performance seems to provide a significant improvement over previously published approaches, these Neural Network (NN) based methods are computationally expensive to train and involve several thousand parameters. In this work, we develop alternative regression models for RSA prediction which are computationally much less expensive, involve orders-of-magnitude fewer parameters, and are still competitive in terms of prediction quality. In particular, we investigate several regression models for RSA prediction using linear L1-support vector regression (SVR) approaches as well as standard linear least squares (LS) regression. Using rigorously derived validation sets of protein structures and extensive cross-validation analysis, we compare the performance of the SVR with that of LS regression and NN-based methods. In particular, we show that the flexibility of the SVR (as encoded by metaparameters such as the error insensitivity and the error penalization terms) can be very beneficial to optimize the prediction accuracy for buried residues. We conclude that the simple and computationally much more efficient linear SVR performs comparably to nonlinear models and thus can be used in order to facilitate further attempts to design more accurate RSA prediction methods, with applications to fold recognition and de novo protein structure prediction methods.

Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics

PubMed Central

Garrison, Louis P.; Towse, Adrian

2017-01-01

‘Value-based’ outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: “What kinds of pricing and reimbursement models should be applied in personalized healthcare?” The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that—to meet this social objective of optimal innovation in personalized healthcare—payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption. PMID:28869571

Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics.

PubMed

Garrison, Louis P; Towse, Adrian

2017-09-04

'Value-based' outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: "What kinds of pricing and reimbursement models should be applied in personalized healthcare?" The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that-to meet this social objective of optimal innovation in personalized healthcare-payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption.

Theoretical predictions of the changes in the irradiance and color of light beams traveling in sugared water caused by optical rotation phenomena, and their possible applications for educational purposes

NASA Astrophysics Data System (ADS)

Tokumitsu, S.; Hasegawa, M.

2018-05-01

The coloring phenomena caused by optical rotation of polarized light beams in sugared water can be an appropriate subject for use as an educational tool. In this paper, such coloring phenomena are studied in terms of theory, and the results are compared with experimental results. First, polarized laser beams in red, blue, or green were allowed to travel in sugared water of certain concentrations, and changes in the irradiance of the beams were measured while changing the distance between a pair of polarizing plates arranged in the sugared water. The angle of rotation was then determined for each color. An equation was established for predicting a theoretical value of the angle of rotation for laser beams of specific colors (wavelengths) traveling in sugared water of specific concentrations. The predicted results from the equation exhibited satisfactory agreement with the experimental values obtained from the measurements. In addition, changes in the irradiance of traveling laser beams, as well as the changes in colors observable for white light beams, were also predicted, resulting in good agreement with the observed results.

Theoretical prediction of Grüneisen parameter for SiO{sub 2}.TiO{sub 2} bulk metallic glasses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Chandra K.; Pandey, Brijesh K., E-mail: bkpmmmec11@gmail.com; Pandey, Anjani K.

2016-05-23

The Grüneisen parameter (γ) is very important to decide the limitations for the prediction of thermoelastic properties of bulk metallic glasses. It can be defined in terms of microscopic and macroscopic parameters of the material in which former is based on vibrational frequencies of atoms in the material while later is closely related to its thermodynamic properties. Different formulation and equation of states are used by the pioneer researchers of this field to predict the true sense of Gruneisen parameter for BMG but for SiO{sub 2}.TiO{sub 2} very few and insufficient information is available till now. In the present workmore » we have tested the validity of two different isothermal EOS viz. Poirrior-Tarantola EOS and Usual-Tait EOS to predict the true value of Gruneisen parameter for SiO{sub 2}.TiO{sub 2} as a function of compression. Using different thermodynamic limitations related to the material constraints and analyzing obtained result it is concluded that the Poirrior-Tarantola EOS gives better numeric values of Grüneisen parameter (γ) for SiO{sub 2}.TiO{sub 2} BMG.« less

Setting the vision: applied patient-reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness.

PubMed

Wysham, Nicholas G; Abernethy, Amy P; Cox, Christopher E

2014-10-01

Prediction models in critical illness are generally limited to short-term mortality and uncommonly include patient-centered outcomes. Current outcome prediction tools are also insensitive to individual context or evolution in healthcare practice, potentially limiting their value over time. Improved prognostication of patient-centered outcomes in critical illness could enhance decision-making quality in the ICU. Patient-reported outcomes have emerged as precise methodological measures of patient-centered variables and have been successfully employed using diverse platforms and technologies, enhancing the value of research in critical illness survivorship and in direct patient care. The learning health system is an emerging ideal characterized by integration of multiple data sources into a smart and interconnected health information technology infrastructure with the goal of rapidly optimizing patient care. We propose a vision of a smart, interconnected learning health system with integrated electronic patient-reported outcomes to optimize patient-centered care, including critical care outcome prediction. A learning health system infrastructure integrating electronic patient-reported outcomes may aid in the management of critical illness-associated conditions and yield tools to improve prognostication of patient-centered outcomes in critical illness.

Predicting influent biochemical oxygen demand: Balancing energy demand and risk management.

PubMed

Zhu, Jun-Jie; Kang, Lulu; Anderson, Paul R

2018-01-01

Ready access to comprehensive influent information can help water reclamation plant (WRP) operators implement better real-time process controls, provide operational reliability and reduce energy consumption. The five-day biochemical oxygen demand (BOD 5 ), a critical parameter for WRP process control, is expensive and difficult to measure using hard-sensors. An alternative approach based on a soft-sensor methodology shows promise, but can be problematic when used to predict high BOD 5 values. Underestimating high BOD 5 concentrations for process control could result in an insufficient amount of aeration, increasing the risk of an effluent violation. To address this issue, we tested a hierarchical hybrid soft-sensor approach involving multiple linear regression, artificial neural networks (ANN), and compromise programming. While this hybrid approach results in a slight decrease in overall prediction accuracy relative to the approach based on ANN only, the underestimation percentage is substantially lower (37% vs. 61%) for predictions of carbonaceous BOD 5 (CBOD 5 ) concentrations higher than the long-term average value. The hybrid approach is also flexible and can be adjusted depending on the relative importance between energy savings and managing the risk of an effluent violation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor.

PubMed

Pandey, Daya Shankar; Das, Saptarshi; Pan, Indranil; Leahy, James J; Kwapinski, Witold

2016-12-01

In this paper, multi-layer feed forward neural networks are used to predict the lower heating value of gas (LHV), lower heating value of gasification products including tars and entrained char (LHV p ) and syngas yield during gasification of municipal solid waste (MSW) during gasification in a fluidized bed reactor. These artificial neural networks (ANNs) with different architectures are trained using the Levenberg-Marquardt (LM) back-propagation algorithm and a cross validation is also performed to ensure that the results generalise to other unseen datasets. A rigorous study is carried out on optimally choosing the number of hidden layers, number of neurons in the hidden layer and activation function in a network using multiple Monte Carlo runs. Nine input and three output parameters are used to train and test various neural network architectures in both multiple output and single output prediction paradigms using the available experimental datasets. The model selection procedure is carried out to ascertain the best network architecture in terms of predictive accuracy. The simulation results show that the ANN based methodology is a viable alternative which can be used to predict the performance of a fluidized bed gasifier. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

PubMed Central

Denkinger, Claudia M.; Kik, Sandra V.; Rangaka, Molebogeng X.; Zwerling, Alice; Oxlade, Olivia; Metcalfe, John Z.; Cattamanchi, Adithya; Dowdy, David W.; Dheda, Keertan; Banaei, Niaz

2014-01-01

SUMMARY Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis. Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers. PMID:24396134

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

A nonparametric multiple imputation approach for missing categorical data.

PubMed

Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh

2017-06-06

Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.

Prediction of cardiovascular outcome by estimated glomerular filtration rate and estimated creatinine clearance in the high-risk hypertension population of the VALUE trial.

PubMed

Ruilope, Luis M; Zanchetti, Alberto; Julius, Stevo; McInnes, Gordon T; Segura, Julian; Stolt, Pelle; Hua, Tsushung A; Weber, Michael A; Jamerson, Ken

2007-07-01

Reduced renal function is predictive of poor cardiovascular outcomes but the predictive value of different measures of renal function is uncertain. We compared the value of estimated creatinine clearance, using the Cockcroft-Gault formula, with that of estimated glomerular filtration rate (GFR), using the Modification of Diet in Renal Disease (MDRD) formula, as predictors of cardiovascular outcome in 15 245 high-risk hypertensive participants in the Valsartan Antihypertensive Long-term Use Evaluation (VALUE) trial. For the primary end-point, the three secondary end-points and for all-cause death, outcomes were compared for individuals with baseline estimated creatinine clearance and estimated GFR < 60 ml/min and > or = 60 ml/min using hazard ratios and 95% confidence intervals. Coronary heart disease, left ventricular hypertrophy, age, sex and treatment effects were included as covariates in the model. For each end-point considered, the risk in individuals with poor renal function at baseline was greater than in those with better renal function. Estimated creatinine clearance (Cockcroft-Gault) was significantly predictive only of all-cause death [hazard ratio = 1.223, 95% confidence interval (CI) = 1.076-1.390; P = 0.0021] whereas estimated GFR was predictive of all outcomes except stroke. Hazard ratios (95% CIs) for estimated GFR were: primary cardiac end-point, 1.497 (1.332-1.682), P < 0.0001; myocardial infarction, 1.501 (1.254-1.796), P < 0.0001; congestive heart failure, 1.699 (1.435-2.013), P < 0.0001; stroke, 1.152 (0.952-1.394) P = 0.1452; and all-cause death, 1.231 (1.098-1.380), P = 0.0004. These results indicate that estimated glomerular filtration rate calculated with the MDRD formula is more informative than estimated creatinine clearance (Cockcroft-Gault) in the prediction of cardiovascular outcomes.

Assessment of right ventricular adaptability to loading conditions can improve the timing of listing to transplantation in patients with pulmonary arterial hypertension.

PubMed

Dandel, Michael; Knosalla, Christoph; Kemper, Dagmar; Stein, Julia; Hetzer, Roland

2015-03-01

Right ventricle (RV) performance is load dependent, and right-sided heart failure (RHF) is the main cause of death in pulmonary arterial hypertension (PAH). Prediction of RV worsening for timely identification of patients needing transplantation (Tx) is paramount. Assessment of RV adaptability to load has proved useful in certain clinical circumstances. This study assessed its predictive value for RHF-free and Tx-free outcome with PAH. Between 2006 and 2012, all potential Tx candidates with PAH, without RHF at the first evaluation, were selected for follow-up (except congenital heart diseases). At selection and at each follow-up, N-terminal prohormone brain natriuretic peptide (NT-proBNP) and the 6-minute walk distance were measured, and RV adaptability to load was assessed by echocardiography. Collected data were tested for the ability to predict RV stability and Tx-free survival. During a 12-month to 92-month follow-up, RHF developed in 23 of 79 evaluated patients, despite similar medication and no differences in initial RV size and ejection fraction compared with the patients who remained stable. However, unstable patients had an initially lower RV load-adaptation index and afterload-corrected peak global systolic longitudinal strain-rate values as well as higher RV dyssynchrony, tricuspid regurgitation, and NT-proBNP levels (p ≤ 0.01). At certain cutoff values, these variables appeared predictive for 1-year and 3-year freedom from RHF and 3-year Tx-free survival. An RV load-adaptation index reduction of ≥20% showed the highest predictive value (90.0%) for short-term (≤1 year) RV decompensation. Assessment of RV adaptability to load allows prediction of RV function and Tx-free survival with severe PAH during the next 1 to 3 years. This can improve the timing of listing for Tx. Copyright © 2015 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Approximating Long-Term Statistics Early in the Global Precipitation Measurement Era

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.; Huffman, George J.; Adler, Robert F.

2017-01-01

Long-term precipitation records are vital to many applications, especially the study of extreme events. The Tropical Rainfall Measuring Mission (TRMM) has served this need, but TRMMs successor mission, Global Precipitation Measurement (GPM), does not yet provide a long-term record. Quantile mapping, the conversion of values across paired empirical distributions, offers a simple, established means to approximate such long-term statistics, but only within appropriately defined domains. This method was applied to a case study in Central America, demonstrating that quantile mapping between TRMM and GPM data maintains the performance of a real-time landslide model. Use of quantile mapping could bring the benefits of the latest satellite-based precipitation dataset to existing user communities such as those for hazard assessment, crop forecasting, numerical weather prediction, and disease tracking.

Evaluating the validity of using unverified indices of body condition

USGS Publications Warehouse

Schamber, J.L.; Esler, Daniel N.; Flint, Paul L.

2009-01-01

Condition indices are commonly used in an attempt to link body condition of birds to ecological variables of interest, including demographic attributes such as survival and reproduction. Most indices are based on body mass adjusted for structural body size, calculated as simple ratios or residuals from regressions. However, condition indices are often applied without confirming their predictive value (i.e., without being validated against measured values of fat and protein), which we term ‘unverified’ use. We evaluated the ability of a number of unverified indices frequently found in the literature to predict absolute and proportional levels of fat and protein across five species of waterfowl. Among indices we considered, those accounting for body size never predicted absolute protein more precisely than body mass, however, some indices improved predictability of fat, although the form of the best index varied by species. Further, the gain in precision by using a condition index to predict either absolute or percent fat was minimal (rise in r2≤0.13), and in many cases model fit was actually reduced. Our data agrees with previous assertions that the assumption that indices provide more precise indicators of body condition than body mass alone is often invalid. We strongly discourage the use of unverified indices, because subjectively selecting indices likely does little to improve precision and might in fact decrease predictability relative to using body mass alone.

A pre-marketing ALT signal predicts post-marketing liver safety.

PubMed

Moylan, Cynthia A; Suzuki, Ayako; Papay, Julie I; Yuen, Nancy A; Ames, Michael; Hunt, Christine M

2012-08-01

Drug induced liver injury during drug development is evidenced by a higher incidence of serum alanine aminotransferase (ALT) elevations in treated versus placebo populations and termed an "ALT signal". We sought to quantify whether an ALT signal in pre-marketing clinical trials predicted post-marketing hepatotoxicity. Incidence of ALT elevations (ALT ≥ 3 times upper limits normal [× ULN]) for drug and placebo of new chemical entities and approved drugs associated with hepatotoxicity was calculated using the Food and Drug Administration (FDA) website. Post-marketing liver safety events were identified using the FDA Adverse Event Reporting System (AERS). The association of FDA AERS signal score (EB05 ≥ 2) and excess risk of pre-marketing ALT elevation (difference in incidence of ALT ≥ 3× ULN in treated versus placebo) was examined. An ALT signal of ≥ 1.2% was significantly associated with a post-marketing liver safety signal (p ≤ 0.013) and a 71.4% positive predictive value. An absent ALT signal was associated with a high likelihood of post-marketing liver safety; negative predictive value of 89.7%. Daily drug dose information improved the prediction of post-marketing liver safety. A cut-off of 1.2% increase in ALT ≥ 3× ULN in treated versus placebo groups provides an easily calculated method for predicting post-marketing liver safety. Published by Elsevier Inc.

In patients with minimally symptomatic OSA can baseline characteristics and early patterns of CPAP usage predict those who are likely to be longer-term users of CPAP

PubMed Central

Bratton, Daniel J.; Craig, Sonya E.; Kohler, Malcolm; Stradling, John R.

2016-01-01

Background Long-term continuous positive airway pressure (CPAP) usage varies between individuals. It would be of value to be able to identify those who are likely to benefit from CPAP (and use it long term), versus those who would not, and might therefore benefit from additional help early on. First, we explored whether baseline characteristics predicted CPAP usage in minimally symptomatic obstructive sleep apnoea (OSA) patients, a group who would be expected to have low usage. Second, we explored if early CPAP usage was predictive of longer-term usage, as has been shown in more symptomatic OSA patients. Methods The MOSAIC trial was a multi-centre randomised controlled trial where minimally symptomatic OSA patients were randomised to CPAP, or standard care, for 6 months. Here we have studied only those patients randomised to CPAP treatment. Baseline characteristics including symptoms, questionnaires [including the Epworth sleepiness score (ESS)] and sleep study parameters were recorded. CPAP usage was recorded at 2–4 weeks after initiation and after 6 months. The correlation and association between baseline characteristics and 6 months CPAP usage was assessed, as was the correlation between 2 and 4 weeks CPAP usage and 6 months CPAP usage. Results One hundred and ninety-five patients randomised to CPAP therapy had median [interquartile range (IQR)] CPAP usage of 2:49 (0:44, 5:13) h:min/night (h/n) at the 2–4 weeks visit, and 2:17 (0:08, 4:54) h/n at the 6 months follow-up visit. Only male gender was associated with increased long-term CPAP use (male usage 2:56 h/n, female 1:57 h/n; P=0.02). There was a moderate correlation between the usage of CPAP at 2–4 weeks and 6 months, with about 50% of the variability in long-term use being predicted by the short-term use. Conclusions In patients with minimally symptomatic OSA, our study has shown that male gender (and not OSA severity or symptom burden) is associated with increased long-term use of CPAP at 6 months. Although, in general, early patterns of CPAP usage predicted longer term use, there are patients in whom this is not the case, and patients with low initial usage may need to extend their CPAP trial before a decision about longer-term use is made. PMID:26904268

Development of Social Anxiety: Social Interaction Predictors of Implicit and Explicit Fear of Negative Evaluation

PubMed Central

Allen, Joseph P.

2012-01-01

Little is known about how to predict which individuals with known temperament vulnerabilities will go on to develop social anxiety problems. Adolescents (N = 185) were followed from age 13 to 18 to evaluate psychosocial, prospective predictors of social anxiety symptoms and fears of negative evaluation (FNE), after accounting for pre-existing social withdrawal symptoms. Results from structural equation modeling suggest that lack of perceived social acceptance predicts subsequent explicit social anxiety and FNE, whereas the emotional intensity of close peer interactions predicts subsequent implicit FNE. Results are discussed in terms of the importance of peer interaction in the development of social anxiety, and the value of measuring both implicit and explicit FNE. PMID:17171538

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE PAGES

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

2018-04-13

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Model for End-stage Liver Disease excluding INR (MELD-XI) score in critically ill patients: Easily available and of prognostic relevance

PubMed Central

Wernly, Bernhard; Lichtenauer, Michael; Franz, Marcus; Kabisch, Bjoern; Muessig, Johanna; Masyuk, Maryna; Hoppe, Uta C.; Kelm, Malte; Jung, Christian

2017-01-01

Purpose MELD-XI, an adapted version of Model for End-stage Liver Disease (MELD) score excluding INR, was reported to predict outcomes e.g. in patients with acute heart failure. We aimed to evaluate MELD-XI in critically ill patients admitted to an intensive care unit (ICU) for prognostic relevance. Methods A total of 4381 medical patients (66±14 years, 2862 male) admitted to a German ICU between 2004 and 2009 were included and retrospectively investigated. Admission diagnoses were e.g. myocardial infarction (n = 2034), sepsis (n = 694) and heart failure (n = 688). We divided our patients in two cohorts basing on their MELD-XI score and evaluated the MELD-XI score for its prognostic relevance regarding short-term and long-term survival. Optimal cut-offs were calculated by means of the Youden-Index. Results Patients with a MELD-XI score >12 had pronounced laboratory signs of organ failure and more comorbidities. MELD-XI >12 was associated with an increase in short-term (27% vs 6%; HR 4.82, 95%CI 3.93–5.93; p<0.001) and long-term (HR 3.69, 95%CI 3.20–4.25; p<0.001) mortality. In a univariate Cox regression analysis for all patients MELD-XI was associated with increased long-term mortality (changes per score point: HR 1.06, 95%CI 1.05–1.07; p<0.001) and remained to be associated with increased mortality after correction in a multivariate regression analysis for renal failure, liver failure, lactate concentration, blood glucose concentration, oxygenation and white blood count (HR 1.04, 95%CI 1.03–1.06; p<0.001). Optimal cut-off for the overall cohort was 11 and varied remarkably depending on the admission diagnosis: myocardial infarction (9), pulmonary embolism (9), cardiopulmonary resuscitation (17) and pneumonia (17). We performed ROC-analysis and compared the AUC: SAPS2 (0.78, 95%CI 0.76–0.80; p<0.0001) and APACHE (0.76, 95%CI 0.74–0.78; p<0.003) score were superior to MELD-XI (0.71, 95%CI 0.68–0.73) for prediction of mortality. Conclusions The easily calculable MELD-XI score is a robust and reliable tool to predict both intra-ICU and long-term mortality in critically ill medical patients admitted to an ICU. Optimal cut-off values for MELD-XI scores seem to depend on the primary disease and need to be validated in future prospective studies. Compared to SAPS2 and APACHE score, MELD-XI lacks precision but might have comparable and even additive value, as it is easily available and independent of subjective values. PMID:28151948

Model for End-stage Liver Disease excluding INR (MELD-XI) score in critically ill patients: Easily available and of prognostic relevance.

PubMed

Wernly, Bernhard; Lichtenauer, Michael; Franz, Marcus; Kabisch, Bjoern; Muessig, Johanna; Masyuk, Maryna; Hoppe, Uta C; Kelm, Malte; Jung, Christian

2017-01-01

MELD-XI, an adapted version of Model for End-stage Liver Disease (MELD) score excluding INR, was reported to predict outcomes e.g. in patients with acute heart failure. We aimed to evaluate MELD-XI in critically ill patients admitted to an intensive care unit (ICU) for prognostic relevance. A total of 4381 medical patients (66±14 years, 2862 male) admitted to a German ICU between 2004 and 2009 were included and retrospectively investigated. Admission diagnoses were e.g. myocardial infarction (n = 2034), sepsis (n = 694) and heart failure (n = 688). We divided our patients in two cohorts basing on their MELD-XI score and evaluated the MELD-XI score for its prognostic relevance regarding short-term and long-term survival. Optimal cut-offs were calculated by means of the Youden-Index. Patients with a MELD-XI score >12 had pronounced laboratory signs of organ failure and more comorbidities. MELD-XI >12 was associated with an increase in short-term (27% vs 6%; HR 4.82, 95%CI 3.93-5.93; p<0.001) and long-term (HR 3.69, 95%CI 3.20-4.25; p<0.001) mortality. In a univariate Cox regression analysis for all patients MELD-XI was associated with increased long-term mortality (changes per score point: HR 1.06, 95%CI 1.05-1.07; p<0.001) and remained to be associated with increased mortality after correction in a multivariate regression analysis for renal failure, liver failure, lactate concentration, blood glucose concentration, oxygenation and white blood count (HR 1.04, 95%CI 1.03-1.06; p<0.001). Optimal cut-off for the overall cohort was 11 and varied remarkably depending on the admission diagnosis: myocardial infarction (9), pulmonary embolism (9), cardiopulmonary resuscitation (17) and pneumonia (17). We performed ROC-analysis and compared the AUC: SAPS2 (0.78, 95%CI 0.76-0.80; p<0.0001) and APACHE (0.76, 95%CI 0.74-0.78; p<0.003) score were superior to MELD-XI (0.71, 95%CI 0.68-0.73) for prediction of mortality. The easily calculable MELD-XI score is a robust and reliable tool to predict both intra-ICU and long-term mortality in critically ill medical patients admitted to an ICU. Optimal cut-off values for MELD-XI scores seem to depend on the primary disease and need to be validated in future prospective studies. Compared to SAPS2 and APACHE score, MELD-XI lacks precision but might have comparable and even additive value, as it is easily available and independent of subjective values.

Effects of feather wear and temperature on prediction of food intake and residual food consumption.

PubMed

Herremans, M; Decuypere, E; Siau, O

1989-03-01

Heat production, which accounts for 0.6 of gross energy intake, is insufficiently represented in predictions of food intake. Especially when heat production is elevated (for example by lower temperature or poor feathering) the classical predictions based on body weight, body-weight change and egg mass are inadequate. Heat production was reliably estimated as [35.5-environmental temperature (degree C)] x [Defeathering (=%IBPW) + 21]. Including this term (PHP: predicted heat production) in equations predicting food intake significantly increased accuracy of prediction, especially under suboptimal conditions. Within the range of body weights tested (from 1.6 kg in brown layers to 2.8 kg in dwarf broiler breeders), body weight as an independent variable contributed little to the prediction of food intake; especially within strains its effect was better included in the intercept. Significantly reduced absolute values of residual food consumption were obtained over a wide range of conditions by using predictions of food intake based on body-weight change, egg mass, predicted heat production (PHP) and an intercept, instead of body weight, body-weight change, egg mass and an intercept.

An Elevated Maternal Plasma Soluble fms-Like Tyrosine Kinase-1 to Placental Growth Factor Ratio at Midtrimester Is a Useful Predictor for Preeclampsia.

PubMed

Hassan, Mahmoud Fathy; Rund, Nancy Mohamed Ali; Salama, Ahmed Husseiny

2013-01-01

Background. To assess the ability of mid-trimester sFlt-1/PlGF ratio for prediction of preeclampsia in two different Arabic populations. Methods. This study measured levels of sFlt-1, PlGF, and sFlt-1/PlGF ratio at midtrimester in 83 patients who developed preeclampsia with contemporary 250 matched controls. Results. Women subsequently developed preeclampsia had significantly lower PlGF levels and higher sFlt-1 and sFlt-1/PlGF ratio levels than women with normal pregnancies (P < 0.0001 for all). Women who with preterm preeclampsia had significantly higher sFlt-1 and sFlt-1/PlGF ratio than term preeclamptic women (P = 0.01, 0.003, resp.). A cutoff value of 3198 pg/mL for sFlt-1 was able to predict preeclampsia with sensitivity, specificity, and accuracy of 88%, 83.6%, and 84.7%, respectively, with odds ratio (OR) 37.2 [95% confidence interval (CI) 17.7-78.1]. PIGF at cutoff value of 138 pg/mL was able to predict preeclampsia with sensitivity, specificity, and accuracy of 85.5%, 77.2%, and 79.3%, respectively, with OR 20 [95% CI, 10.2-39.5]. The sFlt-1/PIGF ratio at cutoff value of 24.5 was able to predict preeclampsia with sensitivity, specificity, and accuracy of 91.6%, 86.4%, and 87.7%, respectively with OR 67 [95% CI, 29.3-162.1]. Conclusion. Midtrimester sFlt-1/PlGF ratio displayed the highest sensitivity, specificity, accuracy, and OR for prediction of preeclampsia, demonstrating that it may stipulate more effective prediction of preeclampsia development than individual factor assay.

Estimating and Predicting Metal Concentration Using Online Turbidity Values and Water Quality Models in Two Rivers of the Taihu Basin, Eastern China

PubMed Central

Yao, Hong; Zhuang, Wei; Qian, Yu; Xia, Bisheng; Yang, Yang; Qian, Xin

2016-01-01

Turbidity (T) has been widely used to detect the occurrence of pollutants in surface water. Using data collected from January 2013 to June 2014 at eleven sites along two rivers feeding the Taihu Basin, China, the relationship between the concentration of five metals (aluminum (Al), titanium (Ti), nickel (Ni), vanadium (V), lead (Pb)) and turbidity was investigated. Metal concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). The linear regression of metal concentration and turbidity provided a good fit, with R2 = 0.86–0.93 for 72 data sets collected in the industrial river and R2 = 0.60–0.85 for 60 data sets collected in the cleaner river. All the regression presented good linear relationship, leading to the conclusion that the occurrence of the five metals are directly related to suspended solids, and these metal concentration could be approximated using these regression equations. Thus, the linear regression equations were applied to estimate the metal concentration using online turbidity data from January 1 to June 30 in 2014. In the prediction, the WASP 7.5.2 (Water Quality Analysis Simulation Program) model was introduced to interpret the transport and fates of total suspended solids; in addition, metal concentration downstream of the two rivers was predicted. All the relative errors between the estimated and measured metal concentration were within 30%, and those between the predicted and measured values were within 40%. The estimation and prediction process of metals’ concentration indicated that exploring the relationship between metals and turbidity values might be one effective technique for efficient estimation and prediction of metal concentration to facilitate better long-term monitoring with high temporal and spatial density. PMID:27028017

Predictive Validity of National Basketball Association Draft Combine on Future Performance.

PubMed

Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

2018-02-01

Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

Estimating and Predicting Metal Concentration Using Online Turbidity Values and Water Quality Models in Two Rivers of the Taihu Basin, Eastern China.

PubMed

Yao, Hong; Zhuang, Wei; Qian, Yu; Xia, Bisheng; Yang, Yang; Qian, Xin

2016-01-01

Turbidity (T) has been widely used to detect the occurrence of pollutants in surface water. Using data collected from January 2013 to June 2014 at eleven sites along two rivers feeding the Taihu Basin, China, the relationship between the concentration of five metals (aluminum (Al), titanium (Ti), nickel (Ni), vanadium (V), lead (Pb)) and turbidity was investigated. Metal concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). The linear regression of metal concentration and turbidity provided a good fit, with R(2) = 0.86-0.93 for 72 data sets collected in the industrial river and R(2) = 0.60-0.85 for 60 data sets collected in the cleaner river. All the regression presented good linear relationship, leading to the conclusion that the occurrence of the five metals are directly related to suspended solids, and these metal concentration could be approximated using these regression equations. Thus, the linear regression equations were applied to estimate the metal concentration using online turbidity data from January 1 to June 30 in 2014. In the prediction, the WASP 7.5.2 (Water Quality Analysis Simulation Program) model was introduced to interpret the transport and fates of total suspended solids; in addition, metal concentration downstream of the two rivers was predicted. All the relative errors between the estimated and measured metal concentration were within 30%, and those between the predicted and measured values were within 40%. The estimation and prediction process of metals' concentration indicated that exploring the relationship between metals and turbidity values might be one effective technique for efficient estimation and prediction of metal concentration to facilitate better long-term monitoring with high temporal and spatial density.

Prediction of lung cancer patient survival via supervised machine learning classification techniques.

PubMed

Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

2017-12-01

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time with the ultimate goal to inform patient care decisions, and that the performance of these techniques with this particular dataset may be on par with that of classical methods. Copyright © 2017 Elsevier B.V. All rights reserved.

The effect of long term combined yoga practice on the basal metabolic rate of healthy adults.

PubMed

Chaya, M S; Kurpad, A V; Nagendra, H R; Nagarathna, R

2006-08-31

Different procedures practiced in yoga have stimulatory or inhibitory effects on the basal metabolic rate when studied acutely. In daily life however, these procedures are usually practiced in combination. The purpose of the present study was to investigate the net change in the basal metabolic rate (BMR) of individuals actively engaging in a combination of yoga practices (asana or yogic postures, meditation and pranayama or breathing exercises) for a minimum period of six months, at a residential yoga education and research center at Bangalore. The measured BMR of individuals practicing yoga through a combination of practices was compared with that of control subjects who did not practice yoga but led similar lifestyles. The BMR of the yoga practitioners was significantly lower than that of the non-yoga group, and was lower by about 13 % when adjusted for body weight (P < 0.001). This difference persisted when the groups were stratified by gender; however, the difference in BMR adjusted for body weight was greater in women than men (about 8 and 18% respectively). In addition, the mean BMR of the yoga group was significantly lower than their predicted values, while the mean BMR of non-yoga group was comparable with their predicted values derived from 1985 WHO/FAO/UNU predictive equations. This study shows that there is a significantly reduced BMR, probably linked to reduced arousal, with the long term practice of yoga using a combination of stimulatory and inhibitory yogic practices.

The effect of long term combined yoga practice on the basal metabolic rate of healthy adults

PubMed Central

Chaya, MS; Kurpad, AV; Nagendra, HR; Nagarathna, R

2006-01-01

Background Different procedures practiced in yoga have stimulatory or inhibitory effects on the basal metabolic rate when studied acutely. In daily life however, these procedures are usually practiced in combination. The purpose of the present study was to investigate the net change in the basal metabolic rate (BMR) of individuals actively engaging in a combination of yoga practices (asana or yogic postures, meditation and pranayama or breathing exercises) for a minimum period of six months, at a residential yoga education and research center at Bangalore. Methods The measured BMR of individuals practicing yoga through a combination of practices was compared with that of control subjects who did not practice yoga but led similar lifestyles. Results The BMR of the yoga practitioners was significantly lower than that of the non-yoga group, and was lower by about 13 % when adjusted for body weight (P < 0.001). This difference persisted when the groups were stratified by gender; however, the difference in BMR adjusted for body weight was greater in women than men (about 8 and 18% respectively). In addition, the mean BMR of the yoga group was significantly lower than their predicted values, while the mean BMR of non-yoga group was comparable with their predicted values derived from 1985 WHO/FAO/UNU predictive equations. Conclusion This study shows that there is a significantly reduced BMR, probably linked to reduced arousal, with the long term practice of yoga using a combination of stimulatory and inhibitory yogic practices. PMID:16945127

Value of intracochlear electrically evoked auditory brainstem response after cochlear implantation in patients with narrow internal auditory canal.

PubMed

Song, Mee Hyun; Bae, Mi Ran; Kim, Hee Nam; Lee, Won-Sang; Yang, Won Sun; Choi, Jae Young

2010-08-01

Cochlear implantation in patients with narrow internal auditory canal (IAC) can result in variable outcomes; however, preoperative evaluations have limitations in accurately predicting outcomes. In this study, we analyzed the outcomes of cochlear implantation in patients with narrow IAC and correlated the intracochlear electrically evoked auditory brainstem response (EABR) findings to postoperative performance to determine the prognostic significance of intracochlear EABR. Retrospective case series at a tertiary hospital. Thirteen profoundly deaf patients with narrow IAC who received cochlear implantation from 2002 to 2008 were included in this study. Postoperative performance was evaluated after at least 12 months of follow-up, and postoperative intracochlear EABR was measured to determine its correlation with outcome. The clinical significance of electrically evoked compound action potential (ECAP) was also analyzed. Patients with narrow IAC showed postoperative auditory performances ranging from CAP 0 to 4 after cochlear implantation. Intracochlear EABR measured postoperatively demonstrated prognostic value in the prediction of long-term outcomes, whereas ECAP measurements failed to show a significant correlation with outcome. Consistent with the advantages of intracochlear EABR over extracochlear EABR, this study demonstrates that intracochlear EABR has prognostic significance in predicting long-term outcomes in patients with narrow IAC. Intracochlear EABR measured either intraoperatively or in the early postoperative period may play an important role in deciding whether to continue with auditory rehabilitation using a cochlear implant or to switch to an auditory brainstem implant so as not to miss the optimal timing for language development.

Advanced Fuel Properties; A Computer Program for Estimating Property Values

DTIC Science & Technology

1993-05-01

security considerations, contractual obligations, or notice on a specific document. REPORT DOCUMENTATION PAGE Fogu Approwd I OMB No. 0704-01=5 Ps NP...found in fuels. 14. SUBJECT TERMS 15. NUMBEROF PAGES 175 Fuel properties, Physical Propertie, Thermodynamnics, Predictions 16. PRICE CODE 17. SECURITY ...CLASSIFICATION is. SECURrrY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITFATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT Unclassified

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

An evaluation of study design for estimating a time-of-day noise weighting

NASA Technical Reports Server (NTRS)

Fields, J. M.

1986-01-01

The relative importance of daytime and nighttime noise of the same noise level is represented by a time-of-day weight in noise annoyance models. The high correlations between daytime and nighttime noise were regarded as a major reason that previous social surveys of noise annoyance could not accurately estimate the value of the time-of-day weight. Study designs which would reduce the correlation between daytime and nighttime noise are described. It is concluded that designs based on short term variations in nighttime noise levels would not be able to provide valid measures of response to nighttime noise. The accuracy of the estimate of the time-of-day weight is predicted for designs which are based on long term variations in nighttime noise levels. For these designs it is predicted that it is not possible to form satisfactorily precise estimates of the time-of-day weighting.

Propellant Vaporization as a Criterion for Rocket-Engine Design; Experimental Performance, Vaporization and Heat-Transfer Rates with Various Propellant Combinations

NASA Technical Reports Server (NTRS)

Clark, Bruce J.; Hersch, Martin; Priem, Richard J.

1959-01-01

Experimental combustion efficiencies of eleven propellant combinations were determined as a function of chamber length. Efficiencies were measured in terms of characteristic exhaust velocities at three chamber lengths and in terms of gas velocities. The data were obtained in a nominal 200-pound-thrust rocket engine. Injector and engine configurations were kept essentially the same to allow comparison of the performance. The data, except for those on hydrazine and ammonia-fluorine, agreed with predicted results based on the assumption that vaporization of the propellants determines the rate of combustion. Decomposition in the liquid phase may be.responsible for the anomalous behavior of hydrazine. Over-all heat-transfer rates were also measured for each combination. These rates were close to the values predicted by standard heat-transfer calculations except for the combinations using ammonia.

Comparison of Code Predictions to Test Measurements for Two Orifice Compensated Hydrostatic Bearings at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Keba, John E.

1996-01-01

Rotordynamic coefficients obtained from testing two different hydrostatic bearings are compared to values predicted by two different computer programs. The first set of test data is from a relatively long (L/D=1) orifice compensated hydrostatic bearing tested in water by Texas A&M University (TAMU Bearing No.9). The second bearing is a shorter (L/D=.37) bearing and was tested in a lower viscosity fluid by Rocketdyne Division of Rockwell (Rocketdyne 'Generic' Bearing) at similar rotating speeds and pressures. Computed predictions of bearing rotordynamic coefficients were obtained from the cylindrical seal code 'ICYL', one of the industrial seal codes developed for NASA-LeRC by Mechanical Technology Inc., and from the hydrodynamic bearing code 'HYDROPAD'. The comparison highlights the difference the bearing has on the accuracy of the predictions. The TAMU Bearing No. 9 test data is closely matched by the predictions obtained for the HYDROPAD code (except for added mass terms) whereas significant differences exist between the data from the Rocketdyne 'Generic' bearing the code predictions. The results suggest that some aspects of the fluid behavior in the shorter, higher Reynolds Number 'Generic' bearing may not be modeled accurately in the codes. The ICYL code predictions for flowrate and direct stiffness approximately equal those of HYDROPAD. Significant differences in cross-coupled stiffness and the damping terms were obtained relative to HYDROPAD and both sets of test data. Several observations are included concerning application of the ICYL code.

Accuracy of color prediction of anthraquinone dyes in methanol solution estimated from first principle quantum chemistry computations.

PubMed

Cysewski, Piotr; Jeliński, Tomasz

2013-10-01

The electronic spectrum of four different anthraquinones (1,2-dihydroxyanthraquinone, 1-aminoanthraquinone, 2-aminoanthraquinone and 1-amino-2-methylanthraquinone) in methanol solution was measured and used as reference data for theoretical color prediction. The visible part of the spectrum was modeled according to TD-DFT framework with a broad range of DFT functionals. The convoluted theoretical spectra were validated against experimental data by a direct color comparison in terms of CIE XYZ and CIE Lab tristimulus model color. It was found, that the 6-31G** basis set provides the most accurate color prediction and there is no need to extend the basis set since it does not improve the prediction of color. Although different functionals were found to give the most accurate color prediction for different anthraquinones, it is possible to apply the same DFT approach for the whole set of analyzed dyes. Especially three functionals seem to be valuable, namely mPW1LYP, B1LYP and PBE0 due to very similar spectra predictions. The major source of discrepancies between theoretical and experimental spectra comes from L values, representing the lightness, and the a parameter, depicting the position on green→magenta axis. Fortunately, the agreement between computed and observed blue→yellow axis (parameter b) is very precise in the case of studied anthraquinone dyes in methanol solution. Despite discussed shortcomings, color prediction from first principle quantum chemistry computations can lead to quite satisfactory results, expressed in terms of color space parameters.

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

NASA Astrophysics Data System (ADS)

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Effects of physical aging on long-term behavior of composites

NASA Technical Reports Server (NTRS)

Brinson, L. Catherine

1993-01-01

The HSCT plane, envisioned to have a lifetime of over 60,000 flight hours and to travel at speeds in excess of Mach 2, is the source of intensive study at NASA. In particular, polymer matrix composites are being strongly considered for use in primary and secondary structures due to their high strength to weight ratio and the options of property tailoring. However, an added difficulty in the use of polymer based materials is that their properties change significantly over time, especially at the elevated temperatures that will be experienced during flight, and prediction of properties based on irregular thermal and mechanical loading is extremely difficult. This study focused on one aspect of long-term polymer composite behavior: physical aging. When a polymer is cooled to below its glass transition temperature, the material is not in thermodynamic equilibrium and the free volume and enthalpy evolve over time to approach their equilibrium values. During this time, the mechanical properties change significantly and this change is termed physical aging. This work begins with a review of the concepts of physical aging on a pure polymer system. The effective time theory, which can be used to predict long term behavior based on short term data, is mathematically formalized. The effects of aging to equilibrium are proven and discussed. The theory developed for polymers is then applied first to a unidirectional composite, then to a general laminate. Comparison to experimental data is excellent. It is shown that the effects of aging on the long-term properties of composites can be counter-intuitive, stressing the importance of the development and use of a predictive theory to analyze structures.

Testing a Model of Self-Management of Fluid Intake in Community-Residing Long-Term Indwelling Urinary Catheter Users

PubMed Central

Wilde, Mary H.; Crean, Hugh F.; McMahon, James M.; McDonald, Margaret V.; Tang, Wan; Brasch, Judith; Fairbanks, Eileen; Shah, Shivani; Zhang, Feng

2015-01-01

Background Urinary tract infection and blockage are serious and recurrent challenges for people with long-term indwelling catheters, and these catheter problems cause worry and anxiety when they disrupt normal daily activities. Objectives The goal was to determine whether urinary catheter-related self-management behaviors focusing on fluid intake would mediate fluid intake related self-efficacy toward decreasing catheter-associated urinary tract infection (CAUTI) and/or catheter blockage. Method The sample involved data collected from 180 adult community-living, long-term indwelling urinary catheter users. The authors tested a model of fluid intake self-management (F-SMG) related to fluid intake self-efficacy (F-SE) for key outcomes of CAUTI and blockage. To account for the large number of zeros in both outcomes, a zero inflated negative binomial (ZINB) structural equation model was tested. Results Structurally, F-SE was positively associated with F-SMG, suggesting that higher F-SE predicts more (higher) F-SMG; however, F-SMG was not associated with either the frequency of CAUTI’s or the presence or absence of CAUTI. F-SE was positively related to F-SMG and F-SMG predicted less frequency of catheter blockage, but neither F-SE nor F-SMG predicted the presence or absence of blockage. Discussion Further research is needed to better understand determinants of CAUTI in long-term catheter users and factors which might influence or prevent its occurrence. Increased confidence (self-efficacy) and self-management behaviors to promote fluid intake could be of value in long-term urinary catheter users to decrease catheter blockage. PMID:26938358

Role of EEG background activity, seizure burden and MRI in predicting neurodevelopmental outcome in full-term infants with hypoxic-ischaemic encephalopathy in the era of therapeutic hypothermia.

PubMed

Weeke, Lauren C; Boylan, Geraldine B; Pressler, Ronit M; Hallberg, Boubou; Blennow, Mats; Toet, Mona C; Groenendaal, Floris; de Vries, Linda S

2016-11-01

To investigate the role of EEG background activity, electrographic seizure burden, and MRI in predicting neurodevelopmental outcome in infants with hypoxic-ischaemic encephalopathy (HIE) in the era of therapeutic hypothermia. Twenty-six full-term infants with HIE (September 2011-September 2012), who had video-EEG monitoring during the first 72 h, an MRI performed within the first two weeks and neurodevelopmental assessment at two years were evaluated. EEG background activity at age 24, 36 and 48 h, seizure burden, and severity of brain injury on MRI, were compared and related to neurodevelopmental outcome. EEG background activity was significantly associated with neurodevelopmental outcome at 36 h (p = 0.009) and 48 h after birth (p = 0.029) and with severity of brain injury on MRI at 36 h (p = 0.002) and 48 h (p = 0.018). All infants with a high seizure burden and moderate-severe injury on MRI had an abnormal outcome. The positive predictive value (PPV) of EEG for abnormal outcome was 100% at 36 h and 48 h and the negative predictive value (NPV) was 75% at 36 h and 69% at 48 h. The PPV of MRI was 100% and the NPV 85%. The PPV of seizure burden was 78% and the NPV 71%. Severely abnormal EEG background activity at 36 h and 48 h after birth was associated with severe injury on MRI and abnormal neurodevelopmental outcome. High seizure burden was only associated with abnormal outcome in combination with moderate-severe injury on MRI. Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

The ability of an electrocardiogram to predict fatal and non-fatal cardiac events in asymptomatic middle-aged subjects.

PubMed

Terho, Henri K; Tikkanen, Jani T; Kenttä, Tuomas V; Junttila, M Juhani; Aro, Aapo L; Anttonen, Olli; Kerola, Tuomas; Rissanen, Harri A; Knekt, Paul; Reunanen, Antti; Huikuri, Heikki V

2016-11-01

The long-term prognostic value of a standard 12-lead electrocardiogram (ECG) for predicting cardiac events in apparently healthy middle-aged subjects is not well defined. A total of 9511 middle-aged subjects (mean age 43 ± 8.2 years, 52% males) without a known cardiac disease and with a follow-up 40 years were included in the study. Fatal and non-fatal cardiac events were collected from the national registries. The predictive value of ECG was separately analyzed for 10 and 30 years. Major ECG abnormalities were classified according to the Minnesota code. Subjects with major ECG abnormalities (N = 1131) had an increased risk of cardiac death after 10-years (adjusted hazard ratio [HR] 1.7; 95% confidence interval [95% CI], 1.1-2.5, p = 0.009) and 30-years of follow-up (HR 1.3, 95% CI, 1.1-1.5, p < 0.001). Model discrimination measured with the C-index showed only a minor improvement with the inclusion of ECG abnormalities: 0.851 versus 0.853 and 0.742 versus 0.743 for 10- and 30-year follow-up, respectively. ECG did not predict non-fatal cardiac events after 10-years or 30-years of follow-up. Major ECG abnormalities are associated with an increased risk of short and long-term cardiac mortality in middle-aged subjects. However, the improvement in discrimination between subjects with and without fatal cardiac events was marginal with abnormal ECG. Abnormalities observed on 12-lead electrocardiogram are shown to have prognostic significance for cardiac events in elderly subjects without known cardiac disease. Our results suggest that ECG abnormalities increase the risk of fatal cardiac events also in middle-aged healthy subjects.

The Value, Protocols, and Scientific Ethics of Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Jordan, Thomas H.

2013-04-01

Earthquakes are different from other common natural hazards because precursory signals diagnostic of the magnitude, location, and time of impending seismic events have not yet been found. Consequently, the short-term, localized prediction of large earthquakes at high probabilities with low error rates (false alarms and failures-to-predict) is not yet feasible. An alternative is short-term probabilistic forecasting based on empirical statistical models of seismic clustering. During periods of high seismic activity, short-term earthquake forecasts can attain prospective probability gains up to 1000 relative to long-term forecasts. The value of such information is by no means clear, however, because even with hundredfold increases, the probabilities of large earthquakes typically remain small, rarely exceeding a few percent over forecasting intervals of days or weeks. Civil protection agencies have been understandably cautious in implementing operational forecasting protocols in this sort of "low-probability environment." This paper will explore the complex interrelations among the valuation of low-probability earthquake forecasting, which must account for social intangibles; the protocols of operational forecasting, which must factor in large uncertainties; and the ethics that guide scientists as participants in the forecasting process, who must honor scientific principles without doing harm. Earthquake forecasts possess no intrinsic societal value; rather, they acquire value through their ability to influence decisions made by users seeking to mitigate seismic risk and improve community resilience to earthquake disasters. According to the recommendations of the International Commission on Earthquake Forecasting (www.annalsofgeophysics.eu/index.php/annals/article/view/5350), operational forecasting systems should appropriately separate the hazard-estimation role of scientists from the decision-making role of civil protection authorities and individuals. They should provide public sources of information on short-term probabilities that are authoritative, scientific, open, and timely. Alert procedures should be negotiated with end-users to facilitate decisions at different levels of society, based in part on objective analysis of costs and benefits but also on less tangible aspects of value-of-information, such as gains in psychological preparedness and resilience. Unfortunately, in most countries, operational forecasting systems do not conform to such high standards, and earthquake scientists are often called upon to advise the public in roles that exceed their civic authority, expertise in risk communication, and situational knowledge. Certain ethical principles are well established; e.g., announcing unreliable predictions in public forums should be avoided, because bad information can be dangerous. But what are the professional responsibilities of earthquake scientists during seismic crises, especially when the public information through official channels is thought to be inadequate or incorrect? How much should these responsibilities be discounted in the face of personal liability? How should scientists contend with highly uncertain forecasts? To what degree should the public be involved in controversies about forecasting results? No simple answers to these questions can be offered, but the need for answers can be reduced by improving operational forecasting systems. This will require more substantial, and more trustful, collaborations between scientists, civil authorities, and public stakeholders.

Noise contribution to the correlation between temperature-induced localized reflectance of diabetic skin and blood glucose.

PubMed

Lowery, Michael G; Calfin, Brenda; Yeh, Shu-Jen; Doan, Tao; Shain, Eric; Hanna, Charles; Hohs, Ronald; Kantor, Stan; Lindberg, John; Khalil, Omar S

2006-01-01

We used the effect of temperature on the localized reflectance of human skin to assess the role of noise sources on the correlation between temperature-induced fractional change in optical density of human skin (DeltaOD(T)) and blood glucose concentration [BG]. Two temperature-controlled optical probes at 30 degrees C contacted the skin, one was then cooled by -10 degrees C; the other was heated by +10 degrees C. DeltaOD(T) upon cooling or heating was correlated with capillary [BG] of diabetic volunteers over a period of three days. Calibration models in the first two days were used to predict [BG] in the third day. We examined the conditions where the correlation coefficient (R2) for predicting [BG] in a third day ranked higher than R2 values resulting from fitting permutations of randomized [BG] to the same DeltaOD(T) values. It was possible to establish a four-term linear regression correlation between DeltaOD(T) upon cooling and [BG] with a correlation coefficient higher than that of an established noise threshold in diabetic patients that were mostly females with less than 20 years of diabetes duration. The ability to predict [BG] values with a correlation coefficient above biological and body-interface noise varied between the cases of cooling and heating.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud.

PubMed

Zia Ullah, Qazi; Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

PubMed Central

Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers. PMID:28811819

Predictive methods of some optoelectronic properties for blends based on quaternized polysulfones

NASA Astrophysics Data System (ADS)

Dobos, Adina Maria; Filimon, Anca

2017-11-01

Blends based on quaternized polysulfones were investigated in terms of optical and electronic properties. By applying the Bicerano formalism the refractive index and dielectric constant were evaluated. Also, the dielectric constant of these blends was studied as a function of temperature and frequency. As the result of the main chain structure and charged groups, an increase in theoretical values of the refractive index and dielectric constant with increasing of the ionic quaternized units content in the polymer blend occurs. Additionally, decrease in the dielectric constant with the increase of frequency and decrease of temperature was observed. Refractive index and dielectric constant values indicate that the analyzed samples are transparent and can be used in obtaining of materials with applications involving a small polarizability. Thus, the results are important in prediction of the special optoelectronic features of new polymers blends to obtain high-performance materials with applications in electronic and biomedical fields.

Experience Transitioning Models and Data at the NOAA Space Weather Prediction Center

NASA Astrophysics Data System (ADS)

Berger, Thomas

2016-07-01

The NOAA Space Weather Prediction Center has a long history of transitioning research data and models into operations and with the validation activities required. The first stage in this process involves demonstrating that the capability has sufficient value to customers to justify the cost needed to transition it and to run it continuously and reliably in operations. Once the overall value is demonstrated, a substantial effort is then required to develop the operational software from the research codes. The next stage is to implement and test the software and product generation on the operational computers. Finally, effort must be devoted to establishing long-term measures of performance, maintaining the software, and working with forecasters, customers, and researchers to improve over time the operational capabilities. This multi-stage process of identifying, transitioning, and improving operational space weather capabilities will be discussed using recent examples. Plans for future activities will also be described.

A multiphase equation of state of three solid phases, liquid, and gas for titanium

NASA Astrophysics Data System (ADS)

Pecker, S.; Eliezer, S.; Fisher, D.; Henis, Z.; Zinamon, Z.

2005-08-01

A multiple-phase equation of state of the α phase, β phase, ω phase, liquid, and gas for titanium is presented. This equation of state is thermodynamically consistent, based on a three-term semiempirical model for the Helmholtz free energy. The parameters of the free energy are first evaluated from the experimental data and solid-state theoretical calculations. Then, the values of the parameters are adjusted using a numerical minimization scheme based on the simplex algorithm, to values that best reproduce measured phase diagrams and other experimental data. The predicted phase diagram shows a compression-induced β-ω transition, up to a β-ω-liquid triple point at ˜45GPa and ˜2200K. For pressures above this triple point, the melting occurs from the ω phase. Moreover, no β-ω transition is predicted along the Hugoniot curve starting at STP conditions.

Clinical value of serum anti-mullerian hormone and inhibin B in prediction of ovarian response in patients with polycystic ovary syndrome.

PubMed

Zhang, Fan; Liu, Xiao-Ling; Rong, Nan; Huang, Xiao-Wen

2017-02-01

The present study aimed to investigate the clinical value of serum anti-mullerian hormone (AMH) and inhibin B (INHB) in predicting the ovarian response of patients with polycystic ovary syndrome (PCOS). A total of 120 PCOS patients were enrolled and divided into three groups in terms of the ovarian response: a low-response group (n=36), a normal-response group (n=44), and a high-response group (n=40). The serum AMH and INHB levels were measured by enzyme-linked immunosorbent assay (ELISA). The follicle stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E2) levels were determined by chemiluminescence microparticle immunoassay. The correlation of the serum AMH and INHB levels with other indicators was analyzed. A receiver operating characteristic (ROC) curve was established to analyze the prediction of ovarian response by AMH and INHB. The results showed that there were significant differences in age, body mass index (BMI), FSH, total gonadotropin-releasing hormone (GnRH), LH, E2, and antral follicle counts (AFCs) between the groups (P<0.05). The serum AMH and INHB levels were increased significantly with the ovarian response of PCOS patients increasing (P<0.05). The serum AMH and INHB levels were negatively correlated with the age, BMI, FSH level, Gn, and E2 levels (P<0.05). They were positively correlated with the LH levels and AFCs (P<0.05). ROC curve analysis of serum AMH and INHB in prediction of a low ovarian response showed that the area under the ROC curve (AUC) value of the serum AMH level was 0.817, with a cut-off value of 1.29 ng/mL. The sensitivity and specificity were 71.2% and 79.6%, respectively. The AUC value of serum INHB was 0.674, with a cut-off value of 38.65 ng/mL, and the sensitivity and specificity were 50.7% and 74.5%, respectively. ROC curve analysis showed when the serum AMH and INHB levels were used to predict a high ovarian response, the AUC value of the serum AMH level was 0.742, with a cut-off value of 2.84 ng/mL, and the sensitivity and specificity were 72.7% and 65.9%, respectively; the AUC value of the serum INHB level was 0.551 with a cut-off of 45.76 ng/mL, and the sensitivity and specificity were 76.3% and 40.2%, respectively. It was suggested the serum AMH and INHB levels have high clinical value in predicting the ovarian response of PCOS patients.

Collective behaviour in vertebrates: a sensory perspective

PubMed Central

Collignon, Bertrand; Fernández-Juricic, Esteban

2016-01-01

Collective behaviour models can predict behaviours of schools, flocks, and herds. However, in many cases, these models make biologically unrealistic assumptions in terms of the sensory capabilities of the organism, which are applied across different species. We explored how sensitive collective behaviour models are to these sensory assumptions. Specifically, we used parameters reflecting the visual coverage and visual acuity that determine the spatial range over which an individual can detect and interact with conspecifics. Using metric and topological collective behaviour models, we compared the classic sensory parameters, typically used to model birds and fish, with a set of realistic sensory parameters obtained through physiological measurements. Compared with the classic sensory assumptions, the realistic assumptions increased perceptual ranges, which led to fewer groups and larger group sizes in all species, and higher polarity values and slightly shorter neighbour distances in the fish species. Overall, classic visual sensory assumptions are not representative of many species showing collective behaviour and constrain unrealistically their perceptual ranges. More importantly, caution must be exercised when empirically testing the predictions of these models in terms of choosing the model species, making realistic predictions, and interpreting the results. PMID:28018616

Cosmological perturbations in inflation and in de Sitter space

NASA Astrophysics Data System (ADS)

Pimentel, Guilherme Leite

This thesis focuses on various aspects of inflationary fluctuations. First, we study gravitational wave fluctuations in de Sitter space. The isometries of the spacetime constrain to a few parameters the Wheeler-DeWitt wavefunctional of the universe, to cubic order in fluctuations. At cubic order, there are three independent terms in the wavefunctional. From the point of view of the bulk action, one term corresponds to Einstein gravity, and a new term comes from a cubic term in the curvature tensor. The third term is a pure phase and does not give rise to a new shape for expectation values of graviton fluctuations. These results can be seen as the leading order non-gaussian contributions in a slow-roll expansion for inflationary observables. We also use the wavefunctional approach to explain a universal consistency condition of n-point expectation values in single field inflation. This consistency condition relates a soft limit of an n-point expectation value to ( n-1)-point expectation values. We show how these conditions can be easily derived from the wavefunctional point of view. Namely, they follow from the momentum constraint of general relativity, which is equivalent to the constraint of spatial diffeomorphism invariance. We also study expectation values beyond tree level. We show that subhorizon fluctuations in loop diagrams do not generate a mass term for superhorizon fluctuations. Such a mass term could spoil the predictivity of inflation, which is based on the existence of properly defined field variables that become constant once their wavelength is bigger than the size of the horizon. Such a mass term would be seen in the two point expectation value as a contribution that grows linearly with time at late times. The absence of this mass term is closely related to the soft limits studied in previous chapters. It is analogous to the absence of a mass term for the photon in quantum electrodynamics, due to gauge symmetry. Finally, we use the tools of holography and entanglement entropy to study superhorizon correlations in quantum field theories in de Sitter space. The entropy has interesting terms that have no equivalent in flat space field theories. These new terms are due to particle creation in an expanding universe. The entropy is calculated directly for free massive scalar theories. For theories with holographic duals, it is determined by the area of some extremal surface in the bulk geometry. We calculate the entropy for different classes of holographic duals. For one of these classes, the holographic dual geometry is an asymptotically Anti-de Sitter space that decays into a crunching cosmology, an open Friedmann-Robertson-Walker universe. The extremal surface used in the calculation of the entropy lies almost entirely on the slice of maximal scale factor of the crunching cosmology.

Soluble E-cadherin is an independent pretherapeutic factor for long-term survival in gastric cancer.

PubMed

Chan, Annie On-On; Chu, Kent-Man; Lam, Shiu-Kum; Wong, Benjamin Chun-Yu; Kwok, Ka-Fai; Law, Simon; Ko, Samuel; Hui, Wai-Mo; Yueng, Yui-Hung; Wong, John

2003-06-15

To evaluate whether pretherapeutic serum soluble E-cadherin is an independent factor predicting long-term survival in gastric cancer. Gastric cancer remains the second leading cause of cancer-related deaths in the world, but a satisfactory tumor marker is currently unavailable for gastric cancer. Soluble E-cadherin has recently been found to have prognostic value in gastric cancer. One hundred sixteen patients with histologically proven gastric adenocarcinoma were included in the trial. Pretherapeutic serum was collected, and soluble E-cadherin was assayed using a commercially available enzyme-linked immunosorbent assay kit. The patients were followed up prospectively at the outpatient clinic. There were 75 men and 41 women, with a mean (+/- SD) age of 66 +/- 14 years. Forty-eight percent of tumors were located in the gastric antrum. The median survival time was 11 months. The mean pretherapeutic value of soluble E-cadherin was 9,159 ng/mL (range, 6,002 to 10,025 ng/mL), and the mean pretherapeutic level of carcinoembryonic antigen was 11 ng/mL (range, 0.3 to 4,895 ng/mL). On multivariate analysis, soluble E-cadherin is an independent factor predicting long-term survival. Ninety percent of patients with a serum level of E-cadherin greater than 10,000 ng/mL had a survival time of less than 3 years (P =.009). Soluble E-cadherin is a potentially valuable pretherapeutic prognostic factor in patients with gastric cancer.

Development of a coupled level set and immersed boundary method for predicting dam break flows

NASA Astrophysics Data System (ADS)

Yu, C. H.; Sheu, Tony W. H.

2017-12-01

Dam-break flow over an immersed stationary object is investigated using a coupled level set (LS)/immersed boundary (IB) method developed in Cartesian grids. This approach adopts an improved interface preserving level set method which includes three solution steps and the differential-based interpolation immersed boundary method to treat fluid-fluid and solid-fluid interfaces, respectively. In the first step of this level set method, the level set function ϕ is advected by a pure advection equation. The intermediate step is performed to obtain a new level set value through a new smoothed Heaviside function. In the final solution step, a mass correction term is added to the re-initialization equation to ensure the new level set is a distance function and to conserve the mass bounded by the interface. For accurately calculating the level set value, the four-point upwinding combined compact difference (UCCD) scheme with three-point boundary combined compact difference scheme is applied to approximate the first-order derivative term shown in the level set equation. For the immersed boundary method, application of the artificial momentum forcing term at points in cells consisting of both fluid and solid allows an imposition of velocity condition to account for the presence of solid object. The incompressible Navier-Stokes solutions are calculated using the projection method. Numerical results show that the coupled LS/IB method can not only predict interface accurately but also preserve the mass conservation excellently for the dam-break flow.

Early PET/CT scan is more effective than RECIST in predicting outcome of patients with liver metastases from colorectal cancer treated with preoperative chemotherapy plus bevacizumab.

PubMed

Lastoria, Secondo; Piccirillo, Maria Carmela; Caracò, Corradina; Nasti, Guglielmo; Aloj, Luigi; Arrichiello, Cecilia; de Lutio di Castelguidone, Elisabetta; Tatangelo, Fabiana; Ottaiano, Alessandro; Iaffaioli, Rosario Vincenzo; Izzo, Francesco; Romano, Giovanni; Giordano, Pasqualina; Signoriello, Simona; Gallo, Ciro; Perrone, Francesco

2013-12-01

Markers predictive of treatment effect might be useful to improve the treatment of patients with metastatic solid tumors. Particularly, early changes in tumor metabolism measured by PET/CT with (18)F-FDG could predict the efficacy of treatment better than standard dimensional Response Evaluation Criteria In Solid Tumors (RECIST) response. We performed PET/CT evaluation before and after 1 cycle of treatment in patients with resectable liver metastases from colorectal cancer, within a phase 2 trial of preoperative FOLFIRI plus bevacizumab. For each lesion, the maximum standardized uptake value (SUV) and the total lesion glycolysis (TLG) were determined. On the basis of previous studies, a ≤ -50% change from baseline was used as a threshold for significant metabolic response for maximum SUV and, exploratively, for TLG. Standard RECIST response was assessed with CT after 3 mo of treatment. Pathologic response was assessed in patients undergoing resection. The association between metabolic and CT/RECIST and pathologic response was tested with the McNemar test; the ability to predict progression-free survival (PFS) and overall survival (OS) was tested with the Log-rank test and a multivariable Cox model. Thirty-three patients were analyzed. After treatment, there was a notable decrease of all the parameters measured by PET/CT. Early metabolic PET/CT response (either SUV- or TLG-based) had a stronger, independent and statistically significant predictive value for PFS and OS than both CT/RECIST and pathologic response at multivariate analysis, although with different degrees of statistical significance. The predictive value of CT/RECIST response was not significant at multivariate analysis. PET/CT response was significantly predictive of long-term outcomes during preoperative treatment of patients with liver metastases from colorectal cancer, and its predictive ability was higher than that of CT/RECIST response after 3 mo of treatment. Such findings need to be confirmed by larger prospective trials.

The Thermodynamics of Drunk Driving

NASA Astrophysics Data System (ADS)

Thompson, Robert Q.

1997-05-01

Chemical and instrumental tests for driving under the influence of alcohol (DUI) measure the concentration of ethanol in the breath (BrAC), while state DUI laws are described in terms of blood alcohol concentration (BAC). Consequently, accurate and fair conversion from BrAC to BAC is crucial to the judicial process. Theoretical treatment of the water-air-ethanol equilibrium system and the related blood-breath-ethanol system, based on principles from general chemistry and biology, yields an equation relating the ratio of BAC to BrAC to the absolute temperature of the breath, the fraction of water in the blood, and the enthalpy and entropy of vaporization of ethanol from aqueous solution. The model equation predicts an average value for the ratio of 2350+100, not significantly different from reported experimental values. An exponential temperature dependence is predicted and has been confirmed experimentally as well. Biological, chemical, and instrumental variables are described along with their contributions to the overall uncertainty in the value of BrAC/BAC. While the forensic science community uses, and debates, a fixed ratio of 2100, the theoretical model suggests that a value of 1880 should be used to reduce the fraction of false positives to <1%.

Response of SOM Decomposition to Anthropogenic N Deposition: Simulations From the PnET-SOM Model.

NASA Astrophysics Data System (ADS)

Tonitto, C.; Goodale, C. L.; Ollinger, S. V.; Jenkins, J. P.

2008-12-01

Anthropogenic forcing of the C and N cycles has caused rapid change in atmospheric CO2 and N deposition, with complex and uncertain effects on forest C and N balance. With some exceptions, models of forest ecosystem response to anthropogenic perturbation have historically focused more on aboveground than belowground processes; the complexity of soil organic matter (SOM) is often represented with abstract or incomplete SOM pools, and remains difficult to quantify. We developed a model of SOM dynamics in northern hardwood forests with explicit feedbacks between C and N cycles. The soil model is linked to the aboveground dynamics of the PnET model to form PnET-SOM. The SOM model includes: 1) physically measurable SOM pools, including humic and mineral-associated SOM in O, A, and B soil horizons, 2) empirical soil turnover times based on 14C data, 3) alternative SOM decomposition algorithms with and without explicit microbial processing, and 4) soluble element transport explicitly linked to the hydrologic cycle. We tested model sensitivity to changes in litter decomposition rate (k) and completeness of decomposition (limit value) by altering these parameters based on experimental observations from long-term litter decomposition experiments with N fertilization treatments. After a 100 year simulation, the Oe+Oa horizon SOC pool was reduced by 15 % and the A-horizon humified SOC was reduced by 7 % for N deposition scenarios relative to forests without N fertilization. In contrast, predictions for slower time-scale pools showed negligible variation in response to variation in the limit values tested, with A-horizon mineral SOC pools reduced by < 3 % and B-horizon mineral SOC reduced by 0.1 % for N deposition scenarios relative to forests without N fertilization. The model was also used to test the effect of varying initial litter decomposition rate to simulate response to N deposition. In contrast to the effect of varying limit values, simulations in which only k-values were varied did not drastically alter the predicted SOC pool distribution throughout the soil profile, but did significantly alter the Oi SOC pool. These results suggest that describing soil response to N deposition via alteration of the limit value alone, or as a combined alteration of limit value and the initial decomposition rate, can lead to significant variation in predicted long-term C storage.

A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

NASA Astrophysics Data System (ADS)

Jakubowski, Jacek

2014-12-01

The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

Response Surface Modeling Using Multivariate Orthogonal Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; DeLoach, Richard

2001-01-01

A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.

Detecting complexes from edge-weighted PPI networks via genes expression analysis.

PubMed

Zhang, Zehua; Song, Jian; Tang, Jijun; Xu, Xinying; Guo, Fei

2018-04-24

Identifying complexes from PPI networks has become a key problem to elucidate protein functions and identify signal and biological processes in a cell. Proteins binding as complexes are important roles of life activity. Accurate determination of complexes in PPI networks is crucial for understanding principles of cellular organization. We propose a novel method to identify complexes on PPI networks, based on different co-expression information. First, we use Markov Cluster Algorithm with an edge-weighting scheme to calculate complexes on PPI networks. Then, we propose some significant features, such as graph information and gene expression analysis, to filter and modify complexes predicted by Markov Cluster Algorithm. To evaluate our method, we test on two experimental yeast PPI networks. On DIP network, our method has Precision and F-Measure values of 0.6004 and 0.5528. On MIPS network, our method has F-Measure and S n values of 0.3774 and 0.3453. Comparing to existing methods, our method improves Precision value by at least 0.1752, F-Measure value by at least 0.0448, S n value by at least 0.0771. Experiments show that our method achieves better results than some state-of-the-art methods for identifying complexes on PPI networks, with the prediction quality improved in terms of evaluation criteria.

A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model.

PubMed

McEwan, Phil; Bennett Wilton, Hayley; Ong, Albert C M; Ørskov, Bjarne; Sandford, Richard; Scolari, Francesco; Cabrera, Maria-Cristina V; Walz, Gerd; O'Reilly, Karl; Robinson, Paul

2018-02-13

Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study aimed to develop a natural history model of ADPKD that predicted progression rates and long-term outcomes in patients with differing baseline characteristics. The ADPKD Outcomes Model (ADPKD-OM) was developed using available patient-level data from the placebo arm of the Tolvaptan Efficacy and Safety in Management of ADPKD and its Outcomes Study (TEMPO 3:4; ClinicalTrials.gov identifier NCT00428948). Multivariable regression equations estimating annual rates of ADPKD progression, in terms of total kidney volume (TKV) and estimated glomerular filtration rate, formed the basis of the lifetime patient-level simulation model. Outputs of the ADPKD-OM were compared against external data sources to validate model accuracy and generalisability to other ADPKD patient populations, then used to predict long-term outcomes in a cohort matched to the overall TEMPO 3:4 study population. A cohort with baseline patient characteristics consistent with TEMPO 3:4 was predicted to reach ESRD at a mean age of 52 years. Most patients (85%) were predicted to reach ESRD by the age of 65 years, with many progressing to ESRD earlier in life (18, 36 and 56% by the age of 45, 50 and 55 years, respectively). Consistent with previous research and clinical opinion, analyses supported the selection of baseline TKV as a prognostic factor for ADPKD progression, and demonstrated its value as a strong predictor of future ESRD risk. Validation exercises and illustrative analyses confirmed the ability of the ADPKD-OM to accurately predict disease progression towards ESRD across a range of clinically-relevant patient profiles. The ADPKD-OM represents a robust tool to predict natural disease progression and long-term outcomes in ADPKD patients, based on readily available and/or measurable clinical characteristics. In conjunction with clinical judgement, it has the potential to support decision-making in research and clinical practice.

Development and validation of a cost-utility model for Type 1 diabetes mellitus.

PubMed

Wolowacz, S; Pearson, I; Shannon, P; Chubb, B; Gundgaard, J; Davies, M; Briggs, A

2015-08-01

To develop a health economic model to evaluate the cost-effectiveness of new interventions for Type 1 diabetes mellitus by their effects on long-term complications (measured through mean HbA1c ) while capturing the impact of treatment on hypoglycaemic events. Through a systematic review, we identified complications associated with Type 1 diabetes mellitus and data describing the long-term incidence of these complications. An individual patient simulation model was developed and included the following complications: cardiovascular disease, peripheral neuropathy, microalbuminuria, end-stage renal disease, proliferative retinopathy, ketoacidosis, cataract, hypoglycemia and adverse birth outcomes. Risk equations were developed from published cumulative incidence data and hazard ratios for the effect of HbA1c , age and duration of diabetes. We validated the model by comparing model predictions with observed outcomes from studies used to build the model (internal validation) and from other published data (external validation). We performed illustrative analyses for typical patient cohorts and a hypothetical intervention. Model predictions were within 2% of expected values in the internal validation and within 8% of observed values in the external validation (percentages represent absolute differences in the cumulative incidence). The model utilized high-quality, recent data specific to people with Type 1 diabetes mellitus. In the model validation, results deviated less than 8% from expected values. © 2014 Research Triangle Institute d/b/a RTI Health Solutions. Diabetic Medicine © 2014 Diabetes UK.

The FIB-4 score predicts postoperative short-term outcomes of hepatocellular carcinoma fulfilling the milan criteria.

PubMed

Dong, J; Xu, X-h; Ke, M-y; Xiang, J-x; Liu, W-y; Liu, X-m; Wang, B; Zhang, X-f; Lv, Y

2016-05-01

The fibrosis score 4 (FIB-4) score is a useful tool to determine the degree of hepatic fibrosis. Liver fibrosis and cirrhosis are well-known predictors of postoperative complications after hepatectomy. This study examined the impact of FIB-4 on postoperative short-term outcomes of patients with hepatocellular carcinoma (HCC). Three hundred and fifty patients undergoing hepatectomy for HCC between 2008 and 2013 were enrolled. The receiver operating characteristic (ROC) curve analysis was performed to determine the cutoff value of the FIB-4. Univariate and multivariate analysis was performed to identify the risk factors. The correlation of the preoperative FIB-4 value with clinicopathological parameters was examined. Postoperative complications were observed in 202 (57.7%) patients. The optimal cutoff value of the FIB-4 was set at 2.88 and 3.85 for postoperative complications and intraoperative blood loss respectively. It was also an independent prognostic factor for postoperative complications (hazard ratio [HR], 1.202; 95% CI, 1.076-1.344; P = 0.001) and intraoperative blood loss (HR, 1.196; 95% CI, 1.091-1.343; P < 0.001) by multivariate analysis. The FIB-4 was significantly correlated with age, liver function, coagulation function, blood loss, intraoperative blood transfusion (all P < 0.05). Preoperative FIB-4 is a useful index to predict postoperative outcomes in patients with HCC. The FIB-4 should be assessed routinely for hepatocellular carcinoma patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Probabilistic seismic loss estimation via endurance time method

NASA Astrophysics Data System (ADS)

Tafakori, Ehsan; Pourzeynali, Saeid; Estekanchi, Homayoon E.

2017-01-01

Probabilistic Seismic Loss Estimation is a methodology used as a quantitative and explicit expression of the performance of buildings using terms that address the interests of both owners and insurance companies. Applying the ATC 58 approach for seismic loss assessment of buildings requires using Incremental Dynamic Analysis (IDA), which needs hundreds of time-consuming analyses, which in turn hinders its wide application. The Endurance Time Method (ETM) is proposed herein as part of a demand propagation prediction procedure and is shown to be an economical alternative to IDA. Various scenarios were considered to achieve this purpose and their appropriateness has been evaluated using statistical methods. The most precise and efficient scenario was validated through comparison against IDA driven response predictions of 34 code conforming benchmark structures and was proven to be sufficiently precise while offering a great deal of efficiency. The loss values were estimated by replacing IDA with the proposed ETM-based procedure in the ATC 58 procedure and it was found that these values suffer from varying inaccuracies, which were attributed to the discretized nature of damage and loss prediction functions provided by ATC 58.

Basic numerical competences in large-scale assessment data: Structure and long-term relevance.

PubMed

Hirsch, Stefa; Lambert, Katharina; Coppens, Karien; Moeller, Korbinian

2018-03-01

Basic numerical competences are seen as building blocks for later numerical and mathematical achievement. The current study aimed at investigating the structure of early numeracy reflected by different basic numerical competences in kindergarten and its predictive value for mathematical achievement 6 years later using data from large-scale assessment. This allowed analyses based on considerably large sample sizes (N > 1700). A confirmatory factor analysis indicated that a model differentiating five basic numerical competences at the end of kindergarten fitted the data better than a one-factor model of early numeracy representing a comprehensive number sense. In addition, these basic numerical competences were observed to reliably predict performance in a curricular mathematics test in Grade 6 even after controlling for influences of general cognitive ability. Thus, our results indicated a differentiated view on early numeracy considering basic numerical competences in kindergarten reflected in large-scale assessment data. Consideration of different basic numerical competences allows for evaluating their specific predictive value for later mathematical achievement but also mathematical learning difficulties. Copyright © 2017 Elsevier Inc. All rights reserved.

Nalidixic acid surrogate test for susceptibility to ciprofloxacin in Salmonella. Revisiting the question.

PubMed

Guzmán-Martín, José Luis; Navarro-Marí, José María; Expósito-Ruiz, Manuela; Gutiérrez-Fernández, José

2018-05-16

We investigated the reliability of nalidixic acid (NA) susceptibility as a marker of ciprofloxacin susceptibility in Salmonella, analysing 302 stool isolates. NC53 of the MicroScan system was used for NA susceptibility tests and the E-test was used for ciprofloxacin susceptibility tests. Among the isolates, 178 (58.9 %) were serogroup B, 74 (24.5 %) were serogroup D, 27 (8.9 %) were serogroup C and 23 (7.6 %) were from other minor serogroups. Globally, susceptibility to NA correctly predicted the susceptibility of Salmonella to ciprofloxacin, with a sensitivity of 81.5 %, a specificity of 97.6 %, and positive and negative predictive values of 88 and 96 %, respectively. However, there were differences among the serogroups in terms of sensitivity (P<0.001) and positive predictive values (P=0.013). NA is a reliable marker for serogroup D, but not for serogroups B or C. According to these findings, NA susceptibility measured with the MicroScan system can be used as a marker of ciprofloxacin resistance in some serogroups in our setting.

Long-term bleeding risk prediction in 'real world' patients with atrial fibrillation: Comparison of the HAS-BLED and ABC-Bleeding risk scores. The Murcia Atrial Fibrillation Project.

PubMed

Esteve-Pastor, María Asunción; Rivera-Caravaca, José Miguel; Roldan, Vanessa; Vicente, Vicente; Valdés, Mariano; Marín, Francisco; Lip, Gregory Y H

2017-10-05

Risk scores in patients with atrial fibrillation (AF) based on clinical factors alone generally have only modest predictive value for predicting high risk patients that sustain events. Biomarkers might be an attractive prognostic tool to improve bleeding risk prediction. The new ABC-Bleeding score performed better than HAS-BLED score in a clinical trial cohort but has not been externally validated. The aim of this study was to analyze the predictive performance of the ABC-Bleeding score compared to HAS-BLED score in an independent "real-world" anticoagulated AF patients with long-term follow-up. We enrolled 1,120 patients stable on vitamin K antagonist treatment. The HAS-BLED and ABC-Bleeding scores were quantified. Predictive values were compared by c-indexes, IDI, NRI, as well as decision curve analysis (DCA). Median HAS-BLED score was 2 (IQR 2-3) and median ABC-Bleeding was 16.5 (IQR 14.3-18.6). After 6.5 years of follow-up, 207 (2.84 %/year) patients had major bleeding events, of which 65 (0.89 %/year) had intracranial haemorrhage (ICH) and 85 (1.17 %/year) had gastrointestinal bleeding events (GIB). The c-index of HAS-BLED was significantly higher than ABC-Bleeding for major bleeding (0.583 vs 0.518; p=0.025), GIB (0.596 vs 0.519; p=0.017) and for the composite of ICH-GIB (0.593 vs 0.527; p=0.030). NRI showed a significant negative reclassification for major bleeding and for the composite of ICH-GIB with the ABC-Bleeding score compared to HAS-BLED. Using DCAs, the use of HAS-BLED score gave an approximate net benefit of 4 % over the ABC-Bleeding score. In conclusion, in the first "real-world" validation of the ABC-Bleeding score, HAS-BLED performed significantly better than the ABC-Bleeding score in predicting major bleeding, GIB and the composite of GIB and ICH.

High resolution statistical downscaling of the EUROSIP seasonal prediction. Application for southeastern Romania

NASA Astrophysics Data System (ADS)

Busuioc, Aristita; Dumitrescu, Alexandru; Dumitrache, Rodica; Iriza, Amalia

2017-04-01

Seasonal climate forecasts in Europe are currently issued at the European Centre for Medium-Range Weather Forecasts (ECMWF) in the form of multi-model ensemble predictions available within the "EUROSIP" system. Different statistical techniques to calibrate, downscale and combine the EUROSIP direct model output are used to optimize the quality of the final probabilistic forecasts. In this study, a statistical downscaling model (SDM) based on canonical correlation analysis (CCA) is used to downscale the EUROSIP seasonal forecast at a spatial resolution of 1km x 1km over the Movila farm placed in southeastern Romania. This application is achieved in the framework of the H2020 MOSES project (http://www.moses-project.eu). The combination between monthly standardized values of three climate variables (maximum/minimum temperatures-Tmax/Tmin, total precipitation-Prec) is used as predictand while combinations of various large-scale predictors are tested in terms of their availability as outputs in the seasonal EUROSIP probabilistic forecasting (sea level pressure, temperature at 850 hPa and geopotential height at 500 hPa). The predictors are taken from the ECMWF system considering 15 members of the ensemble, for which the hindcasts since 1991 until present are available. The model was calibrated over the period 1991-2014 and predictions for summers 2015 and 2016 were achieved. The calibration was made for the ensemble average as well as for each ensemble member. The model was developed for each lead time: one month anticipation for June, two months anticipation for July and three months anticipation for August. The main conclusions from these preliminary results are: best predictions (in terms of the anomaly sign) for Tmax (July-2 months anticipation, August-3 months anticipation) for both years (2015, 2016); for Tmin - good predictions only for August (3 months anticipation ) for both years; for precipitation, good predictions for July (2 months anticipation) in 2015 and August (3 months anticipation) in 2016; failed prediction for June (1-month anticipation) for all parameters. To see if the results obtained for 2015 and 2016 summers are in agreement with the general ECMWF model performance in forecast of the three predictors used in the CCA SDM calibration, the mean bias and root mean square errors (RMSE) calculated over the entire period in each grid point, for each ensemble member and ensemble average were computed. The obtained results are confirmed, showing highest ECMWF performance in forecasting of the three predictors for 3 months anticipation (August) and lowest performance for one month anticipation (June). The added value of the CCA SDM in forecasting local Tmax/Tmin and total precipitation was compared to the ECMWF performance using nearest grid point method. Comparisons were performed for the 1991-2014 period, taking into account the forecast made in May for July. An important improvement was found for the CCA SDM predictions in terms of the RMSE value (computed against observations) for Tmax/Tmin and less for precipitation. The tests are in progress for the other summer months (June, July).

Rheumatoid arthritis patient perceptions on the value of predictive testing for treatments: a qualitative study.

PubMed

Kumar, Kanta; Peters, Sarah; Barton, Anne

2016-11-08

Rheumatoid arthritis (RA) is a long term condition that requires early treatment to control symptoms and improve long-term outcomes. Lack of response to RA treatments is not only a waste of healthcare resources, but also causes disability and distress to patients. Identifying biomarkers predictive of treatment response offers an opportunity to improve clinical decisions about which treatment to recommend in patients and could ultimately lead to better patient outcomes. The aim of this study was to explore the understanding of and factors affecting Rheumatoid Arthritis (RA) patients' decisions around predictive treatment testing. A qualitative study was conducted with a purposive sample of 16 patients with RA from three major UK cities. Four focus groups explored patient perceptions of the use of biomarker tests to predict response to treatments. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis by three researchers. Data were organised within three interlinking themes: [1] Perceptions of predictive tests and patient preference of tests; [2] Utility of the test to manage expectations; [3] The influence of the disease duration on take up of predictive testing. During consultations for predictive testing, patients felt they would need, first, careful explanations detailing the consequences of untreated RA and delayed treatment response and, second, support to balance the risks of tests, which might be invasive and/or only moderately accurate, with the potential benefits of better management of symptoms. This study provides important insights into predictive testing. Besides supporting clinical decision making, the development of predictive testing in RA is largely supported by patients. Developing strategies which communicate risk information about predictive testing effectively while reducing the psychological burden associated with this information will be essential to maximise uptake.

Post audit of a numerical prediction of wellfield drawdown in a semiconfined aquifer system

USGS Publications Warehouse

Stewart, M.; Langevin, C.

1999-01-01

A numerical ground water flow model was created in 1978 and revised in 1981 to predict the drawdown effects of a proposed municipal wellfield permitted to withdraw 30 million gallons per day (mgd; 1.1 x 105 m3/day) of water from the semiconfined Floridan Aquifer system. The predictions are based on the assumption that water levels in the semiconfined Floridan Aquifer reach a long-term, steady-state condition within a few days of initiation of pumping. Using this assumption, a 75 day simulation without water table recharge, pumping at the maximum permitted rates, was considered to represent a worst-case condition and the greatest drawdowns that could be experienced during wellfield operation. This method of predicting wellfield effects was accepted by the permitting agency. For this post audit, observed drawdowns were derived by taking the difference between pre-pumping and post-pumping potentiometric surface levels. Comparison of predicted and observed drawdowns suggests that actual drawdown over a 12 year period exceeds predicted drawdown by a factor of two or more. Analysis of the source of error in the 1981 predictions suggests that the values used for transmissivity, storativity, specific yield, and leakance are reasonable at the wellfield scale. Simulation using actual 1980-1992 pumping rates improves the agreement between predicted and observed drawdowns. The principal source of error is the assumption that water levels in a semiconfined aquifer achieve a steady-state condition after a few days or weeks of pumping. Simulations using a version of the 1981 model modified to include recharge and evapotranspiration suggest that it can take hundreds of days or several years for water levels in the linked Surficial and Floridan Aquifers to reach an apparent steady-state condition, and that slow declines in levels continue for years after the initiation of pumping. While the 1981 'impact' model can be used for reasonably predicting short-term, wellfield-scale effects of pumping, using a 75 day long simulation without recharge to predict the long-term behavior of the wellfield was an inappropriate application, resulting in significant underprediction of wellfield effects.A numerical ground water flow model was created in 1978 and revised in 1981 to predict the drawdown effects of a proposed municipal wellfield permitted to withdraw 30 million gallons per day (mgd; 1.1??105 m3/day) of water from the semiconfined Floridan Aquifer system. The predictions are based on the assumption that water levels in the semiconfined Floridan Aquifer reach a long-term, steady-state condition within a few days of initiation of pumping. Using this assumption, a 75 day simulation without water table recharge, pumping at the maximum permitted rates, was considered to represent a worst-case condition and the greatest drawdowns that could be experienced during wellfield operation. This method of predicting wellfield effects was accepted by the permitting agency. For this post audit, observed drawdowns were derived by taking the difference between pre-pumping and post-pumping potentiometric surface levels. Comparison of predicted and observed drawdowns suggests that actual drawdown over a 12 year period exceeds predicted drawdown by a factor of two or more. Analysis of the source of error in the 1981 predictions suggests that the values used for transmissivity, storativity, specific yield, and leakance are reasonable at the wellfield scale. Simulation using actual 1980-1992 pumping rates improves the agreement between predicted and observed drawdowns. The principal source of error is the assumption that water levels in a semiconfined aquifer achieve a steady-state condition after a few days or weeks of pumping. Simulations using a version of the 1981 model modified to include recharge and evapotranspiration suggest that it can take hundreds of days or several years for water levels in the linked Surficial and Floridan Aquifers to reach an apparent stead

Preoperative Serum Thyrotropin to Thyroglobulin Ratio Is Effective for Thyroid Nodule Evaluation in Euthyroid Patients.

PubMed

Wang, Lina; Li, Hao; Yang, Zhongyuan; Guo, Zhuming; Zhang, Quan

2015-07-01

This study was designed to assess the efficiency of the serum thyrotropin to thyroglobulin ratio for thyroid nodule evaluation in euthyroid patients. Cross-sectional study. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China. Retrospective analysis was performed for 400 previously untreated cases presenting with thyroid nodules. Thyroid function was tested with commercially available radioimmunoassays. The receiver operating characteristic curves were constructed to determine cutoff values. The efficacy of the thyrotropin:thyroglobulin ratio and thyroid-stimulating hormone for thyroid nodule evaluation was evaluated in terms of sensitivity, specificity, positive predictive value, positive likelihood ratio, negative likelihood ratio, and odds ratio. In receiver operating characteristic curve analysis, the area under the curve was 0.746 for the thyrotropin:thyroglobulin ratio and 0.659 for thyroid-stimulating hormone. With a cutoff point value of 24.97 IU/g for the thyrotropin:thyroglobulin ratio, the sensitivity, specificity, positive predictive value, positive likelihood ratio, and negative likelihood ratio were 78.9%, 60.8%, 75.5%, 2.01, and 0.35, respectively. The odds ratio for the thyrotropin:thyroglobulin ratio indicating malignancy was 5.80. With a cutoff point value of 1.525 µIU/mL for thyroid-stimulating hormone, the sensitivity, specificity, positive predictive value, positive likelihood ratio, and negative likelihood ratio were 74.0%, 53.2%, 70.8%, 1.58, and 0.49, respectively. The odds ratio indicating malignancy for thyroid-stimulating hormone was 3.23. Increasing preoperative serum thyrotropin:thyroglobulin ratio is a risk factor for thyroid carcinoma, and the correlation of the thyrotropin:thyroglobulin ratio to malignancy is higher than that for serum thyroid-stimulating hormone. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Changes in the yield of chlorophyll a from dissolved available inorganic nitrogen after an enrichment event—applications for predicting eutrophication in coastal waters

NASA Astrophysics Data System (ADS)

Edwards, V. R.; Tett, P.; Jones, K. J.

2003-11-01

An understanding of the dynamic relationship between nitrogen supply and the formation of phytoplankton biomass is important in predicting and avoiding marine eutrophication. This relationship can be expressed as the short-term yield q of chlorophyll from dissolved available inorganic nitrogen (DAIN), the sum of nitrate, nitrite and ammonium. This paper communicates the results of a continuous culture nitrate enrichment experiment undertaken to investigate the cumulative yield of chlorophyll from DAIN ( q). The purposes of the study were: to acquire a better understanding of the relationship between chlorophyll formation and DAIN; to obtain values that could be used in models for predicting eutrophication. The results of a time series experiment carried out using microplankton (all organisms <200 μm in size) indicate that the parameter q does not have a single value but is affected by the ecophysiological response of phytoplankton to changing nutrient status after an enrichment event. It is also dependent on changes in the allocation of nitrogen between autotrophs and heterotrophs. The value of yield obtained at the height of the bloom can be represented by q (max) (2.35 μg chl (μmol N) -1). The post-bloom, steady state value of q can be represented by qeq (0.95 μg chl (μmol N) -1). The microcosm steady state yield was not significantly different from the median value obtained from synoptic studies of Scottish west coast waters. It is proposed that qeq is the most appropriate value for assessing the general potential for eutrophication resulting from continuous nutrient enrichment into coastal waters. It is further proposed that q (max) be used for cases of sporadic enrichment and where a short burst of unrestricted growth may be detrimental.

Effect of bulk modulus on deformation of the brain under rotational accelerations

NASA Astrophysics Data System (ADS)

Ganpule, S.; Daphalapurkar, N. P.; Cetingul, M. P.; Ramesh, K. T.

2018-01-01

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2-mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber bundles for modeling white matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformations in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

A utility/cost analysis of breast cancer risk prediction algorithms

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

2016-03-01

Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening.

Sex differences in the prediction of the effectiveness of paroxetine for patients with major depressive disorder identified using a receiver operating characteristic curve analysis for early response.

PubMed

Tomita, Tetsu; Yasui-Furukori, Norio; Norio, Yasui-Furukori; Sato, Yasushi; Nakagami, Taku; Tsuchimine, Shoko; Kaneda, Ayako; Kaneko, Sunao

2014-01-01

We investigated cutoff values for the early response of patients with major depressive disorder to paroxetine and their sex differences by using a receiver operating characteristic (ROC) curve analysis to predict the effectiveness of paroxetine. In total, 120 patients with major depressive disorder were enrolled and treated with 10-40 mg/day paroxetine for 6 weeks; 89 patients completed the protocol. A clinical evaluation using the Montgomery-Asberg Depression Rating Scale (MADRS) was performed at weeks 0, 1, 2, 4, and 6. In male subjects, the cutoff values for MADRS improvement rating in week 1, week 2, and week 4 were 20.9%, 34.9%, and 33.3%, respectively. The sensitivities and the specificities were 83.3% and 80.0%, 83.3% and 80.0%, and 100% and 90%, respectively. The areas under the curve (AUC) were 0.908, 0.821, and 0.979, respectively. In female subjects, the cutoff values for the MADRS improvement rating in week 1, week 2, and week 4 were 21.4%, 35.7%, and 32.3%, respectively. The sensitivities and the specificities were 71.4% and 84.6%, 73.8% and 76.9%, and 90.5% and 76.9%, respectively. The AUCs were 0.781, 0.735, and 0.904, respectively. Early improvement with paroxetine may predict the long-term response. The accuracy of the prediction for the response is higher in male subjects.

Application of the migration models implemented in the decision system MOIRA-PLUS to assess the long term behaviour of (137)Cs in water and fish of the Baltic Sea.

PubMed

Monte, Luigi

2014-08-01

This work presents and discusses the results of an application of the contaminant migration models implemented in the decision support system MOIRA-PLUS to simulate the time behaviour of the concentrations of (137)Cs of Chernobyl origin in water and fish of the Baltic Sea. The results of the models were compared with the extensive sets of highly reliable empirical data of radionuclide contamination available from international databases and covering a period of, approximately, twenty years. The model application involved three main phases: a) the customisation performed by using hydrological, morphometric and water circulation data obtained from the literature; b) a blind test of the model results, in the sense that the models made use of default values of the migration parameters to predict the dynamics of the contaminant in the environmental components; and c) the adjustment of the model parameter values to improve the agreement of the predictions with the empirical data. The results of the blind test showed that the models successfully predicted the empirical contamination values within the expected range of uncertainty of the predictions (confidence level at 68% of approximately a factor 2). The parameter adjustment can be helpful for the assessment of the fluxes of water circulating among the main sub-basins of the Baltic Sea, substantiating the usefulness of radionuclides to trace the movement of masses of water in seas. Copyright © 2014 Elsevier Ltd. All rights reserved.

Value of long-term streamflow forecast to reservoir operations for water supply in snow-dominated catchments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea F.

In this study, we develop a forecast-based adaptive control framework for Oroville reservoir, California, to assess the value of seasonal and inter-annual forecasts for reservoir operation.We use an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity hydrology model. The optimal sequence of daily release decisions from the reservoir is then determined by Model Predictive Control, a flexible and adaptive optimization scheme.We assess the forecast value by comparing system performance based on the ESP forecasts with that based on climatology and a perfect forecast. In addition, we evaluate system performance based onmore » a synthetic forecast, which is designed to isolate the contribution of seasonal and inter-annual forecast skill to the overall value of the ESP forecasts.Using the same ESP forecasts, we generalize our results by evaluating forecast value as a function of forecast skill, reservoir features, and demand. Our results show that perfect forecasts are valuable when the water demand is high and the reservoir is sufficiently large to allow for annual carry-over. Conversely, ESP forecast value is highest when the reservoir can shift water on a seasonal basis.On average, for the system evaluated here, the overall ESP value is 35% less than the perfect forecast value. The inter-annual component of the ESP forecast contributes 20-60% of the total forecast value. Improvements in the seasonal component of the ESP forecast would increase the overall ESP forecast value between 15 and 20%.« less

Combined predictive value of the expanded donor criteria for long-term graft survival of kidneys from donors after cardiac death: A single-center experience over three decades.

PubMed

Kusaka, Mamoru; Kubota, Yusuke; Sasaki, Hitomi; Fukami, Naohiko; Fujita, Tamio; Hirose, Yuichi; Takahashi, Hiroshi; Kenmochi, Takashi; Shiroki, Ryoichi; Hoshinaga, Kiyotaka

2016-04-01

Kidneys procured from the deceased hold great potential for expanding the donor pool. The aims of the present study were to investigate the post-transplant outcomes of renal allografts recovered from donors after cardiac death, to identify risk factors affecting the renal prognosis and to compare the long-term survival from donors after cardiac death according to the number of risk factors shown by expanded criteria donors. A total of 443 grafts recovered using an in situ regional cooling technique from 1983 to 2011 were assessed. To assess the combined predictive value of the significant expanded criteria donor risk criteria, the patients were divided into three groups: those with no expanded criteria donor risk factors (no risk), one expanded criteria donor risk factor (single-risk) and two or more expanded criteria donor risk factors (multiple-risk). Among the donor factors, age ≥50 years, hypertension, maximum serum creatinine level ≥1.5 mg/dL and a warm ischemia time ≥30 min were identified as independent predictors of long-term graft failure on multivariate analysis. Regarding the expanded criteria donors criteria for marginal donors, cerebrovascular disease, hypertension and maximum serum creatinine level ≥1.5 mg/dL were identified as significant predictors on univariate analysis. The single- and multiple-risk groups showed 2.01- and 2.40-fold higher risks of graft loss, respectively. Renal grafts recovered from donors after cardiac death donors have a good renal function with an excellent long-term graft survival. However, an increased number of expanded criteria donors risk factors increase the risk of graft loss. © 2016 The Japanese Urological Association.

Neuroimaging and Neurodevelopmental Outcome in Extremely Preterm Infants

PubMed Central

Barnes, Patrick D.; Bulas, Dorothy; Slovis, Thomas L.; Finer, Neil N.; Wrage, Lisa A.; Das, Abhik; Tyson, Jon E.; Stevenson, David K.; Carlo, Waldemar A.; Walsh, Michele C.; Laptook, Abbot R.; Yoder, Bradley A.; Van Meurs, Krisa P.; Faix, Roger G.; Rich, Wade; Newman, Nancy S.; Cheng, Helen; Heyne, Roy J.; Vohr, Betty R.; Acarregui, Michael J.; Vaucher, Yvonne E.; Pappas, Athina; Peralta-Carcelen, Myriam; Wilson-Costello, Deanne E.; Evans, Patricia W.; Goldstein, Ricki F.; Myers, Gary J.; Poindexter, Brenda B.; McGowan, Elisabeth C.; Adams-Chapman, Ira; Fuller, Janell; Higgins, Rosemary D.

2015-01-01

BACKGROUND: Extremely preterm infants are at risk for neurodevelopmental impairment (NDI). Early cranial ultrasound (CUS) is usual practice, but near-term brain MRI has been reported to better predict outcomes. We prospectively evaluated MRI white matter abnormality (WMA) and cerebellar lesions, and serial CUS adverse findings as predictors of outcomes at 18 to 22 months’ corrected age. METHODS: Early and late CUS, and brain MRI were read by masked central readers, in a large cohort (n = 480) of infants <28 weeks’ gestation surviving to near term in the Neonatal Research Network. Outcomes included NDI or death after neuroimaging, and significant gross motor impairment or death, with NDI defined as cognitive composite score <70, significant gross motor impairment, and severe hearing or visual impairment. Multivariable models evaluated the relative predictive value of neuroimaging while controlling for other factors. RESULTS: Of 480 infants, 15 died and 20 were lost. Increasing severity of WMA and significant cerebellar lesions on MRI were associated with adverse outcomes. Cerebellar lesions were rarely identified by CUS. In full multivariable models, both late CUS and MRI, but not early CUS, remained independently associated with NDI or death (MRI cerebellar lesions: odds ratio, 3.0 [95% confidence interval: 1.3–6.8]; late CUS: odds ratio, 9.8 [95% confidence interval: 2.8–35]), and significant gross motor impairment or death. In models that did not include late CUS, MRI moderate-severe WMA was independently associated with adverse outcomes. CONCLUSIONS: Both late CUS and near-term MRI abnormalities were associated with outcomes, independent of early CUS and other factors, underscoring the relative prognostic value of near-term neuroimaging. PMID:25554820

Relationship of neonatal cerebral blood flow velocity asymmetry with early motor, cognitive and language development in term infants.

PubMed

Wu, Ying-Chin; Hsieh, Wu-Shiun; Hsu, Chyong-Hsin; Chiu, Nan-Chang; Chou, Hung-Chieh; Chen, Chien-Yi; Peng, Shinn-Forng; Hung, Han-Yang; Chang, Jui-Hsing; Chen, Wei J; Jeng, Suh-Fang

2013-05-01

The objective of this study was to examine the relationships of Doppler cerebral blood flow velocity (CBFV) asymmetry measures with developmental outcomes in term infants. Doppler CBFV parameters (peak systolic velocity [PSV] and mean velocity [MV]) of the bilateral middle cerebral arteries of 52 healthy term infants were prospectively examined on postnatal days 1-5, and then their motor, cognitive and language development was evaluated with the Bayley Scales of Infant and Toddler Development, Third Edition, at 6, 12, 18 and 24 months of age. The left CBFV asymmetry measure (PSV or MV) was calculated by subtracting the right-side value from the left-side value. Left CBFV asymmetry measures were significantly positively related to motor scores at 6 (r = 0.3-0.32, p < 0.05) and 12 (r = 0.35, p < 0.05) months of age, but were not related to cognitive or language outcome. Thus, the leftward hemodynamic status of the middle cerebral arteries, as measured by cranial Doppler ultrasound in the neonatal period, predicts early motor outcome in term infants. Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Medial orbitofrontal cortex codes relative rather than absolute value of financial rewards in humans.

PubMed

Elliott, R; Agnew, Z; Deakin, J F W

2008-05-01

Functional imaging studies in recent years have confirmed the involvement of orbitofrontal cortex (OFC) in human reward processing and have suggested that OFC responses are context-dependent. A seminal electrophysiological experiment in primates taught animals to associate abstract visual stimuli with differently valuable food rewards. Subsequently, pairs of these learned abstract stimuli were presented and firing of OFC neurons to the medium-value stimulus was measured. OFC firing was shown to depend on the relative value context. In this study, we developed a human analogue of this paradigm and scanned subjects using functional magnetic resonance imaging. The analysis compared neuronal responses to two superficially identical events, which differed only in terms of the preceding context. Medial OFC response to the same perceptual stimulus was greater when the stimulus predicted the more valuable of two rewards than when it predicted the less valuable. Additional responses were observed in other components of reward circuitry, the amygdala and ventral striatum. The central finding is consistent with the primate results and suggests that OFC neurons code relative rather than absolute reward value. Amygdala and striatal involvement in coding reward value is also consistent with recent functional imaging data. By using a simpler and less confounded paradigm than many functional imaging studies, we are able to demonstrate that relative financial reward value per se is coded in distinct subregions of an extended reward and decision-making network.

Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations.

PubMed

Robb, Matthew L; Böhning, Dankmar

2011-02-01

Capture–recapture techniques have been used for considerable time to predict population size. Estimators usually rely on frequency counts for numbers of trappings; however, it may be the case that these are not available for a particular problem, for example if the original data set has been lost and only a summary table is available. Here, we investigate techniques for specific examples; the motivating example is an epidemiology study by Mosley et al., which focussed on a cholera outbreak in East Pakistan. To demonstrate the wider range of the technique, we also look at a study for predicting the long-term outlook of the AIDS epidemic using information on number of sexual partners. A new estimator is developed here which uses the EM algorithm to impute unobserved values and then uses these values in a similar way to the existing estimators. The results show that a truncated approach – mimicking the Chao lower bound approach – gives an improved estimate when population homogeneity is violated.

A direct comparison of decision rules for early discharge of suspected acute coronary syndromes in the era of high sensitivity troponin.

PubMed

Chew, Pei Gee; Frost, Fredrick; Mullen, Liam; Fisher, Michael; Zadeh, Heidar; Grainger, Ruth; Albouaini, Khaled; Dodd, James; Patel, Bilal; Velavan, Periaswamy; Kunadian, Babu; Rawat, Anju; Obafemi, Toba; Tong, Sarah; Jones, Julia; Khand, Aleem

2018-02-01

We tested the hypothesis that a single high sensitivity troponin at limits of detection (LOD HSTnT) (<5 ng/l) combined with a presentation non-ischaemic electrocardiogram is superior to low-risk Global Registry of Acute Coronary Events (GRACE) (<75), Thrombolysis in Myocardial Infarction (TIMI) (≤1) and History, ECG, Age, Risk factors and Troponin (HEART) score (≤3) as an aid to early, safe discharge for suspected acute coronary syndrome. In a prospective cohort study, risk scores were computed in consecutive patients with suspected acute coronary syndrome presenting to the Emergency Room of a large English hospital. Adjudication of myocardial infarction, as per third universal definition, involved a two-physician, blinded, independent review of all biomarker positive chest pain re-presentations to any national hospital. The primary and secondary outcome was a composite of type 1 myocardial infarction, unplanned coronary revascularisation and all cause death (MACE) at six weeks and one year. Of 3054 consecutive presentations with chest pain 1642 had suspected acute coronary syndrome (52% male, median age 59 years, 14% diabetic, 20% previous myocardial infarction). Median time from chest pain to presentation was 9.7 h. Re-presentations occurred in eight hospitals with 100% follow-up achieved. Two hundred and eleven (12.9%) and 279 (17%) were adjudicated to suffer MACE at six weeks and one year respectively. Only HEART ≤3 (negative predictive value MACE 99.4%, sensitivity 97.6%, %discharge 53.4) and LOD HSTnT strategy (negative predictive value MACE 99.8%, sensitivity 99.5%, %discharge 36.9) achieved pre-specified negative predictive value of >99% for MACE at six weeks. For type 1 myocardial infarction alone the negative predictive values at six weeks and one year were identical, for both HEART ≤3 and LOD HSTnT at 99.8% and 99.5% respectively. HEART ≤3 or LOD HSTnT strategy rules out short and medium term myocardial infarction with ≥99.5% certainty, and short-term MACE with >99% certainty, allowing for early discharge of 53.4% and 36.9% respectively of suspected acute coronary syndrome. Adoption of either strategy has the potential to greatly reduce Emergency Room pressures and minimise follow-up investigations. Very early presenters (<3 h), due to limited numbers, are excluded from these conclusions.