Challenges in Rotorcraft Acoustic Flight Prediction and Validation

NASA Technical Reports Server (NTRS)

Boyd, D. Douglas, Jr.

2003-01-01

Challenges associated with rotorcraft acoustic flight prediction and validation are examined. First, an outline of a state-of-the-art rotorcraft aeroacoustic prediction methodology is presented. Components including rotorcraft aeromechanics, high resolution reconstruction, and rotorcraft acoustic prediction arc discussed. Next, to illustrate challenges and issues involved, a case study is presented in which an analysis of flight data from a specific XV-15 tiltrotor acoustic flight test is discussed in detail. Issues related to validation of methodologies using flight test data are discussed. Primary flight parameters such as velocity, altitude, and attitude are discussed and compared for repeated flight conditions. Other measured steady state flight conditions are examined for consistency and steadiness. A representative example prediction is presented and suggestions are made for future research.

Numerical study of single and two interacting turbulent plumes in atmospheric cross flow

NASA Astrophysics Data System (ADS)

Mokhtarzadeh-Dehghan, M. R.; König, C. S.; Robins, A. G.

The paper presents a numerical study of two interacting full-scale dry plumes issued into neutral boundary layer cross flow. The study simulates plumes from a mechanical draught cooling tower. The plumes are placed in tandem or side-by-side. Results are first presented for plumes with a density ratio of 0.74 and plume-to-crosswind speed ratio of 2.33, for which data from a small-scale wind tunnel experiment were available and were used to assess the accuracy of the numerical results. Further results are then presented for the more physically realistic density ratio of 0.95, maintaining the same speed ratio. The sensitivity of the results with respect to three turbulence models, namely, the standard k- ɛ model, the RNG k- ɛ model and the Differential Flux Model (DFM) is presented. Comparisons are also made between the predicted rise height and the values obtained from existing integral models. The formation of two counter-rotating vortices is well predicted. The results show good agreement for the rise height predicted by different turbulence models, but the DFM predicts temperature profiles more accurately. The values of predicted rise height are also in general agreement. However, discrepancies between the present results for the rise height for single and multiple plumes and the values obtained from known analytical relations are apparent and possible reasons for these are discussed.

A Case for Transforming the Criterion of a Predictive Validity Study

ERIC Educational Resources Information Center

Patterson, Brian F.; Kobrin, Jennifer L.

2011-01-01

This study presents a case for applying a transformation (Box and Cox, 1964) of the criterion used in predictive validity studies. The goals of the transformation were to better meet the assumptions of the linear regression model and to reduce the residual variance of fitted (i.e., predicted) values. Using data for the 2008 cohort of first-time,…

State-of-the-art of high-speed propeller noise prediction - A multidisciplinary approach and comparison with measured data

NASA Technical Reports Server (NTRS)

Dunn, Mark H.; Farassat, F.

1990-01-01

The results of NASA's Propeller Test Assessment program involving extensive flight tests of a large-scale advanced propeller are presented. This has provided the opportunity to evaluate the current capability of advanced propeller noise prediction utilizing principally the exterior acoustic measurements for the prediction of exterior noise. The principal object of this study was to evaluate the state-of-the-art of noise prediction for advanced propellers utilizing the best available codes of the disciplines involved. The effects of blade deformation on the aerodynamics and noise of advanced propellers were also studied. It is concluded that blade deformation can appreciably influence propeller noise and aerodynamics, and that, in general, centrifugal and blade forces must both be included in the calculation of blade forces. It is noted that the present capability for free-field noise prediction of the first three harmonics for advanced propellers is fairly good. Detailed data and diagrams of the test results are presented.

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

ERIC Educational Resources Information Center

Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

2010-01-01

Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

Vibration Prediction Model for Floating-Slab Rail Transit Track

DOT National Transportation Integrated Search

1975-08-01

This report presents the theoretical development of a model to predict the vibration reduction by floating-slab tracks in subway tunnels. Data from a field study in New York City are also presented. The report is one of three reports dealing with noi...

Syntactic Predictability in the Recognition of Carefully and Casually Produced Speech

ERIC Educational Resources Information Center

Viebahn, Malte C.; Ernestus, Mirjam; McQueen, James M.

2015-01-01

The present study investigated whether the recognition of spoken words is influenced by how predictable they are given their syntactic context and whether listeners assign more weight to syntactic predictability when acoustic-phonetic information is less reliable. Syntactic predictability was manipulated by varying the word order of past…

A multilevel modeling approach to examining the implementation-effectiveness relationship of a behavior change intervention for health care professional trainees.

PubMed

Tomasone, Jennifer R; Sweet, Shane N; McReynolds, Stuart; Martin Ginis, Kathleen A

2017-09-01

Changing Minds, Changing Lives, a seminar-mediated behavior change intervention, aims to enhance health care professionals' (HCPs') social cognitions for discussing leisure-time physical activity (LTPA) with patients with physical disabilities. This study examines which seminar implementation variables (presenter characteristics, delivery components) predict effectiveness using multilevel modeling. HCP trainees (n = 564) attended 24 seminars and completed Theory of Planned Behavior-based measures for discussing LTPA at pre-, post-, 1-month post-, and 6-months post-seminar. Implementation variables were extracted from presenter-completed questionnaires/checklists. Seminars presented by a HCP predicted positive changes in all cognitions pre-post but negative changes in attitudes and perceived behavioral control (PBC) over follow-up (ps < .05). The number of seminars the presenter had delivered predicted negative changes in attitudes and PBC during follow-up (ps < .001). Inclusion of audiovisual components predicted positive changes in attitudes pre-post (p < .001). Presenter characteristics may be "key ingredients" to educational interventions for HCPs; however, future studies should examine additional implementation variables.

Prediction is Production: The missing link between language production and comprehension.

PubMed

Martin, Clara D; Branzi, Francesca M; Bar, Moshe

2018-01-18

Language comprehension often involves the generation of predictions. It has been hypothesized that such prediction-for-comprehension entails actual language production. Recent studies provided evidence that the production system is recruited during language comprehension, but the link between production and prediction during comprehension remains hypothetical. Here, we tested this hypothesis by comparing prediction during sentence comprehension (primary task) in participants having the production system either available or not (non-verbal versus verbal secondary task). In the primary task, sentences containing an expected or unexpected target noun-phrase were presented during electroencephalography recording. Prediction, measured as the magnitude of the N400 effect elicited by the article (expected versus unexpected), was hindered only when the production system was taxed during sentence context reading. The present study provides the first direct evidence that the availability of the speech production system is necessary for generating lexical prediction during sentence comprehension. Furthermore, these important results provide an explanation for the recruitment of language production during comprehension.

Ottawa Ankle Rules and Subjective Surgeon Perception to Evaluate Radiograph Necessity Following Foot and Ankle Sprain

PubMed Central

Pires, RES; Pereira, AA; Abreu-e-Silva, GM; Labronici, PJ; Figueiredo, LB; Godoy-Santos, AL; Kfuri, M

2014-01-01

Background: Foot and ankle injuries are frequent in emergency departments. Although only a few patients with foot and ankle sprain present fractures and the fracture patterns are almost always simple, lack of fracture diagnosis can lead to poor functional outcomes. Aim: The present study aims to evaluate the reliability of the Ottawa ankle rules and the orthopedic surgeon subjective perception to assess foot and ankle fractures after sprains. Subjects and Methods: A cross-sectional study was conducted from July 2012 to December 2012. Ethical approval was granted. Two hundred seventy-four adult patients admitted to the emergency department with foot and/or ankle sprain were evaluated by an orthopedic surgeon who completed a questionnaire prior to radiographic assessment. The Ottawa ankle rules and subjective perception of foot and/or ankle fractures were evaluated on the questionnaire. Results: Thirteen percent (36/274) patients presented fracture. Orthopedic surgeon subjective analysis showed 55.6% sensitivity, 90.1% specificity, 46.5% positive predictive value and 92.9% negative predictive value. The general orthopedic surgeon opinion accuracy was 85.4%. The Ottawa ankle rules presented 97.2% sensitivity, 7.8% specificity, 13.9% positive predictive value, 95% negative predictive value and 19.9% accuracy respectively. Weight-bearing inability was the Ottawa ankle rule item that presented the highest reliability, 69.4% sensitivity, 61.6% specificity, 63.1% accuracy, 21.9% positive predictive value and 93% negative predictive value respectively. Conclusion: The Ottawa ankle rules showed high reliability for deciding when to take radiographs in foot and/or ankle sprains. Weight-bearing inability was the most important isolated item to predict fracture presence. Orthopedic surgeon subjective analysis to predict fracture possibility showed a high specificity rate, representing a confident method to exclude unnecessary radiographic exams. PMID:24971221

"Computer as Data Gatherer" for a New Generation: Martorella's Predictions, the Past, the Present, and the Future of Technology in Social Studies

ERIC Educational Resources Information Center

Friedman, Adam

2014-01-01

In his 1997 article "Technology and the Social Studies--or: Which Way to the Sleeping Giant?" Peter Martorella made several predictions regarding technology resources in the social studies. Through a 2014 lens, Martorella's Internet seems archaic, yet two of his predictions were particularly poignant and have had a significant impact on…

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

Validity of one-repetition maximum predictive equations in men with spinal cord injury.

PubMed

Ribeiro Neto, F; Guanais, P; Dornelas, E; Coutinho, A C B; Costa, R R G

2017-10-01

Cross-sectional study. The study aimed (a) to test the cross-validation of current one-repetition maximum (1RM) predictive equations in men with spinal cord injury (SCI); (b) to compare the current 1RM predictive equations to a newly developed equation based on the 4- to 12-repetition maximum test (4-12RM). SARAH Rehabilitation Hospital Network, Brasilia, Brazil. Forty-five men aged 28.0 years with SCI between C6 and L2 causing complete motor impairment were enrolled in the study. Volunteers were tested, in a random order, in 1RM test or 4-12RM with 2-3 interval days. Multiple regression analysis was used to generate an equation for predicting 1RM. There were no significant differences between 1RM test and the current predictive equations. ICC values were significant and were classified as excellent for all current predictive equations. The predictive equation of Lombardi presented the best Bland-Altman results (0.5 kg and 12.8 kg for mean difference and interval range around the differences, respectively). The two created equation models for 1RM demonstrated the same and a high adjusted R 2 (0.971, P<0.01), but different SEE of measured 1RM (2.88 kg or 5.4% and 2.90 kg or 5.5%). All 1RM predictive equations are accurate to assess individuals with SCI at the bench press exercise. However, the predictive equation of Lombardi presented the best associated cross-validity results. A specific 1RM prediction equation was also elaborated for individuals with SCI. The created equation should be tested in order to verify whether it presents better accuracy than the current ones.

Changes in monthly unemployment rates may predict changes in the number of psychiatric presentations to emergency services in South Australia.

PubMed

Bidargaddi, Niranjan; Bastiampillai, Tarun; Schrader, Geoffrey; Adams, Robert; Piantadosi, Cynthia; Strobel, Jörg; Tucker, Graeme; Allison, Stephen

2015-07-24

To determine the extent to which variations in monthly Mental Health Emergency Department (MHED) presentations in South Australian Public Hospitals are associated with the Australian Bureau of Statistics (ABS) monthly unemployment rates. Times series modelling of relationships between monthly MHED presentations to South Australian Public Hospitals derived from the Integrated South Australian Activity Collection (ISAAC) data base and the ABS monthly unemployment rates in South Australia between January 2004-June 2011. Time series modelling using monthly unemployment rates from ABS as a predictor variable explains 69% of the variation in monthly MHED presentations across public hospitals in South Australia. Thirty-two percent of the variation in current month's male MHED presentations can be predicted by using the 2 months' prior male unemployment rate. Over 63% of the variation in monthly female MHED presentations can be predicted by either male or female prior monthly unemployment rates. The findings of this study highlight that even with the relatively favourable economic conditions, small shifts in monthly unemployment rates can predict variations in monthly MHED presentations, particularly for women. Monthly ABS unemployment rates may be a useful metric for predicting demand for emergency mental health services.

Effects of anticipated emotional category and temporal predictability on the startle reflex.

PubMed

Parisi, Elizabeth A; Hajcak, Greg; Aneziris, Eleni; Nelson, Brady D

2017-09-01

Anticipated emotional category and temporal predictability are key characteristics that have both been shown to impact psychophysiological indices of defensive motivation (e.g., the startle reflex). To date, research has primarily examined these features in isolation, and it is unclear whether they have additive or interactive effects on defensive motivation. In the present study, the startle reflex was measured in anticipation of low arousal neutral, moderate arousal pleasant, and high arousal unpleasant pictures that were presented with either predictable or unpredictable timing. Linear mixed-effects modeling was conducted to examine startle magnitude across time, and the intercept at the beginning and end of the task. Across the entire task, the anticipation of temporally unpredictable (relative to predictable) pictures and emotional (relative to neutral) pictures potentiated startle magnitude, but there was no interaction between the two features. However, examination of the intercept at the beginning of the task indicated a Predictability by Emotional Category interaction, such that temporal unpredictability enhanced startle potentiation in anticipation of unpleasant pictures only. Examination of the intercept at the end of the task indicated that the effects of predictability and emotional category on startle magnitude were largely diminished. The present study replicates previous reports demonstrating that emotional category and temporal predictability impact the startle reflex, and provides novel evidence suggesting an interactive effect on defensive motivation at the beginning of the task. This study also highlights the importance of examining the time course of the startle reflex. Copyright © 2017 Elsevier B.V. All rights reserved.

Fatigue crack growth and life prediction under mixed-mode loading

NASA Astrophysics Data System (ADS)

Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

2018-04-01

Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.

Perceived Parental Bonding, Fear of Failure and Stress during Class Presentations

ERIC Educational Resources Information Center

Sideridis, Georgios D.; Kafetsios, Konstantinos

2008-01-01

The purpose of the present studies was to test the hypothesis that students' perceptions of parental bonding may be predictive of how individuals approach achievement situations. It was hypothesized that reports of parental overprotection would be predictive of elevated fears and subsequent stress and low achievement compared to perceived parental…

1984-2008. Predictions for Higher Education. From the 25th Anniversary Colloquium. [Proceedings].

ERIC Educational Resources Information Center

Hardee, Melvene Draheim, Ed.

Predictions on higher education for 1984-2009 are presented in the proceedings of a colloquium of the Institute for Studies in Higher Education of Florida State University. Presentations were made at the colloquium by 10 graduates of the university whose current positions represent administration-management, instruction, research, and student…

Bayesian accrual prediction for interim review of clinical studies: open source R package and smartphone application.

PubMed

Jiang, Yu; Guarino, Peter; Ma, Shuangge; Simon, Steve; Mayo, Matthew S; Raghavan, Rama; Gajewski, Byron J

2016-07-22

Subject recruitment for medical research is challenging. Slow patient accrual leads to increased costs and delays in treatment advances. Researchers need reliable tools to manage and predict the accrual rate. The previously developed Bayesian method integrates researchers' experience on former trials and data from an ongoing study, providing a reliable prediction of accrual rate for clinical studies. In this paper, we present a user-friendly graphical user interface program developed in R. A closed-form solution for the total subjects that can be recruited within a fixed time is derived. We also present a built-in Android system using Java for web browsers and mobile devices. Using the accrual software, we re-evaluated the Veteran Affairs Cooperative Studies Program 558- ROBOTICS study. The application of the software in monitoring and management of recruitment is illustrated for different stages of the trial. This developed accrual software provides a more convenient platform for estimation and prediction of the accrual process.

Ultimate pier and contraction scour prediction in cohesive soils at selected bridges in Illinois

USGS Publications Warehouse

Straub, Timothy D.; Over, Thomas M.; Domanski, Marian M.

2013-01-01

The Scour Rate In COhesive Soils-Erosion Function Apparatus (SRICOS-EFA) method includes an ultimate scour prediction that is the equilibrium maximum pier and contraction scour of cohesive soils over time. The purpose of this report is to present the results of testing the ultimate pier and contraction scour methods for cohesive soils on 30 bridge sites in Illinois. Comparison of the ultimate cohesive and noncohesive methods, along with the Illinois Department of Transportation (IDOT) cohesive soil reduction-factor method and measured scour are presented. Also, results of the comparison of historic IDOT laboratory and field values of unconfined compressive strength of soils (Qu) are presented. The unconfined compressive strength is used in both ultimate cohesive and reduction-factor methods, and knowing how the values from field methods compare to the laboratory methods is critical to the informed application of the methods. On average, the non-cohesive method results predict the highest amount of scour, followed by the reduction-factor method results; and the ultimate cohesive method results predict the lowest amount of scour. The 100-year scour predicted for the ultimate cohesive, noncohesive, and reduction-factor methods for each bridge site and soil are always larger than observed scour in this study, except 12% of predicted values that are all within 0.4 ft of the observed scour. The ultimate cohesive scour prediction is smaller than the non-cohesive scour prediction method for 78% of bridge sites and soils. Seventy-six percent of the ultimate cohesive predictions show a 45% or greater reduction from the non-cohesive predictions that are over 10 ft. Comparing the ultimate cohesive and reduction-factor 100-year scour predictions methods for each bridge site and soil, the scour predicted by the ultimate cohesive scour prediction method is less than the reduction-factor 100-year scour prediction method for 51% of bridge sites and soils. Critical shear stress remains a needed parameter in the ultimate scour prediction for cohesive soils. The unconfined soil compressive strength measured by IDOT in the laboratory was found to provide a good prediction of critical shear stress, as measured by using the erosion function apparatus in a previous study. Because laboratory Qu analyses are time-consuming and expensive, the ability of field-measured Rimac data to estimate unconfined soil strength in the critical shear–soil strength relation was tested. A regression analysis was completed using a historic IDOT dataset containing 366 data pairs of laboratory Qu and field Rimac measurements from common sites with cohesive soils. The resulting equations provide a point prediction of Qu, given any Rimac value with the 90% confidence interval. The prediction equations are not significantly different from the identity Qu = Rimac. The alternative predictions of ultimate cohesive scour presented in this study assume Qu will be estimated using Rimac measurements that include computed uncertainty. In particular, the ultimate cohesive predicted scour is greater than observed scour for the entire 90% confidence interval range for predicting Qu at the bridges and soils used in this study, with the exception of the six predicted values that are all within 0.6 ft of the observed scour.

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya

PubMed Central

Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively. PMID:29664961

Perfectionistic concerns predict increases in adolescents' anxiety symptoms: a three-wave longitudinal study.

PubMed

Damian, Lavinia E; Negru-Subtirica, Oana; Stoeber, Joachim; Băban, Adriana

2017-09-01

Although perfectionism has been proposed to be a risk factor for the development of anxiety, research on perfectionism and anxiety symptoms in adolescents is scarce and inconclusive. The aim of the present study was to investigate whether the two higher-order dimensions of perfectionism - perfectionistic strivings and perfectionistic concerns - predict the development and maintenance of anxiety symptoms. An additional aim of the present study was to examine potential reciprocal effects of anxiety symptoms predicting increases in perfectionism. The study used a longitudinal design with three waves spaced 4-5 months apart. A non-clinical sample of 489 adolescents aged 12-19 years completed a paper-and-pencil questionnaire. As expected, results showed a positive effect from perfectionistic concerns to anxiety symptoms, but the effect was restricted to middle-to-late adolescents (16-19 years old): Perfectionistic concerns predicted longitudinal increases in adolescents' anxiety symptoms, whereas perfectionistic strivings did not. Furthermore, anxiety symptoms did not predict increases in perfectionism. Implications for the understanding of the relationship between perfectionism and anxiety symptoms are discussed.

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya.

PubMed

Thapa, Sunil; Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

Empirical Observations on the Sensitivity of Hot Cathode Ionization Type Vacuum Gages

NASA Technical Reports Server (NTRS)

Summers, R. L.

1969-01-01

A study of empirical methods of predicting tile relative sensitivities of hot cathode ionization gages is presented. Using previously published gage sensitivities, several rules for predicting relative sensitivity are tested. The relative sensitivity to different gases is shown to be invariant with gage type, in the linear range of gage operation. The total ionization cross section, molecular and molar polarizability, and refractive index are demonstrated to be useful parameters for predicting relative gage sensitivity. Using data from the literature, the probable error of predictions of relative gage sensitivity based on these molecular properties is found to be about 10 percent. A comprehensive table of predicted relative sensitivities, based on empirical methods, is presented.

Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

PubMed

Lopes, F B; Wu, X-L; Li, H; Xu, J; Perkins, T; Genho, J; Ferretti, R; Tait, R G; Bauck, S; Rosa, G J M

2018-02-01

Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP-LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP-LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de-regressed EBV was slightly small (i.e. 0.87%-18.75%). The present study also compared the performance of five genomic prediction models and two cross-validation methods. The five genomic models predicted EBV and de-regressed EBV of the ten traits similarly well. Of the two cross-validation methods, leave-one-out cross-validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle. © 2018 Blackwell Verlag GmbH.

Neuroanatomical correlates of time perspective: A voxel-based morphometry study.

PubMed

Chen, Zhiyi; Guo, Yiqun; Feng, Tingyong

2018-02-26

Previous studies indicated that time perspective can affect many behaviors, such as decisions, risk taking, substance abuse and health behaviors. However, very little is known about the neural substrates of time perspective (TP). To address this question, we characterized different dimensions of TP (including the Past, Present, and Future TP) using standardized Zimbardo Time Perspective Inventory (ZTPI), and quantified the gray matter volume using voxel-based morphometry (VBM) method across two independent samples. Our whole-brain analysis (sample 1, N=150) revealed Past-Negative TP was positively correlated with the GMV of a cluster in LPFC whereas Past-Positive was negatively correlated with the GMV in OFC, and Future TP was negatively correlated with GMV in mPFC. Moreover, two present scales (Present-Hedonistic and Present-Fatalistic TPs) were positively correlated with the GMV of regions in MTG and precuneus, respectively. We further examined the reliability of these correlations between multidimensional TPs and neuroanatomical structures in another independent sample (sample 2, N=58). Results verified our findings that GMV in LPFC could predict Past-Negative TP while GMV in OFC could predict Past-Positive TP, and the GMV in MTG could predict Present-Hedonistic while the GMV in presuneus could predict Present-Fatalistic, as well as the GMV in mPFC could predict Future TP. Thus, our findings suggest that the existence of selective neural basis underlying TPs, and further provide the stable biomarkers for multidimensional TPs. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic steady-state analysis of crack propagation in rubber-like solids using an extended finite element method

NASA Astrophysics Data System (ADS)

Kroon, Martin

2012-01-01

In the present study, a computational framework for studying high-speed crack growth in rubber-like solids under conditions of plane stress and steady-state is proposed. Effects of inertia, viscoelasticity and finite strains are included. The main purpose of the study is to examine the contribution of viscoelastic dissipation to the total work of fracture required to propagate a crack in a rubber-like solid. The computational framework builds upon a previous work by the present author (Kroon in Int J Fract 169:49-60, 2011). The model was fully able to predict experimental results in terms of the local surface energy at the crack tip and the total energy release rate at different crack speeds. The predicted distributions of stress and dissipation around the propagating crack tip are presented. The predicted crack tip profiles also agree qualitatively with experimental findings.

Settling for less out of fear of being single.

PubMed

Spielmann, Stephanie S; MacDonald, Geoff; Maxwell, Jessica A; Joel, Samantha; Peragine, Diana; Muise, Amy; Impett, Emily A

2013-12-01

The present research demonstrates that fear of being single predicts settling for less in romantic relationships, even accounting for constructs typically examined in relationship research such as anxious attachment. Study 1 explored the content of people's thoughts about being single. Studies 2A and 2B involved the development and validation of the Fear of Being Single Scale. Study 2C provided preliminary support for the hypothesis that fear of being single predicts settling for less in ongoing relationships, as evidenced by greater dependence in unsatisfying relationships. Study 3 replicated this effect in a longitudinal study demonstrating that fear of being single predicts lower likelihood of initiating the dissolution of a less satisfying relationship. Studies 4A and 4B explored the predictive ability of fear of being single for self-reported dating standards. Across both samples, fear of being single was unrelated to self-reported standards for a mate, with the exception of consistently higher standards for parenting. Studies 5 and 6 explored romantic interest in targets that were manipulated to vary in responsiveness and physical attractiveness. These studies found that fear of being single consistently predicted romantic interest in less responsive and less attractive dating targets. Study 7 explored fear of being single during a speed-dating event. We found that fear of being single predicted being less selective in expressing romantic interest but did not predict other daters' romantic interest. Taken together, the present research suggests that fear of being single is a meaningful predictor of settling for less in relationships. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Skipping Syntactically Illegal "the" Previews: The Role of Predictability

ERIC Educational Resources Information Center

Abbott, Matthew J.; Angele, Bernhard; Ahn, Y. Danbi; Rayner, Keith

2015-01-01

Readers tend to skip words, particularly when they are short, frequent, or predictable. Angele and Rayner (2013) recently reported that readers are often unable to detect syntactic anomalies in parafoveal vision. In the present study, we manipulated target word predictability to assess whether contextual constraint modulates…

Predicting chaos in memristive oscillator via harmonic balance method.

PubMed

Wang, Xin; Li, Chuandong; Huang, Tingwen; Duan, Shukai

2012-12-01

This paper studies the possible chaotic behaviors in a memristive oscillator with cubic nonlinearities via harmonic balance method which is also called the method of describing function. This method was proposed to detect chaos in classical Chua's circuit. We first transform the considered memristive oscillator system into Lur'e model and present the prediction of the existence of chaotic behaviors. To ensure the prediction result is correct, the distortion index is also measured. Numerical simulations are presented to show the effectiveness of theoretical results.

Robust model predictive control for satellite formation keeping with eccentricity/inclination vector separation

NASA Astrophysics Data System (ADS)

Lim, Yeerang; Jung, Youeyun; Bang, Hyochoong

2018-05-01

This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach.

Analytical prediction of digital signal crosstalk of FCC

NASA Technical Reports Server (NTRS)

Belleisle, A. P.

1972-01-01

The results are presented of study effort whose aim was the development of accurate means of analyzing and predicting signal cross-talk in multi-wire digital data cables. A complete analytical model is developed n + 1 wire systems of uniform transmission lines with arbitrary linear boundary conditions. In addition, a minimum set of parameter measurements required for the application of the model are presented. Comparisons between cross-talk predicted by this model and actual measured cross-talk are shown for a six conductor ribbon cable.

Medium-range, objective predictions of thunderstorm location and severity for aviation

NASA Technical Reports Server (NTRS)

Wilson, G. S.; Turner, R. E.

1981-01-01

This paper presents a computerized technique for medium-range (12-48h) prediction of both the location and severity of thunderstorms utilizing atmospheric predictions from the National Meteorological Center's limited-area fine-mesh model (LFM). A regional-scale analysis scheme is first used to examine the spatial and temporal distributions of forecasted variables associated with the structure and dynamics of mesoscale systems over an area of approximately 10 to the 6th sq km. The final prediction of thunderstorm location and severity is based upon an objective combination of these regionally analyzed variables. Medium-range thunderstorm predictions are presented for the late afternoon period of April 10, 1979, the day of the Wichita Falls, Texas tornado. Conventional medium-range thunderstorm forecasts, made from observed data, are presented with the case study to demonstrate the possible application of this objective technique in improving 12-48 h thunderstorm forecasts for aviation.

Impaired gas exchange: accuracy of defining characteristics in children with acute respiratory infection1

PubMed Central

Pascoal, Lívia Maia; Lopes, Marcos Venícios de Oliveira; Chaves, Daniel Bruno Resende; Beltrão, Beatriz Amorim; da Silva, Viviane Martins; Monteiro, Flávia Paula Magalhães

2015-01-01

OBJECTIVE: to analyze the accuracy of the defining characteristics of the Impaired gas exchange nursing diagnosis in children with acute respiratory infection. METHOD: open prospective cohort study conducted with 136 children monitored for a consecutive period of at least six days and not more than ten days. An instrument based on the defining characteristics of the Impaired gas exchange diagnosis and on literature addressing pulmonary assessment was used to collect data. The accuracy means of all the defining characteristics under study were computed. RESULTS: the Impaired gas exchange diagnosis was present in 42.6% of the children in the first assessment. Hypoxemia was the characteristic that presented the best measures of accuracy. Abnormal breathing presented high sensitivity, while restlessness, cyanosis, and abnormal skin color showed high specificity. All the characteristics presented negative predictive values of 70% and cyanosis stood out by its high positive predictive value. CONCLUSION: hypoxemia was the defining characteristic that presented the best predictive ability to determine Impaired gas exchange. Studies of this nature enable nurses to minimize variability in clinical situations presented by the patient and to identify more precisely the nursing diagnosis that represents the patient's true clinical condition. PMID:26155010

Studies in Bilingual Evaluation, Work Unit I: Bilingual Prediction Project. Final Report.

ERIC Educational Resources Information Center

de Porcel, Antonio; And Others

The final report of the Bilingual Prediction Project presents a review of the project from its inception in 1975 through completion in 1979. The main goal was to predict a student's academic ability in English. A prediction index was constructed in two stages. The first stage was a description of the target population and their school setting, as…

RFI simulation definition study, exhibit D

NASA Technical Reports Server (NTRS)

Braun, W. R.

1981-01-01

Comparative analyses of experimental and predicted effects of the radio frequency interference (RFI) environment on the Shuttle/TDRSS S-band links were performed. Specifications are defined ad ESTL test requirements are presented. Procedures for using the RFI test generator in the ESTL S-band link tests are presented and performance predictions for these links in the RFI environment are provided.

Computational Fluency and Strategy Choice Predict Individual and Cross-National Differences in Complex Arithmetic

ERIC Educational Resources Information Center

Vasilyeva, Marina; Laski, Elida V.; Shen, Chen

2015-01-01

The present study tested the hypothesis that children's fluency with basic number facts and knowledge of computational strategies, derived from early arithmetic experience, predicts their performance on complex arithmetic problems. First-grade students from United States and Taiwan (N = 152, mean age: 7.3 years) were presented with problems that…

Teacher' Interpersonal Self-Efficacy: Evaluation and Predictive Capacity of Teacher Burnout

ERIC Educational Resources Information Center

García-Ros, Rafael; Fuentes, María C.; Fernández, Basilio

2015-01-01

Introduction: This study analyzed the predictive capacity and incremental validity of teachers' interpersonal self-efficacy on their levels of burnout. First, it presents the validation process of a Spanish adaptation of the Teacher Interpersonal Self-Efficacy Scale--TISES--(Browers & Tomic, 1999, 2001). Second, the predictive capacity of…

Statistical Learning of Probabilistic Nonadjacent Dependencies by Multiple-Cue Integration

ERIC Educational Resources Information Center

van den Bos, Esther; Christiansen, Morten H.; Misyak, Jennifer B.

2012-01-01

Previous studies have indicated that dependencies between nonadjacent elements can be acquired by statistical learning when each element predicts only one other element (deterministic dependencies). The present study investigates statistical learning of probabilistic nonadjacent dependencies, in which each element predicts several other elements…

The left inferior parietal lobe represents stored hand-postures for object use and action prediction

PubMed Central

van Elk, Michiel

2014-01-01

Action semantics enables us to plan actions with objects and to predict others' object-directed actions as well. Previous studies have suggested that action semantics are represented in a fronto-parietal action network that has also been implicated to play a role in action observation. In the present fMRI study it was investigated how activity within this network changes as a function of the predictability of an action involving multiple objects and requiring the use of action semantics. Participants performed an action prediction task in which they were required to anticipate the use of a centrally presented object that could be moved to an associated target object (e.g., hammer—nail). The availability of actor information (i.e., presenting a hand grasping the central object) and the number of possible target objects (i.e., 0, 1, or 2 target objects) were independently manipulated, resulting in different levels of predictability. It was found that making an action prediction based on actor information resulted in an increased activation in the extrastriate body area (EBA) and the fronto-parietal action observation network (AON). Predicting actions involving a target object resulted in increased activation in the bilateral IPL and frontal motor areas. Within the AON, activity in the left inferior parietal lobe (IPL) and the left premotor cortex (PMC) increased as a function of the level of action predictability. Together these findings suggest that the left IPL represents stored hand-postures that can be used for planning object-directed actions and for predicting other's actions as well. PMID:24795681

A study of fault prediction and reliability assessment in the SEL environment

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Patnaik, Debabrata

1986-01-01

An empirical study on estimation and prediction of faults, prediction of fault detection and correction effort, and reliability assessment in the Software Engineering Laboratory environment (SEL) is presented. Fault estimation using empirical relationships and fault prediction using curve fitting method are investigated. Relationships between debugging efforts (fault detection and correction effort) in different test phases are provided, in order to make an early estimate of future debugging effort. This study concludes with the fault analysis, application of a reliability model, and analysis of a normalized metric for reliability assessment and reliability monitoring during development of software.

Passion for work and emotional exhaustion: the mediating role of rumination and recovery.

PubMed

Donahue, Eric G; Forest, Jacques; Vallerand, Robert J; Lemyre, Pierre-Nicolas; Crevier-Braud, Laurence; Bergeron, Eliane

2012-11-01

The purpose of the present research is to present a model pertaining to the mediating roles of rumination and recovery experiences in the relationship between a harmonious and an obsessive passion (Vallerand et al., 2003) for work and workers' emotional exhaustion. Two populations were measured in the present research: namely elite coaches and nurses. Study 1's model posits that obsessive passion positively predicts rumination about one's work when being physically away from work, while harmonious passion negatively predicts ruminative thoughts. In turn, rumination is expected to positively contribute to emotional exhaustion. The results of Study 1 were replicated in Study 2. In addition, in the model of Study 2, obsessive passion was expected to undermine recovery experiences, while harmonious passion was expected to predict recovery experiences. In turn, recovery experiences were expected to protect workers from emotional exhaustion. Results of both studies provided support for the proposed model. The present findings demonstrate that passion for work may lead to some adaptive and maladaptive psychological processes depending on the type of passion that is prevalent. © 2012 The Authors. Applied Psychology: Health and Well-Being © 2012 The International Association of Applied Psychology.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance.

PubMed

Eksborg, Staffan

2013-01-01

Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8-1.2.

Moral Attitudes Predict Cheating and Gamesmanship Behaviors Among Competitive Tennis Players

PubMed Central

Lucidi, Fabio; Zelli, Arnaldo; Mallia, Luca; Nicolais, Giampaolo; Lazuras, Lambros; Hagger, Martin S.

2017-01-01

Background: The present study tested Lee et al.’s (2008) model of moral attitudes and cheating behavior in sports in an Italian sample of young tennis players and extended it to predict behavior in actual match play. In the first phase of the study we proposed that moral, competence and status values would predict prosocial and antisocial moral attitudes directly, and indirectly through athletes’ goal orientations. In the second phase, we hypothesized that moral attitudes would directly predict actual cheating behavior observed during match play. Method: Adolescent competitive tennis players (N = 314, 76.75% males, M age = 14.36 years, SD = 1.50) completed measures of values, goal orientations, and moral attitudes. A sub-sample (n = 90) was observed in 45 competitive tennis matches by trained observers who recorded their cheating and gamesmanship behaviors on a validated checklist. Results: Consistent with hypotheses, athletes’ values predicted their moral attitudes through the effects of goal orientations. Anti-social attitudes directly predicted cheating behavior in actual match play providing support for a direct link between moral attitude and actual behavior. Conclusion: The present study findings support key propositions of Lee and colleagues’ model, and extended its application to competitive athletes in actual match play. PMID:28446891

The role of anti-cyclic citrullinated peptide antibodies in predicting rheumatoid arthritis.

PubMed

Rexhepi, Sylejman; Rexhepi, Mjellma; Sahatçiu-Meka, Vjollca; Tafaj, Argjend; Izairi, Remzi; Rexhepi, Blerta

2011-01-01

The study presents the results of predicting role of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis, compared to rheumatoid factor. 32 patients with rheumatoid arthritis were identified from a retrospective chart review. The results of our study show that presence of the rheumatoid factor has less diagnostic and prognostic significance than the anti-cyclic citrullinated peptide, and suggests its superiority in predicting an erosive disease course.

Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

ERIC Educational Resources Information Center

Powell, Erica Dion

2013-01-01

This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation.

PubMed

Paluch, Andrew S; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L

2015-01-28

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

NASA Astrophysics Data System (ADS)

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Predicting the Longitudinal Course of Marriages.

ERIC Educational Resources Information Center

Gottman, John M.

1991-01-01

Reviews studies which indicated physiological arousal, particularly of husband, as well as husband's stonewalling and the wife's verbal expressions of contempt, predicted longitudinal deterioration of marital satisfaction. Presents stages of disengagement and emotional withdrawal. (ABL)

NNLO QCD predictions for fully-differential top-quark pair production at the Tevatron

NASA Astrophysics Data System (ADS)

Czakon, Michal; Fiedler, Paul; Heymes, David; Mitov, Alexander

2016-05-01

We present a comprehensive study of differential distributions for Tevatron top-pair events at the level of stable top quarks. All calculations are performed in NNLO QCD with the help of a fully differential partonic Monte-Carlo and are exact at this order in perturbation theory. We present predictions for all kinematic distributions for which data exists. Particular attention is paid on the top-quark forward-backward asymmetry which we study in detail. We compare the NNLO results with existing approximate NNLO predictions as well as differential distributions computed with different parton distribution sets. Theory errors are significantly smaller than current experimental ones with overall agreement between theory and data.

Synthesis of Virtual Environments for Aircraft Community Noise Impact Studies

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Sullivan, Brenda M.

2005-01-01

A new capability has been developed for the creation of virtual environments for the study of aircraft community noise. It is applicable for use with both recorded and synthesized aircraft noise. When using synthesized noise, a three-stage process is adopted involving non-real-time prediction and synthesis stages followed by a real-time rendering stage. Included in the prediction-based source noise synthesis are temporal variations associated with changes in operational state, and low frequency fluctuations that are present under all operating conditions. Included in the rendering stage are the effects of spreading loss, absolute delay, atmospheric absorption, ground reflections, and binaural filtering. Results of prediction, synthesis and rendering stages are presented.

Reward prediction error signal enhanced by striatum-amygdala interaction explains the acceleration of probabilistic reward learning by emotion.

PubMed

Watanabe, Noriya; Sakagami, Masamichi; Haruno, Masahiko

2013-03-06

Learning does not only depend on rationality, because real-life learning cannot be isolated from emotion or social factors. Therefore, it is intriguing to determine how emotion changes learning, and to identify which neural substrates underlie this interaction. Here, we show that the task-independent presentation of an emotional face before a reward-predicting cue increases the speed of cue-reward association learning in human subjects compared with trials in which a neutral face is presented. This phenomenon was attributable to an increase in the learning rate, which regulates reward prediction errors. Parallel to these behavioral findings, functional magnetic resonance imaging demonstrated that presentation of an emotional face enhanced reward prediction error (RPE) signal in the ventral striatum. In addition, we also found a functional link between this enhanced RPE signal and increased activity in the amygdala following presentation of an emotional face. Thus, this study revealed an acceleration of cue-reward association learning by emotion, and underscored a role of striatum-amygdala interactions in the modulation of the reward prediction errors by emotion.

Experimental studies on thermodynamic effects of developed cavitation

NASA Technical Reports Server (NTRS)

Ruggeri, R. S.

1974-01-01

A method for predicting thermodynamic effects of cavitation (changes in cavity pressure relative to stream vapor pressure) is presented. The prediction method accounts for changes in liquid, liquid temperature, flow velocity, and body scale. Both theoretical and experimental studies used in formulating the method are discussed. The prediction method provided good agreement between predicted and experimental results for geometrically scaled venturis handling four different liquids of widely diverse physical properties. Use of the method requires geometric similarity of the body and cavitated region and a known reference cavity-pressure depression at one operating condition.

Predicting Student Actions in a Procedural Training Environment

ERIC Educational Resources Information Center

Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta

2017-01-01

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

Does the Social Working Environment Predict Beginning Teachers' Self-Efficacy and Feelings of Depression?

ERIC Educational Resources Information Center

Devos, Christelle; Dupriez, Vincent; Paquay, Leopold

2012-01-01

We investigate how the social working environment predicts beginning teachers' self-efficacy and feelings of depression. Two quantitative studies are presented. The results show that the goal structure of the school culture (mastery or performance orientation) predicts both outcomes. Frequent collaborative interactions with colleagues are related…

Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students

ERIC Educational Resources Information Center

Yildiz, Osman; Bal, Abdullah; Gulsecen, Sevinc

2013-01-01

It is essential to predict distance education students' year-end academic performance early during the course of the semester and to take precautions using such prediction-based information. This will, in particular, help enhance their academic performance and, therefore, improve the overall educational quality. The present study was on the…

Less than Optimal Parenting Strategies Predict Maternal Low-Level Depression beyond that of Child Transgressions

ERIC Educational Resources Information Center

Lagace-Seguin, Daniel G.; d'Entremont, Marc-Robert L.

2006-01-01

The relationship between less than optimal parenting styles, child transgressions and maternal depression were examined. It was predicted that variations in parenting styles would predict maternal depression over and above child transgressions. The present study involved approximately 68 children, their mothers and their preschool teachers.…

Evidence for an Explanation Advantage in Naive Biological Reasoning

ERIC Educational Resources Information Center

Legare, Cristine H.; Wellman, Henry M.; Gelman, Susan A.

2009-01-01

The present studies compare young children's explanations and predictions for the biological phenomenon of contamination. In Study 1, 36 preschoolers and 24 adults heard vignettes concerning contamination, and were asked either to make a prediction or to provide an explanation. Even 3-year-olds readily supplied contamination-based explanations,…

Project for Solar-Terrestrial Environment Prediction (PSTEP): Towards Predicting Next Solar Cycle

NASA Astrophysics Data System (ADS)

Imada, S.; Iijima, H.; Hotta, H.; Shiota, D.; Kanou, O.; Fujiyama, M.; Kusano, K.

2016-10-01

It is believed that the longer-term variations of the solar activity can affect the Earth's climate. Therefore, predicting the next solar cycle is crucial for the forecast of the "solar-terrestrial environment". To build prediction schemes for the activity level of the next solar cycle is a key for the long-term space weather study. Although three-years prediction can be almost achieved, the prediction of next solar cycle is very limited, so far. We are developing a five-years prediction scheme by combining the Surface Flux Transport (SFT) model and the most accurate measurements of solar magnetic fields as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction),. We estimate the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters are used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle. We also report the present status and the future perspective of our project.

Light-transmittance predictions under multiple-light-scattering conditions. I. Direct problem: hybrid-method approximation.

PubMed

Czerwiński, M; Mroczka, J; Girasole, T; Gouesbet, G; Gréhan, G

2001-03-20

Our aim is to present a method of predicting light transmittances through dense three-dimensional layered media. A hybrid method is introduced as a combination of the four-flux method with coefficients predicted from a Monte Carlo statistical model to take into account the actual three-dimensional geometry of the problem under study. We present the principles of the hybrid method, some exemplifying results of numerical simulations, and their comparison with results obtained from Bouguer-Lambert-Beer law and from Monte Carlo simulations.

Life prediction of turbine components: On-going studies at the NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Spera, D. A.; Grisaffe, S. J.

1973-01-01

An overview is presented of the many studies at NASA-Lewis that form the turbine component life prediction program. This program has three phases: (1) development of life prediction methods for major failure modes through materials studies, (2) evaluation and improvement of these methods through a variety of burner rig studies on simulated components in research engines and advanced rigs. These three phases form a cooperative, interdisciplinary program. A bibliography of Lewis publications on fatigue, oxidation and coatings, and turbine engine alloys is included.

Using remote sensing, ecological niche modeling, and Geographic Information Systems for Rift Valley fever risk assessment in the United States

NASA Astrophysics Data System (ADS)

Tedrow, Christine Atkins

The primary goal in this study was to explore remote sensing, ecological niche modeling, and Geographic Information Systems (GIS) as aids in predicting candidate Rift Valley fever (RVF) competent vector abundance and distribution in Virginia, and as means of estimating where risk of establishment in mosquitoes and risk of transmission to human populations would be greatest in Virginia. A second goal in this study was to determine whether the remotely-sensed Normalized Difference Vegetation Index (NDVI) can be used as a proxy variable of local conditions for the development of mosquitoes to predict mosquito species distribution and abundance in Virginia. As part of this study, a mosquito surveillance database was compiled to archive the historical patterns of mosquito species abundance in Virginia. In addition, linkages between mosquito density and local environmental and climatic patterns were spatially and temporally examined. The present study affirms the potential role of remote sensing imagery for species distribution prediction, and it demonstrates that ecological niche modeling is a valuable predictive tool to analyze the distributions of populations. The MaxEnt ecological niche modeling program was used to model predicted ranges for potential RVF competent vectors in Virginia. The MaxEnt model was shown to be robust, and the candidate RVF competent vector predicted distribution map is presented. The Normalized Difference Vegetation Index (NDVI) was found to be the most useful environmental-climatic variable to predict mosquito species distribution and abundance in Virginia. However, these results indicate that a more robust prediction is obtained by including other environmental-climatic factors correlated to mosquito densities (e.g., temperature, precipitation, elevation) with NDVI. The present study demonstrates that remote sensing and GIS can be used with ecological niche and risk modeling methods to estimate risk of virus establishment in mosquitoes and transmission to humans. Maps delineating the geographic areas in Virginia with highest risk for RVF establishment in mosquito populations and RVF disease transmission to human populations were generated in a GIS using human, domestic animal, and white-tailed deer population estimates and the MaxEnt potential RVF competent vector species distribution prediction. The candidate RVF competent vector predicted distribution and RVF risk maps presented in this study can help vector control agencies and public health officials focus Rift Valley fever surveillance efforts in geographic areas with large co-located populations of potential RVF competent vectors and human, domestic animal, and wildlife hosts. Keywords. Rift Valley fever, risk assessment, Ecological Niche Modeling, MaxEnt, Geographic Information System, remote sensing, Pearson's Product-Moment Correlation Coefficient, vectors, mosquito distribution, mosquito density, mosquito surveillance, United States, Virginia, domestic animals, white-tailed deer, ArcGIS

Prediction of PM2.5 along urban highway corridor under mixed traffic conditions using CALINE4 model.

PubMed

Dhyani, Rajni; Sharma, Niraj; Maity, Animesh Kumar

2017-08-01

The present study deals with spatial-temporal distribution of PM 2.5 along a highly trafficked national highway corridor (NH-2) in Delhi, India. Population residing in areas near roads and highways of high vehicular activities are exposed to high levels of PM 2.5 resulting in various health issues. The spatial extent of PM 2.5 has been assessed with the help of CALINE4 model. Various input parameters of the model were estimated and used to predict PM 2.5 concentration along the selected highway corridor. The results indicated that there are many factors involved which affects the prediction of PM 2.5 concentration by CALINE4 model. In fact, these factors either not considered by model or have little influence on model's prediction capabilities. Therefore, in the present study CALINE4 model performance was observed to be unsatisfactory for prediction of PM 2.5 concentration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction of Readiness in Kindergarten and Achievement in the First Primary Year. Study Number Two.

ERIC Educational Resources Information Center

University City School District, MO.

A 4-year United States Office of Education prekindergarten-kindergarten series of research studies has provided data useful in predicting school success. The present study compares test scores of the Complete Assessment Battery administered before the children entered kindergarten with scores of the same children on the Metropolitan Readiness…

Prediction of Emotional Understanding and Emotion Regulation Skills of 4-5 Age Group Children with Parent-Child Relations

ERIC Educational Resources Information Center

Dereli, Esra

2016-01-01

The objective of the present study is to examine whether personal attributes, family characteristics of the child and parent-child relations predict children's emotional understanding and emotion regulation skills. The study was conducted with relational screening model, one of the screening models. Study sample included 423 children between the…

Nonequilibrium Stagnation-Line Radiative Heating for Fire II

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.; Hollis, Brian R.; Sutton, Kenneth

2007-01-01

This paper presents a detailed analysis of the shock-layer radiative heating to the Fire II vehicle using a new air radiation model and a viscous shock-layer flowfield model. This new air radiation model contains the most up-to-date properties for modeling the atomic-line, atomic photoionization, molecular band, and non-Boltzmann processes. The applied viscous shock-layer flowfield analysis contains the same thermophysical properties and nonequilibrium models as the LAURA Navier-Stokes code. Radiation-flowfield coupling, or radiation cooling, is accounted for in detail in this study. It is shown to reduce the radiative heating by about 30% for the peak radiative heating points, while reducing the convective heating only slightly. A detailed review of past Fire II radiative heating studies is presented. It is observed that the scatter in the radiation predicted by these past studies is mostly a result of the different flowfield chemistry models and the treatment of the electronic state populations. The present predictions provide, on average throughout the trajectory, a better comparison with Fire II flight data than any previous study. The magnitude of the vacuum ultraviolet (VUV) contribution to the radiative flux is estimated from the calorimeter measurements. This is achieved using the radiometer measurements and the predicted convective heating. The VUV radiation predicted by the present model agrees well with the VUV contribution inferred from the Fire II calorimeter measurement, although only when radiation-flowfield coupling is accounted for. This agreement provides evidence that the present model accurately models the VUV radiation, which is shown to contribute significantly to the Fire II radiative heating.

Predicting suicide attempts with the SAD PERSONS scale: a longitudinal analysis.

PubMed

Bolton, James M; Spiwak, Rae; Sareen, Jitender

2012-06-01

The SAD PERSONS scale is a widely used risk assessment tool for suicidal behavior despite a paucity of supporting data. The objective of this study was to examine the ability of the scale in predicting suicide attempts. Participants consisted of consecutive referrals (N=4,019) over 2 years (January 1, 2009 to December 31, 2010) to psychiatric services in the emergency departments of the 2 largest tertiary care hospitals in the province of Manitoba, Canada. SAD PERSONS and Modified SAD PERSONS (MSPS) scale scores were recorded for individuals at their index and all subsequent presentations. The 2 main outcome measures in the study included current suicide attempts (at index presentation) and future suicide attempts (within the next 6 months). The ability of the scales to predict suicide attempts was evaluated with logistic regression, sensitivity and specificity analyses, and receiver operating characteristic curves. 566 people presented with suicide attempts (14.1% of the sample). Both SAD PERSONS and MSPS showed poor predictive ability for future suicide attempts. Compared to low risk scores, high risk baseline scores had low sensitivity (19.6% and 40.0%, respectively) and low positive predictive value (5.3% and 7.4%, respectively). SAD PERSONS did not predict suicide attempts better than chance (area under the curve =0.572; 95% confidence interval [CI], 0.51-0.64; P value nonsignificant). Stepwise regression identified 5 original scale items that accounted for the greatest proportion of future suicide attempt variance. High risk scores using this model had high sensitivity (93.5%) and were associated with a 5-fold higher likelihood of future suicide attempt presentation (odds ratio =5.58; 95% CI, 2.24-13.86; P<.001). In their current form, SAD PERSONS and MSPS do not accurately predict future suicide attempts. © Copyright 2012 Physicians Postgraduate Press, Inc.

Influence of multiple categories on the prediction of unknown properties

PubMed Central

Verde, Michael F.; Murphy, Gregory L.; Ross, Brian H.

2006-01-01

Knowing an item's category helps us predict its unknown properties. Previous studies suggest that when asked to evaluate the probability of an unknown property, people tend to consider only an item's most likely category, ignoring alternative categories. In the present study, property prediction took the form of either a probability rating or a speeded, binary-choice judgment. Consistent with past findings, subjects ignored alternative categories in their probability ratings. However, their binary-choice judgments were influenced by alternative categories. This novel finding suggests that the way category knowledge is used in prediction depends critically on the form of the prediction. PMID:16156183

Dread of uncertain pain: An event-related potential study

PubMed Central

Huang, Yujing; Shang, Qian; Dai, Shenyi; Ma, Qingguo

2017-01-01

Humans experience more stress about uncertain situations than certain situations. However, the neural mechanism underlying the uncertainty of a negative stimulus has not been determined. In the present study, event-related potential was recorded to examine neural responses during the dread of unpredictable pain. We used a cueing paradigm in which predictable cues were always followed by electric shocks, unpredictable cues by electric shocks at a 50/50 ratio and safe cues by no electric shock. Visual analogue scales following electric shocks were presented to quantify subjective anxiety levels. The behavioral results showed that unpredictable cues evoked high-level anxiety compared with predictable cues in both painful and unpainful stimulation conditions. More importantly, the ERPs results revealed that unpredictable cues elicited a larger P200 at parietal sites than predictable cues. In addition, unpredictable cues evoked larger P200 compared with safe cues at frontal electrodes and compared with predictable cues at parietal electrodes. In addition, larger P3b and LPP were observed during perception of safe cues compared with predictable cues at frontal and central electrodes. The similar P3b effect was also revealed in the left sites. The present study underlined that the uncertain dread of pain was associated with threat appraisal process in pain system. These findings on early event-related potentials were significant for a neural marker and development of therapeutic interventions. PMID:28832607

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes

PubMed Central

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system. PMID:28584447

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes.

PubMed

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system.

Small Area Variance Estimation for the Siuslaw NF in Oregon and Some Results

Treesearch

S. Lin; D. Boes; H.T. Schreuder

2006-01-01

The results of a small area prediction study for the Siuslaw National Forest in Oregon are presented. Predictions were made for total basal area, number of trees and mortality per ha on a 0.85 mile grid using data on a 1.7 mile grid and additional ancillary information from TM. A reliable method of estimating prediction errors for individual plot predictions called the...

COMPASS: A computational model to predict changes in MMSE scores 24-months after initial assessment of Alzheimer's disease.

PubMed

Zhu, Fan; Panwar, Bharat; Dodge, Hiroko H; Li, Hongdong; Hampstead, Benjamin M; Albin, Roger L; Paulson, Henry L; Guan, Yuanfang

2016-10-05

We present COMPASS, a COmputational Model to Predict the development of Alzheimer's diSease Spectrum, to model Alzheimer's disease (AD) progression. This was the best-performing method in recent crowdsourcing benchmark study, DREAM Alzheimer's Disease Big Data challenge to predict changes in Mini-Mental State Examination (MMSE) scores over 24-months using standardized data. In the present study, we conducted three additional analyses beyond the DREAM challenge question to improve the clinical contribution of our approach, including: (1) adding pre-validated baseline cognitive composite scores of ADNI-MEM and ADNI-EF, (2) identifying subjects with significant declines in MMSE scores, and (3) incorporating SNPs of top 10 genes connected to APOE identified from functional-relationship network. For (1) above, we significantly improved predictive accuracy, especially for the Mild Cognitive Impairment (MCI) group. For (2), we achieved an area under ROC of 0.814 in predicting significant MMSE decline: our model has 100% precision at 5% recall, and 91% accuracy at 10% recall. For (3), "genetic only" model has Pearson's correlation of 0.15 to predict progression in the MCI group. Even though addition of this limited genetic model to COMPASS did not improve prediction of progression of MCI group, the predictive ability of SNP information extended beyond well-known APOE allele.

Prediction of thermal cycling induced matrix cracking

NASA Technical Reports Server (NTRS)

Mcmanus, Hugh L.

1992-01-01

Thermal fatigue has been observed to cause matrix cracking in laminated composite materials. A method is presented to predict transverse matrix cracks in composite laminates subjected to cyclic thermal load. Shear lag stress approximations and a simple energy-based fracture criteria are used to predict crack densities as a function of temperature. Prediction of crack densities as a function of thermal cycling is accomplished by assuming that fatigue degrades the material's inherent resistance to cracking. The method is implemented as a computer program. A simple experiment provides data on progressive cracking of a laminate with decreasing temperature. Existing data on thermal fatigue is also used. Correlations of the analytical predictions to the data are very good. A parametric study using the analytical method is presented which provides insight into material behavior under cyclical thermal loads.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

PubMed Central

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes. PMID:25637996

Subliminal enhancement of predictive effects during syntactic processing in the left inferior frontal gyrus: an MEG study

PubMed Central

Iijima, Kazuki; Sakai, Kuniyoshi L.

2014-01-01

Predictive syntactic processing plays an essential role in language comprehension. In our previous study using Japanese object-verb (OV) sentences, we showed that the left inferior frontal gyrus (IFG) responses to a verb increased at 120–140 ms after the verb onset, indicating predictive effects caused by a preceding object. To further elucidate the automaticity of the predictive effects in the present magnetoencephalography study, we examined whether a subliminally presented verb (“subliminal verb”) enhanced the predictive effects on the sentence-final verb (“target verb”) unconsciously, i.e., without awareness. By presenting a subliminal verb after the object, enhanced predictive effects on the target verb would be detected in the OV sentences when the transitivity of the target verb matched with that of the subliminal verb (“congruent condition”), because the subliminal verb just after the object could determine the grammaticality of the sentence. For the OV sentences under the congruent condition, we observed significantly increased left IFG responses at 140–160 ms after the target verb onset. In contrast, responses in the precuneus and midcingulate cortex (MCC) were significantly reduced for the OV sentences under the congruent condition at 110–140 and 280–300 ms, respectively. By using partial Granger causality analyses for the OV sentences under the congruent condition, we revealed a bidirectional interaction between the left IFG and MCC at 60–160 ms, as well as a significant influence from the MCC to the precuneus. These results indicate that a top-down influence from the left IFG to the MCC, and then to the precuneus, is critical in syntactic decisions, whereas the MCC shares its task-set information with the left IFG to achieve automatic and predictive processes of syntax. PMID:25404899

Subliminal enhancement of predictive effects during syntactic processing in the left inferior frontal gyrus: an MEG study.

PubMed

Iijima, Kazuki; Sakai, Kuniyoshi L

2014-01-01

Predictive syntactic processing plays an essential role in language comprehension. In our previous study using Japanese object-verb (OV) sentences, we showed that the left inferior frontal gyrus (IFG) responses to a verb increased at 120-140 ms after the verb onset, indicating predictive effects caused by a preceding object. To further elucidate the automaticity of the predictive effects in the present magnetoencephalography study, we examined whether a subliminally presented verb ("subliminal verb") enhanced the predictive effects on the sentence-final verb ("target verb") unconsciously, i.e., without awareness. By presenting a subliminal verb after the object, enhanced predictive effects on the target verb would be detected in the OV sentences when the transitivity of the target verb matched with that of the subliminal verb ("congruent condition"), because the subliminal verb just after the object could determine the grammaticality of the sentence. For the OV sentences under the congruent condition, we observed significantly increased left IFG responses at 140-160 ms after the target verb onset. In contrast, responses in the precuneus and midcingulate cortex (MCC) were significantly reduced for the OV sentences under the congruent condition at 110-140 and 280-300 ms, respectively. By using partial Granger causality analyses for the OV sentences under the congruent condition, we revealed a bidirectional interaction between the left IFG and MCC at 60-160 ms, as well as a significant influence from the MCC to the precuneus. These results indicate that a top-down influence from the left IFG to the MCC, and then to the precuneus, is critical in syntactic decisions, whereas the MCC shares its task-set information with the left IFG to achieve automatic and predictive processes of syntax.

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.

Emerging trend prediction in biomedical literature.

PubMed

Moerchen, Fabian; Fradkin, Dmitriy; Dejori, Mathaeus; Wachmann, Bernd

2008-11-06

We present a study on how to predict new emerging trends in the biomedical domain based on textual data. We thereby propose a way of anticipating the transformation of arbitrary information into ground truth knowledge by predicting the inclusion of new terms into the MeSH ontology. We also discuss the preparation of a dataset for the evaluation of emerging trend prediction algorithms that is based on PubMed abstracts and related MeSH terms. The results suggest that early prediction of emerging trends is possible.

New formulae for estimating stature in the Balkans.

PubMed

Ross, Ann H; Konigsberg, Lyle W

2002-01-01

Recent studies of secular change and allometry have observed differential limb proportions between the sexes, among and within populations. These studies suggest that stature prediction formulae developed from American Whites may be inappropriate for European populations. The purpose of this investigation is to present more appropriate stature prediction equations for use in the Balkans to aid present-day identifications of the victims of genocide. The reference sample totals 545 white males obtained from World War II data. The Eastern European sample totals 177 males and includes both Bosnian and Croatian victims of the recent war. Mean stature for Eastern Europeans was obtained from the literature. Results show that formulae based on Trotter and Gleser systematically underestimate stature in the Balkans. Because Eastern Europeans are taller than American Whites it is appropriate to use this as an "informative prior" that can be applied to future cases. This informative prior can be used in predictive formulae, since it is probably similar to the sample from which the Balkan forensic cases were drawn. Based on Bayes' Theorem new predictive stature formulae are presented for Eastern Europeans.

Measuring pedestrian volumes and conflicts. Volume 2, Accident prediction model

DOT National Transportation Integrated Search

1987-12-01

This final report presents the findings, conclusions, and recommendations of the study conducted to model pedestrian/vehicle accidents. A group-type analysis approach for the prediction of pedestrian/vehicle accidents using pedestrian/vehicle conflic...

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.

PubMed

Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta; Watzl, Bernhard; Bub, Achim; Miller, Edgar R; Castenmiller, Jacqueline J M; Pasman, Wilrike J; van Het Hof, Karin; Chopra, Mridula; Karlsen, Anette; Dragsted, Lars O; Winkels, Renate; Itsiopoulos, Catherine; Brazionis, Laima; O'Dea, Kerin; van Loo-Bouwman, Carolien A; Naber, Ton H J; van der Voet, Hilko; Boshuizen, Hendriek C

2015-05-14

Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258.0 g, the correlation between observed and predicted intake was 0.78 and the mean difference between observed and predicted intake was - 1.7 g (limits of agreement: - 466.3, 462.8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201.1 g, the correlation was 0.65 and the mean bias was 2.4 g (limits of agreement: -368.2, 373.0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake.

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.

PubMed

Goldstein, Benjamin A; Navar, Ann Marie; Pencina, Michael J; Ioannidis, John P A

2017-01-01

Electronic health records (EHRs) are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges. We sought to evaluate the current state of EHR based risk prediction modeling through a systematic review of clinical prediction studies using EHR data. We searched PubMed for articles that reported on the use of an EHR to develop a risk prediction model from 2009 to 2014. Articles were extracted by two reviewers, and we abstracted information on study design, use of EHR data, model building, and performance from each publication and supplementary documentation. We identified 107 articles from 15 different countries. Studies were generally very large (median sample size = 26 100) and utilized a diverse array of predictors. Most used validation techniques (n = 94 of 107) and reported model coefficients for reproducibility (n = 83). However, studies did not fully leverage the breadth of EHR data, as they uncommonly used longitudinal information (n = 37) and employed relatively few predictor variables (median = 27 variables). Less than half of the studies were multicenter (n = 50) and only 26 performed validation across sites. Many studies did not fully address biases of EHR data such as missing data or loss to follow-up. Average c-statistics for different outcomes were: mortality (0.84), clinical prediction (0.83), hospitalization (0.71), and service utilization (0.71). EHR data present both opportunities and challenges for clinical risk prediction. There is room for improvement in designing such studies. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Compound Stimulus Presentation Does Not Deepen Extinction in Human Causal Learning

PubMed Central

Griffiths, Oren; Holmes, Nathan; Westbrook, R. Fred

2017-01-01

Models of associative learning have proposed that cue-outcome learning critically depends on the degree of prediction error encountered during training. Two experiments examined the role of error-driven extinction learning in a human causal learning task. Target cues underwent extinction in the presence of additional cues, which differed in the degree to which they predicted the outcome, thereby manipulating outcome expectancy and, in the absence of any change in reinforcement, prediction error. These prediction error manipulations have each been shown to modulate extinction learning in aversive conditioning studies. While both manipulations resulted in increased prediction error during training, neither enhanced extinction in the present human learning task (one manipulation resulted in less extinction at test). The results are discussed with reference to the types of associations that are regulated by prediction error, the types of error terms involved in their regulation, and how these interact with parameters involved in training. PMID:28232809

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

NASA Astrophysics Data System (ADS)

Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014 California Drought will be presented. Further Reading: Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.

Validation of CRASH Model in Prediction of 14-day Mortality and 6-month Unfavorable Outcome of Head Trauma Patients.

PubMed

Hashemi, Behrooz; Amanat, Mahnaz; Baratloo, Alireza; Forouzanfar, Mohammad Mehdi; Rahmati, Farhad; Motamedi, Maryam; Safari, Saeed

2016-11-01

To date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. External validation of these models in different populations is of great importance for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic model in prediction of 14-day mortality (14-DM) and 6-month unfavorable outcome (6-MUO) of patients with traumatic brain injury. In the present prospective diagnostic test study, calibration and discrimination of CRASH model were evaluated in head trauma patients referred to the emergency department. Variables required for calculating CRASH expected risks (ER), and observed 14-DM and 6-MUO were gathered. Then ER of 14-DM and 6-MUO were calculated. The patients were followed for 6 months and their 14-DM and 6-MUO were recorded. Finally, the correlation of CRASH ER and the observed outcome of the patients was evaluated. The data were analyzed using STATA version 11.0. In this study, 323 patients with the mean age of 34.0 ± 19.4 years were evaluated (87.3% male). Calibration of the basic and CT models in prediction of 14-day and 6-month outcome were in the desirable range (P < 0.05). Area under the curve in the basic model for prediction of 14-DM and 6-MUO were 0.92 (95% CI: 0.89-0.96) and 0.92 (95% CI: 0.90-0.95), respectively. In addition, area under the curve in the CT model for prediction of 14-DM and 6-MUO were 0.93 (95% CI: 0.91-0.97) and 0.93 (95% CI: 0.91-0.96), respectively. There was no significant difference between the discriminations of the two models in prediction of 14-DM (p = 0.11) and 6-MUO (p = 0.1). The results of the present study showed that CRASH prediction model has proper discrimination and calibration in predicting 14-DM and 6-MUO of head trauma patients. Since there was no difference between the values of the basic and CT models, using the basic model is recommended to simplify the risk calculations.

Error-related negativities elicited by monetary loss and cues that predict loss.

PubMed

Dunning, Jonathan P; Hajcak, Greg

2007-11-19

Event-related potential studies have reported error-related negativity following both error commission and feedback indicating errors or monetary loss. The present study examined whether error-related negativities could be elicited by a predictive cue presented prior to both the decision and subsequent feedback in a gambling task. Participants were presented with a cue that indicated the probability of reward on the upcoming trial (0, 50, and 100%). Results showed a negative deflection in the event-related potential in response to loss cues compared with win cues; this waveform shared a similar latency and morphology with the traditional feedback error-related negativity.

Psychopathy, IQ, and Violence in European American and African American County Jail Inmates

ERIC Educational Resources Information Center

Walsh, Zach; Swogger, Marc T.; Kosson, David S.

2004-01-01

The accuracy of the prediction of criminal violence may be improved by combining psychopathy with other variables that have been found to predict violence. Research has suggested that assessing intelligence (i.e., IQ) as well as psychopathy improves the accuracy of violence prediction. In the present study, the authors tested this hypothesis by…

Dynamic properties and damping predictions for laminated plates: High order theories - Timoshenko beam

NASA Astrophysics Data System (ADS)

Diveyev, Bohdan; Konyk, Solomija; Crocker, Malcolm J.

2018-01-01

The main aim of this study is to predict the elastic and damping properties of composite laminated plates. This problem has an exact elasticity solution for simple uniform bending and transverse loading conditions. This paper presents a new stress analysis method for the accurate determination of the detailed stress distributions in laminated plates subjected to cylindrical bending. Some approximate methods for the stress state predictions for laminated plates are presented here. The present method is adaptive and does not rely on strong assumptions about the model of the plate. The theoretical model described here incorporates deformations of each sheet of the lamina, which account for the effects of transverse shear deformation, transverse normal strain-stress and nonlinear variation of displacements with respect to the thickness coordinate. Predictions of the dynamic and damping values of laminated plates for various geometrical, mechanical and fastening properties are presented. Comparison with the Timoshenko beam theory is systematically made for analytical and approximation variants.

Understanding heat and fluid flow in linear GTA welds

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

Zacharia, T.; David, S.A.; Vitek, J.M.

1992-01-01

A transient heat flow and fluid flow model was used to predict the development of gas tungsten arc (GTA) weld pools in 1.5 mm thick AISI 304 SS. The welding parameters were chosen so as to correspond to an earlier experimental study which produced high-resolution surface temperature maps. The motivation of the present study was to verify the predictive capability of the computational model. Comparison of the numerical predictions and experimental observations indicate good agreement.

Understanding heat and fluid flow in linear GTA welds

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

Zacharia, T.; David, S.A.; Vitek, J.M.

1992-12-31

A transient heat flow and fluid flow model was used to predict the development of gas tungsten arc (GTA) weld pools in 1.5 mm thick AISI 304 SS. The welding parameters were chosen so as to correspond to an earlier experimental study which produced high-resolution surface temperature maps. The motivation of the present study was to verify the predictive capability of the computational model. Comparison of the numerical predictions and experimental observations indicate good agreement.

Prediction of tropical cyclone over North Indian Ocean using WRF model: sensitivity to scatterometer winds, ATOVS and ATMS radiances

NASA Astrophysics Data System (ADS)

Dodla, Venkata B.; Srinivas, Desamsetti; Dasari, Hari Prasad; Gubbala, Chinna Satyanarayana

2016-05-01

Tropical cyclone prediction, in terms of intensification and movement, is important for disaster management and mitigation. Hitherto, research studies were focused on this issue that lead to improvement in numerical models, initial data with data assimilation, physical parameterizations and application of ensemble prediction. Weather Research and Forecasting (WRF) model is the state-of-art model for cyclone prediction. In the present study, prediction of tropical cyclone (Phailin, 2013) that formed in the North Indian Ocean (NIO) with and without data assimilation using WRF model has been made to assess impacts of data assimilation. WRF model was designed to have nested two domains of 15 and 5 km resolutions. In the present study, numerical experiments are made without and with the assimilation of scatterometer winds, and radiances from ATOVS and ATMS. The model performance was assessed in respect to the movement and intensification of cyclone. ATOVS data assimilation experiment had produced the best prediction with least errors less than 100 km up to 60 hours and producing pre-deepening and deepening periods accurately. The Control and SCAT wind assimilation experiments have shown good track but the errors were 150-200 km and gradual deepening from the beginning itself instead of sudden deepening.

Predicting the Resiliency in Parents with Exceptional Children Based on Their Mindfulness

ERIC Educational Resources Information Center

Jabbari, Sosan; Firoozabadi, Somayeh Sadati; Rostami, Sedighe

2016-01-01

The purpose of the present study was to predict the resiliency in parents with exceptional children based on their mindfulness. This descriptive correlational study was performed on 260 parents of student (105 male and 159 female) that were selected by cluster sampling method. Family resiliency questionnaire (Sickby, 2005) and five aspect…

Mothers' Depressive Symptoms and Children's Cognitive and Social Agency: Predicting First-Grade Cognitive Functioning

ERIC Educational Resources Information Center

Yan, Ni; Dix, Theodore

2016-01-01

Using data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (N = 1,364), the present study supports an agentic perspective; it demonstrates that mothers' depressive symptoms in infancy predict children's poor first-grade cognitive functioning because depressive symptoms…

Does Acute Stress Disorder Predict Posttraumatic Stress Disorder Following Bank Robbery?

ERIC Educational Resources Information Center

Hansen, Maj; Elklit, Ask

2013-01-01

Unfortunately, the number of bank robberies is increasing and little is known about the subsequent risk of posttraumatic stress disorder (PTSD). Several studies have investigated the prediction of PTSD through the presence of acute stress disorder (ASD). However, there have only been a few studies following nonsexual assault. The present study…

Predicting Word Reading and Comprehension with Executive Function and Speed Measures across Development: A Latent Variable Analysis

ERIC Educational Resources Information Center

Christopher, Micaela E.; Miyake, Akira; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2012-01-01

The present study explored whether different executive control and speed measures (working memory, inhibition, processing speed, and naming speed) independently predict individual differences in word reading and reading comprehension. Although previous studies suggest these cognitive constructs are important for reading, the authors analyze the…

Modeling ready biodegradability of fragrance materials.

PubMed

Ceriani, Lidia; Papa, Ester; Kovarich, Simona; Boethling, Robert; Gramatica, Paola

2015-06-01

In the present study, quantitative structure activity relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, classification and regression tree (CART) and k-nearest neighbors (kNN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥80%; external ≥68%), specificity (internal ≥80%; external 73%), and overall accuracy (≥75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. © 2015 SETAC.

Stalling of Helicopter Blades

NASA Technical Reports Server (NTRS)

Gustafson, F B; Myers, G C , Jr

1946-01-01

Theoretical studies have predicted that operation of helicopter rotor beyond certain combinations of thrust, forward speed, and rotational speed might be prevented by rapidly increasing stalling of the retreating blade. The same studies also indicate that the efficiency of the rotor will increase until these limits are reached or closely approached, so that it is desirable to design helicopter rotors for operation close to the limits imposed by blade stalling. Inasmuch as the theoretical predictions of blade stalling involve numerous approximations and assumptions, an experimental investigation was needed to determine whether, in actual practice, the stall did occur and spread as predicted and to establish the amount of stalling that could be present without severe vibration or control difficulties being introduced. This report presents the results of such an investigation.

Time for prediction? The effect of presentation rate on predictive sentence comprehension during word-by-word reading

PubMed Central

Wlotko, Edward W.; Federmeier, Kara D.

2015-01-01

Predictive processing is a core component of normal language comprehension, but the brain may not engage in prediction to the same extent in all circumstances. This study investigates the effects of timing on anticipatory comprehension mechanisms. Event-related brain potentials (ERPs) were recorded while participants read two-sentence mini-scenarios previously shown to elicit prediction-related effects for implausible items that are categorically related to expected items (‘They wanted to make the hotel look more like a tropical resort. So along the driveway they planted rows of PALMS/PINES/TULIPS.’). The first sentence of every pair was presented in its entirety and was self-paced. The second sentence was presented word-by-word with a fixed stimulus onset asynchrony (SOA) of either 500 ms or 250 ms that was manipulated in a within-subjects blocked design. Amplitudes of the N400 ERP component are taken as a neural index of demands on semantic processing. At 500 ms SOA, implausible words related to predictable words elicited reduced N400 amplitudes compared to unrelated words (PINES vs. TULIPS), replicating past studies. At 250 ms SOA this prediction-related semantic facilitation was diminished. Thus, timing is a factor in determining the extent to which anticipatory mechanisms are engaged. However, we found evidence that prediction can sometimes be engaged even under speeded presentation rates. Participants who first read sentences in the 250 ms SOA block showed no effect of semantic similarity for this SOA, although these same participants showed the effect in the second block with 500 ms SOA. However, participants who first read sentences in the 500 ms SOA block continued to show the N400 semantic similarity effect in the 250 ms SOA block. These findings add to results showing that the brain flexibly allocates resources to most effectively achieve comprehension goals given the current processing environment. PMID:25987437

Measuring pedestrian volumes and conflicts. Volume 1, Pedestrian volume sampling

DOT National Transportation Integrated Search

1987-12-01

This final report presents the findings, conclusions, and recommendations of the study conducted to develop a model to predict pedestrian volumes using small sampling schemes. This research produced four pedestrian volume prediction models (i.e., 1-,...

Combination of three-dimensional ultrasound measurement of foetal adrenal gland enlargement and placental alpha microglobulin-1 for the prediction of the timing of delivery within seven days in women with threatened preterm labour and preterm labour.

PubMed

Santipap, Monchai; Phupong, Vorapong

2018-03-23

The aim of this study was to predict the timing of delivery within seven days in singleton pregnant women with threatened preterm labour and preterm labour by using a three-dimensional (3D) ultrasound measurement of foetal adrenal gland volume enlargement, a foetal zone enlargement and cervicovaginal placental alpha microglobulin-1 (PAMG-1) test. This prospective cohort study included singleton pregnant women at 22-36 +6  weeks of gestation who presented with threatened preterm labour and with preterm labour. Transabdominal 3D ultrasound measurement of the whole foetal adrenal gland and of the foetal adrenal zone were performed. Qualitative cervicovaginal PAMG-1 detection was performed at the same time. One hundred and fifty-four pregnant women were included into the study. Eighty-four pregnant women had threatened preterm labour and seventy pregnant women had preterm labour. Twenty-nine pregnant women (18%) delivered within seven days. Use of foetal adrenal gland volume enlargement, foetal zone enlargement and the PAMG-1 test in combination increased sensitivity; if one parameter was positive, the sensitivity, specificity, positive predictive value and negative predictive value were 82.8%, 27.2%, 20.9% and 87.2%, respectively, in the prediction of the timing of delivery within seven days. The combination of foetal adrenal gland enlargement and PAMG-1 increased sensitivity for the prediction of the timing of delivery within seven days in pregnant women presenting with threatened preterm labour and preterm labour. Impact Statement What is already known on this subject? An increased foetal adrenal gland volume is significantly correlated with the risk of preterm birth. What do the results of this study add? The combination of a foetal adrenal gland enlargement and a placental alpha microglobulin-1 increased sensitivity for the prediction of the timing of delivery within seven days in pregnant women presenting with threatened preterm labour and preterm labour. What are the implications of these findings for clinical practice and/or further research? The combination of a foetal adrenal gland enlargement and placental alpha microglobulin-1 may be used for the prediction of the timing of delivery within seven days in pregnant women presenting with threatened preterm labour and with preterm labour.

Are prediction models for Lynch syndrome valid for probands with endometrial cancer?

PubMed

Backes, Floor J; Hampel, Heather; Backes, Katherine A; Vaccarello, Luis; Lewandowski, George; Bell, Jeffrey A; Reid, Gary C; Copeland, Larry J; Fowler, Jeffrey M; Cohn, David E

2009-01-01

Currently, three prediction models are used to predict a patient's risk of having Lynch syndrome (LS). These models have been validated in probands with colorectal cancer (CRC), but not in probands presenting with endometrial cancer (EMC). Thus, the aim was to determine the performance of these prediction models in women with LS presenting with EMC. Probands with EMC and LS were identified. Personal and family history was entered into three prediction models, PREMM(1,2), MMRpro, and MMRpredict. Probabilities of mutations in the mismatch repair genes were recorded. Accurate prediction was defined as a model predicting at least a 5% chance of a proband carrying a mutation. From 562 patients prospectively enrolled in a clinical trial of patients with EMC, 13 (2.2%) were shown to have LS. Nine patients had a mutation in MSH6, three in MSH2, and one in MLH1. MMRpro predicted that 3 of 9 patients with an MSH6, 3 of 3 with an MSH2, and 1 of 1 patient with an MLH1 mutation could have LS. For MMRpredict, EMC coded as "proximal CRC" predicted 5 of 5, and as "distal CRC" three of five. PREMM(1,2) predicted that 4 of 4 with an MLH1 or MSH2 could have LS. Prediction of LS in probands presenting with EMC using current models for probands with CRC works reasonably well. Further studies are needed to develop models that include questions specific to patients with EMC with a greater age range, as well as placing increased emphasis on prediction of LS in probands with MSH6 mutations.

Predictability effects in auditory scene analysis: a review

PubMed Central

Bendixen, Alexandra

2014-01-01

Many sound sources emit signals in a predictable manner. The idea that predictability can be exploited to support the segregation of one source's signal emissions from the overlapping signals of other sources has been expressed for a long time. Yet experimental evidence for a strong role of predictability within auditory scene analysis (ASA) has been scarce. Recently, there has been an upsurge in experimental and theoretical work on this topic resulting from fundamental changes in our perspective on how the brain extracts predictability from series of sensory events. Based on effortless predictive processing in the auditory system, it becomes more plausible that predictability would be available as a cue for sound source decomposition. In the present contribution, empirical evidence for such a role of predictability in ASA will be reviewed. It will be shown that predictability affects ASA both when it is present in the sound source of interest (perceptual foreground) and when it is present in other sound sources that the listener wishes to ignore (perceptual background). First evidence pointing toward age-related impairments in the latter capacity will be addressed. Moreover, it will be illustrated how effects of predictability can be shown by means of objective listening tests as well as by subjective report procedures, with the latter approach typically exploiting the multi-stable nature of auditory perception. Critical aspects of study design will be delineated to ensure that predictability effects can be unambiguously interpreted. Possible mechanisms for a functional role of predictability within ASA will be discussed, and an analogy with the old-plus-new heuristic for grouping simultaneous acoustic signals will be suggested. PMID:24744695

Assessment of correlations and models for the prediction of CHF in water subcooled flow boiling

NASA Astrophysics Data System (ADS)

Celata, G. P.; Cumo, M.; Mariani, A.

1994-01-01

The present paper provides an analysis of available correlations and models for the prediction of Critical Heat Flux (CHF) in subcooled flow boiling in the range of interest of fusion reactors thermal-hydraulic conditions, i.e. high inlet liquid subcooling and velocity and small channel diameter and length. The aim of the study was to establish the limits of validity of present predictive tools (most of them were proposed with reference to light water reactors (LWR) thermal-hydraulic studies) in the above conditions. The reference dataset represents almost all available data (1865 data points) covering wide ranges of operating conditions in the frame of present interest (0.1 less than p less than 8.4 MPa; 0.3 less than D less than 25.4 mm; 0.1 less than L less than 0.61 m; 2 less than G less than 90.0 Mg/sq m/s; 90 less than delta T(sub sub,in) less than 230 K). Among the tens of predictive tools available in literature four correlations (Levy, Westinghouse, modified-Tong and Tong-75) and three models (Weisman and Ileslamlou, Lee and Mudawar and Katto) were selected. The modified-Tong correlation and the Katto model seem to be reliable predictive tools for the calculation of the CHF in subcooled flow boiling.

Anticipatory eye movements evoked after active following versus passive observation of a predictable motion stimulus.

PubMed

Burke, M R; Barnes, G R

2008-12-15

We used passive and active following of a predictable smooth pursuit stimulus in order to establish if predictive eye movement responses are equivalent under both passive and active conditions. The smooth pursuit stimulus was presented in pairs that were either 'predictable' in which both presentations were matched in timing and velocity, or 'randomized' in which each presentation in the pair was varied in both timing and velocity. A visual cue signaled the type of response required from the subject; a green cue indicated the subject should follow both the target presentations (Go-Go), a pink cue indicated that the subject should passively observe the 1st target and follow the 2nd target (NoGo-Go), and finally a green cue with a black cross revealed a randomized (Rnd) trial in which the subject should follow both presentations. The results revealed better prediction in the Go-Go trials than in the NoGo-Go trials, as indicated by higher anticipatory velocity and earlier eye movement onset (latency). We conclude that velocity and timing information stored from passive observation of a moving target is diminished when compared to active following of the target. This study has significant consequences for understanding how visuomotor memory is generated, stored and subsequently released from short-term memory.

Error-rate prediction for programmable circuits: methodology, tools and studied cases

NASA Astrophysics Data System (ADS)

Velazco, Raoul

2013-05-01

This work presents an approach to predict the error rates due to Single Event Upsets (SEU) occurring in programmable circuits as a consequence of the impact or energetic particles present in the environment the circuits operate. For a chosen application, the error-rate is predicted by combining the results obtained from radiation ground testing and the results of fault injection campaigns performed off-beam during which huge numbers of SEUs are injected during the execution of the studied application. The goal of this strategy is to obtain accurate results about different applications' error rates, without using particle accelerator facilities, thus significantly reducing the cost of the sensitivity evaluation. As a case study, this methodology was applied a complex processor, the Power PC 7448 executing a program issued from a real space application and a crypto-processor application implemented in an SRAM-based FPGA and accepted to be embedded in the payload of a scientific satellite of NASA. The accuracy of predicted error rates was confirmed by comparing, for the same circuit and application, predictions with measures issued from radiation ground testing performed at the cyclotron Cyclone cyclotron of HIF (Heavy Ion Facility) of Louvain-la-Neuve (Belgium).

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.

Mental workload prediction based on attentional resource allocation and information processing.

PubMed

Xiao, Xu; Wanyan, Xiaoru; Zhuang, Damin

2015-01-01

Mental workload is an important component in complex human-machine systems. The limited applicability of empirical workload measures produces the need for workload modeling and prediction methods. In the present study, a mental workload prediction model is built on the basis of attentional resource allocation and information processing to ensure pilots' accuracy and speed in understanding large amounts of flight information on the cockpit display interface. Validation with an empirical study of an abnormal attitude recovery task showed that this model's prediction of mental workload highly correlated with experimental results. This mental workload prediction model provides a new tool for optimizing human factors interface design and reducing human errors.

A CFD Study on the Prediction of Cyclone Collection Efficiency

NASA Astrophysics Data System (ADS)

Gimbun, Jolius; Chuah, T. G.; Choong, Thomas S. Y.; Fakhru'L-Razi, A.

2005-09-01

This work presents a Computational Fluid Dynamics calculation to predict and to evaluate the effects of temperature, operating pressure and inlet velocity on the collection efficiency of gas cyclones. The numerical solutions were carried out using spreadsheet and commercial CFD code FLUENT 6.0. This paper also reviews four empirical models for the prediction of cyclone collection efficiency, namely Lapple [1], Koch and Licht [2], Li and Wang [3], and Iozia and Leith [4]. All the predictions proved to be satisfactory when compared with the presented experimental data. The CFD simulations predict the cyclone cut-off size for all operating conditions with a deviation of 3.7% from the experimental data. Specifically, results obtained from the computer modelling exercise have demonstrated that CFD model is the best method of modelling the cyclones collection efficiency.

Predicting plantar fasciitis in runners.

PubMed

Warren, B L; Jones, C J

1987-02-01

Ninety-one runners were studied to determine whether specific variables were indicative of runners who had suffered with plantar fasciitis either presently or formerly vs runners who had never suffered with plantar fasciitis. Each runner was asked to complete a running history, was subjected to several anatomical measurements, and was asked to run on a treadmill in both a barefoot and shoe condition at a speed of 3.35 mps (8 min mile pace). Factor coefficients were used in a discriminant function analysis which revealed that, when group membership was predicted, 63% of the runners could be correctly assigned to their group. Considering that 76% of the control group was correctly predicted, it was concluded that the predictor variables were able to correctly predict membership of the control group, but not able to correctly predict the presently or formerly injured sufferers of plantar fasciitis.

Harpoon Pyrotechnic Shock Study

DTIC Science & Technology

1979-09-01

Air Systems Command, was performed from July 1973 to July 1979. In the Interest of economy and timeliness in presenting the information, the report is...Both actual test data and predicted shock levey are presented. .L{U’Shock spectra environment predictions are made for several types of explosive ...mounting structure 5 to 10 inches (127 to 254 mm) from the explosive device. Attenuation across the component mounting interface is the only loss

Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

ERIC Educational Resources Information Center

Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

2013-01-01

The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

The Interactive Role of Anxiety Sensitivity and Pubertal Status in Predicting Anxious Responding to Bodily Sensations among Adolescents

ERIC Educational Resources Information Center

Leen-Feldner, Ellen W.; Reardon, Laura E.; McKee, Laura G.; Feldner, Matthew T.; Babson, Kimberly A.; Zvolensky, Michael J. J.

2006-01-01

The present study examined the interaction between pubertal status and anxiety sensitivity (AS) in predicting anxious and fearful responding to a three-minute voluntary hyperventilation challenge among 124 (57 females) adolescents between the ages of 12 and 17 years (Mage = 15.04; SD = 1.49). As predicted, after controlling for baseline anxiety,…

A Case Study on Using Prediction Markets as a Rich Environment for Active Learning

ERIC Educational Resources Information Center

Buckley, Patrick; Garvey, John; McGrath, Fergal

2011-01-01

In this paper, prediction markets are presented as an innovative pedagogical tool which can be used to create a Rich Environment for Active Learning (REAL). Prediction markets are designed to make forecasts about specific future events by using a market mechanism to aggregate the information held by a large group of traders about that event into a…

Sensitivity and specificity of radiographic methods for predicting insertion torque of dental implants.

PubMed

Cortes, Arthur Rodriguez Gonzalez; Eimar, Hazem; Barbosa, Jorge de Sá; Costa, Claudio; Arita, Emiko Saito; Tamimi, Faleh

2015-05-01

Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aims to identify quantitative bone features influencing IT and to use these findings to develop an objective radiographic classification for predicting IT. Demographics, panoramic radiographs (taken at the beginning of dental treatment), and cone-beam computed tomographic scans (taken for implant surgical planning) of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, microcomputed tomography, and histology. Odds ratio, sensitivity, and specificity of all variables to predict high peak IT were assessed. A ridge cortical thickness >0.75 mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. Within the limitations of this study, the results suggest that it is possible to predict IT accurately based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.

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.

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network

PubMed Central

López-Caraballo, C. H.; Lazzús, J. A.; Salfate, I.; Rojas, P.; Rivera, M.; Palma-Chilla, L.

2015-01-01

An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level (σ N) from 0.01 to 0.1. PMID:26351449

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network.

PubMed

López-Caraballo, C H; Lazzús, J A; Salfate, I; Rojas, P; Rivera, M; Palma-Chilla, L

2015-01-01

An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level (σ(N)) from 0.01 to 0.1.

The Predictive Effects of Motivation toward Learning Science on TIMSS Grade 8 Students' Science Achievement: A Comparative Study between Malaysia and Singapore

ERIC Educational Resources Information Center

Lay, Yoon Fah; Chandrasegaran, A. L.

2016-01-01

TIMSS routinely presents very powerful evidence showing that students with more positive motivation toward learning science have substantially higher achievement. The results from TIMSS 2011 are consistent with previous assessments. This study explored the predictive effects of motivation toward learning science on science achievement among…

Candy consumption in childhood is not predictive of weight, adiposity measures or cardiovascular risk factors in young adults: the Bogalusa Heart Study

USDA-ARS?s Scientific Manuscript database

There are limited data available on the longitudinal relationship between candy consumption by children on weight and other cardiovascular risk factors (CVRF) in young adults. The present study investigated whether candy consumption in children was predictive of weight and CVRF in young adults. A lo...

"A Prophecy for the Arts" in Higher Education

ERIC Educational Resources Information Center

Merrion, Margaret

2009-01-01

This article presents a Delphi study that captured a myriad of predictions that represent the best thinking of a panel of creative minds, experts in a variety of arts and with many years of experience as arts leaders. Predictions provide a set of interlinked challenges and opportunities. In this study, the experts forecast changes in students that…

Home Away Home: Better Understanding of the Role of Social Support in Predicting Cross-Cultural Adjustment among International Students

ERIC Educational Resources Information Center

Baba, Yoko; Hosoda, Megumi

2014-01-01

Numerous studies have examined international students' adjustment problems, yet, these studies have not explored the mechanisms through which social support operates in the context of stressful events in predicting cross-cultural adjustment among international students. Using Barrera's (1988) models of social support, the present study…

Determinant Factors and Predictability of Occupation and Residence Patterns for Rural American High School Graduates.

ERIC Educational Resources Information Center

Holland, David Lee

The study examined the hypothesis that occupation and residence patterns present after high school graduation are generally predictable. The data come from a homogeneous, all white central Minnesota farming community with a 1961 population of 3,300. The study population is the 1961 high school graduating class, who were surveyed by questionnaire…

Could Learning Outcomes of the First Course in Accounting Predict Overall Academic Performance?

ERIC Educational Resources Information Center

Alanzi, Khalid A.; Alfraih, Mishari M.

2017-01-01

Purpose: This study aims to question whether learning outcomes of the first course in accounting could predict the overall academic performance of accounting students as measured by their graduating grade point average (GPA). Design/methodology/approach The sample of the present study was drawn from accounting students who were graduated during…

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

Surgical prediction of skeletal and soft tissue changes in treatment of Class II.

PubMed

de Lira, Ana de Lourdes Sá; de Moura, Walter Leal; Artese, Flávia; Bittencourt, Marcos Alan Vieira; Nojima, Lincoln Issamu

2013-04-01

The purpose of this study was to study the treatment outcomes and the accuracy of digital prediction and the actual postoperative outcome with Dolphin program on subjects presenting Class II malocclusions. Forty patients underwent surgical mandibular advancement (Group 1) and 40 underwent combined surgery of mandibular advancement and maxillary impaction (Group 2). The available pre surgical (t₁) and a minimum of 12 months post surgical (t₂) cephalometric radiographs were digitized. Predictive cephalograms (t₃) for both groups were traced. At all times evaluated, Group 1 displayed a shorter mandibular length and Group 2 had a longer lower face. In both groups the surgical interventions (t₂) were greater than initially predicted. There was no significant difference between groups with regards to overjet, overbite and soft tissue measurements. In both groups surgeries were more extensive than planned. Facial convexity and the distance of the lips to cranial base presented similar values between t₂ (post surgical) and t₃ (predicted). Copyright © 2012 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Personality and Defense Styles: Clinical Specificities and Predictive Factors of Alcohol Use Disorder in Women.

PubMed

Ribadier, Aurélien; Dorard, Géraldine; Varescon, Isabelle

2016-01-01

This study investigated personality traits and defense styles in order to determine clinical specificities and predictive factors of alcohol use disorders (AUDs) in women. A female sample, composed of AUD outpatients (n = 48) and a control group (n = 50), completed a sociodemographic self-report and questionnaires assessing personality traits (BFI), defense mechanisms and defense styles (DSQ-40). Comparative and correlational analyses, as well as univariate and multivariate logistic regressions, were performed. AUD women presented with higher neuroticism and lower extraversion and conscientiousness. They used less mature and more neurotic and immature defense styles than the control group. Concerning personality traits, high neuroticism and lower conscientiousness were predictive of AUD, as well as low mature, high neurotic, and immature defense styles. Including personality traits and defense styles in a logistic model, high neuroticism was the only AUD predictive factor. AUD women presented clinical specificities and predictive factors in personality traits and defense styles that must be taken into account in AUD studies. Implications for specific treatment for women are discussed.

Prediction of first episode of panic attack among white-collar workers.

PubMed

Watanabe, Akira; Nakao, Kazuhisa; Tokuyama, Madoka; Takeda, Masatoshi

2005-04-01

The purpose of the present study was to elucidate a longitudinal matrix of the etiology for first-episode panic attack among white-collar workers. A path model was designed for this purpose. A 5-year, open-cohort study was carried out in a Japanese company. To evaluate the risk factors associated with the onset of a first episode of panic attack, the odds ratios of a new episode of panic attack were calculated by logistic regression. The path model contained five predictor variables: gender difference, overprotection, neuroticism, lifetime history of major depression, and recent stressful life events. The logistic regression analysis indicated that a person with a lifetime history of major depression and recent stressful life events had a fivefold and a threefold higher risk of panic attacks at follow up, respectively. The path model for the prediction of a first episode of panic attack fitted the data well. However, this model presented low accountability for the variance in the ultimate dependent variables, the first episode of panic attack. Three predictors (neuroticism, lifetime history of major depression, and recent stressful life events) had a direct effect on the risk for a first episode of panic attack, whereas gender difference and overprotection had no direct effect. The present model could not fully predict first episodes of panic attack in white-collar workers. To make a path model for the prediction of the first episode of panic attack, other strong predictor variables, which were not surveyed in the present study, are needed. It is suggested that genetic variables are among the other strong predictor variables. A new path model containing genetic variables (e.g. family history etc.) will be needed to predict the first episode of panic attack.

Triple Test in Carcinoma Breast

PubMed Central

Sameer; Mukherjee, Arindam

2014-01-01

Introduction: The commonest clinical presentation in majority of breast pathology is a lump. A definite diagnosis of breast lump is very important for the surgeon to decide on the final course of treatment and also saves the patient from unnecessary physical, emotional and psychological trauma if there is a definite preoperative diagnosis of benign lesion. The present study was done to evaluate the effectiveness and relevance of “TRIPLE TEST”in diagnosis of carcinoma breast in rural labour class population. Materials and Methods: The present study was a prospective study conducted on patients over 35 years of age having palpable breast lumps presenting in the out patient department of general surgery, ESI Hospital Basaidarapur New Delhi, India. The duration of study was from May 2007 to June 2009 and a total of 100 cases were studied. Each patient was subjected to a detailed history, clinical breast examination ,diagnostic mammography and FNAC. In this study, the results of each modality was divided in three groups: benign, suspicious and malignant. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of each test was calculated individually and as combined. Result: Out of 100 patients enrolled in this study, 60 cases were benign and 40 cases were of malignant breast disease. The age of patients with carcinoma breast in the series varied from 35 years to 70 years. The highest incidence of malignancy noted was 30% in 41-50 years age group (4th decade) followed by 27.5% in 51-60 years age group (5th decade). The sensitivity of clinical examination was found to be 75%, specificity was 83.3%, positive predictive value (PPV) of 75% and diagnostic accuracy of 80%. The sensitivity, specificity, positive predictive value and diagnostic accuracy of mammography was calculated and was found to be 94.9% , 90% , 86% and 92% respectively. The sensitivity, specificity, positive predictive value and diagnostic accuracy of FNAC was 94.7%, 98.3%, 97.3% and 96.6% respectively. Out of 100 cases triple test was concordant (all three test either benign or malignant) in 80 cases, all the benign cases detected by triple test were benign on final biopsy i.e. 100% specificity and 100% negative predictive value. Conclusion: TTS is an accurate and least invasive diagnostic test based on which definitive treatment can be initiated. PMID:25478391

Prospective associations between friendship adjustment and social strategies: friendship as a context for building social skills.

PubMed

Glick, Gary C; Rose, Amanda J

2011-07-01

The proposal that friendships provide a context for the development of social skills is widely accepted. Yet little research exists to support this claim. In the present study, children and adolescents (N = 912) were presented with vignettes in which a friend encountered a social stressor and they could help the friend and vignettes in which they encountered a stressor and could seek help from the friend. Social strategies in response to these vignettes were assessed in the fall and spring of the school year. Different indicators of friendship adjustment had unique effects on youths' strategies in response to helping tasks. Whereas having more friends predicted decreases in avoidant or hostile strategies, having high-quality friendships predicted emotionally engaged strategies that involved talking about the problem. Moreover, whereas having more friends predicted increases in relatively disengaged strategies, like distraction and acting like the problem never happened, having high-quality friendships predicted decreases in these strategies. The present study also tested whether youths' strategies in the fall predicted changes in friendship adjustment by the spring. Only strategies which may be seen as major friendship transgressions (i.e., avoiding or blaming the friend when the friend encounters a problem) predicted changes in friendship over time. Collectively, these results provide important new information on the interplay between social competencies and friendship experiences and suggest that friendships may provide a critical venue for the development of important relationship skills. PsycINFO Database Record (c) 2011 APA, all rights reserved

Prospective Associations Between Friendship Adjustment and Social Strategies: Friendship as a Context for Building Social Skills

PubMed Central

Glick, Gary C.; Rose, Amanda J.

2012-01-01

The proposal that friendships provide a context for the development of social skills is widely accepted. Yet little research exists to support these claims. In the present study, children and adolescents (N = 912) were presented with vignettes in which their friend encountered a social stressor and they could help the friend and vignettes in which they encountered a stressor and could seek help from the friend. Social strategies in response to these vignettes were assessed in the fall and spring of the school year. Notably, different indicators of friendship adjustment had unique effects on youths’ strategies in response to helping tasks. Whereas having more friends predicted decreases in avoidant or hostile strategies, having high-quality friendships predicted emotionally-engaged strategies that involved talking about the problem. Moreover, whereas having more friends predicted increases in relatively disengaged strategies, like distraction and acting like the problem never happened, having high-quality predicted decreases in these strategies. The present study also tested whether youths’ strategies in fall predicted changes in friendship adjustment by the spring. Only strategies which may be seen as major friendship transgressions (i.e., avoiding or blaming the friend when the friend encounters a problem) predicted changes in friendship over time. Collectively, these results provide important new information on the interplay between social competencies and friendship experiences and suggest that friendships may provide a critical venue for the development of important relationship skills. PMID:21443336

EFFECTS OF WATERSHED DISTURBANCE ON SMALL STREAMS

EPA Science Inventory

This presentation presents the effects of watershed disturbance on small streams. The South Fork Broad River Watershed was studied to evaluate the use of landscape indicators to predict pollutant loading at small spatial scales and to develop indicators of pollutants. Also studie...

Design of the Next Generation Aircraft Noise Prediction Program: ANOPP2

NASA Technical Reports Server (NTRS)

Lopes, Leonard V., Dr.; Burley, Casey L.

2011-01-01

The requirements, constraints, and design of NASA's next generation Aircraft NOise Prediction Program (ANOPP2) are introduced. Similar to its predecessor (ANOPP), ANOPP2 provides the U.S. Government with an independent aircraft system noise prediction capability that can be used as a stand-alone program or within larger trade studies that include performance, emissions, and fuel burn. The ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software. The design of the system is described in terms of its functionality and capability to perform predictions accounting for distributed sources, installation effects, and propagation through a non-uniform atmosphere including refraction and the influence of terrain. The philosophy of mixed fidelity noise prediction through the use of nested Ffowcs Williams and Hawkings surfaces is presented and specific issues associated with its implementation are identified. Demonstrations for a conventional twin-aisle and an unconventional hybrid wing body aircraft configuration are presented to show the feasibility and capabilities of the system. Isolated model-scale jet noise predictions are also presented using high-fidelity and reduced order models, further demonstrating ANOPP2's ability to provide predictions for model-scale test configurations.

How accurately can we estimate energetic costs in a marine top predator, the king penguin?

PubMed

Halsey, Lewis G; Fahlman, Andreas; Handrich, Yves; Schmidt, Alexander; Woakes, Anthony J; Butler, Patrick J

2007-01-01

King penguins (Aptenodytes patagonicus) are one of the greatest consumers of marine resources. However, while their influence on the marine ecosystem is likely to be significant, only an accurate knowledge of their energy demands will indicate their true food requirements. Energy consumption has been estimated for many marine species using the heart rate-rate of oxygen consumption (f(H) - V(O2)) technique, and the technique has been applied successfully to answer eco-physiological questions. However, previous studies on the energetics of king penguins, based on developing or applying this technique, have raised a number of issues about the degree of validity of the technique for this species. These include the predictive validity of the present f(H) - V(O2) equations across different seasons and individuals and during different modes of locomotion. In many cases, these issues also apply to other species for which the f(H) - V(O2) technique has been applied. In the present study, the accuracy of three prediction equations for king penguins was investigated based on validity studies and on estimates of V(O2) from published, field f(H) data. The major conclusions from the present study are: (1) in contrast to that for walking, the f(H) - V(O2) relationship for swimming king penguins is not affected by body mass; (2) prediction equation (1), log(V(O2) = -0.279 + 1.24log(f(H) + 0.0237t - 0.0157log(f(H)t, derived in a previous study, is the most suitable equation presently available for estimating V(O2) in king penguins for all locomotory and nutritional states. A number of possible problems associated with producing an f(H) - V(O2) relationship are discussed in the present study. Finally, a statistical method to include easy-to-measure morphometric characteristics, which may improve the accuracy of f(H) - V(O2) prediction equations, is explained.

Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: the PALMS study protocol.

PubMed

Jerosch-Herold, Christina; Shepstone, Lee; Wilson, Edward C F; Dyer, Tony; Blake, Julian

2014-02-07

Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions.

Convergence of temperate and tropical stream fish assemblages

EPA Science Inventory

The hypothesis of convergence takes the deterministic view that community (or assemblage) structure can be predicted from the environment, and that the environment is expected to drive evolution in a predictable direction. Here we present results of a comparative study of freshwa...

A traveling salesman approach for predicting protein functions.

PubMed

Johnson, Olin; Liu, Jing

2006-10-12

Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm 1 on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems.

A traveling salesman approach for predicting protein functions

PubMed Central

Johnson, Olin; Liu, Jing

2006-01-01

Background Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Results Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm [1] on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Conclusion Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems. PMID:17147783

Low trait self-control predicts self-handicapping.

PubMed

Uysal, Ahmet; Knee, C Raymond

2012-02-01

Past research has shown that self-handicapping stems from uncertainty about one's ability and self-presentational concerns. The present studies suggest that low dispositional self-control is also associated with self-handicapping. In 3 studies (N = 289), the association between self-control and self-handicapping was tested. Self-control was operationalized as trait self-control, whereas self-handicapping was operationalized as trait self-handicapping in Study 1 (N = 160), self-reported self-handicapping in Study 2 (N = 74), and behavioral self-handicapping in Study 3 (N = 55). In all 3 studies, hierarchical regression analyses revealed that low self-control predicts self-handicapping, independent of self-esteem, self-doubt, social desirability, and gender. © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.

Supersonic jet noise - Its generation, prediction and effects on people and structures

NASA Technical Reports Server (NTRS)

Preisser, J. S.; Golub, R. A.; Seiner, J. M.; Powell, C. A.

1990-01-01

This paper presents the results of a study aimed at quantifying the effects of jet source noise reduction, increases in aircraft lift, and reduced aircraft thrust on the take-off noise associated with supersonic civil transports. Supersonic jet noise sources are first described, and their frequency and directivity dependence are defined. The study utilizes NASA's Aircraft Noise Prediction Program in a parametric study to weigh the relative benefits of several approaches to low noise. The baseline aircraft concept used in these predictions is the AST-205-1 powered by GE21/J11-B14A scaled engines. Noise assessment is presented in terms of effective perceived noise levels at the FAA's centerline and sideline measuring locations for current subsonic aircraft, and in terms of audiologically perceived sound of people and other indirect effects. The results show that significant noise benefit can be achieved through proper understanding and utilization of all available approaches.

Evidence for an Explanation Advantage in Naïve Biological Reasoning

PubMed Central

Legare, Cristine H.; Wellman, Henry M.; Gelman, Susan A.

2013-01-01

The present studies compare young children's explanations and predictions for the biological phenomenon of contamination. In Study 1, 36 preschoolers and 24 adults heard vignettes concerning contamination, and were asked either to make a prediction or to provide an explanation. Even 3-year-olds readily supplied contamination-based explanations, and most children mentioned an unseen mechanism (germs, contact through bodily fluids). Moreover, unlike adults who performed at ceiling across both explanation and prediction tasks, children were significantly more accurate with their explanations than their predictions. In Study 2, we varied the strength of cues regarding the desirability of the contaminated substance (N = 24 preschoolers). Although desirability affected responses, for both levels of desirability participants were significantly more accurate on explanation than prediction questions. Altogether, these studies demonstrate a significant “explanation advantage” for children's reasoning in the domain of everyday biology. PMID:18710700

Prediction of serine/threonine phosphorylation sites in bacteria proteins.

PubMed

Li, Zhengpeng; Wu, Ping; Zhao, Yuanyuan; Liu, Zexian; Zhao, Wei

2015-01-01

As a critical post-translational modification, phosphorylation plays important roles in regulating various biological processes, while recent studies suggest that phosphorylation in bacteria is also critical for functional signaling transduction. Since identification of phosphorylation substrates and sites is fundamental for understanding the phosphorylation mediated regulatory mechanism, a number of studies have been contributed to this area. Since experimental identification of phosphorylation sites is time-consuming and labor-intensive, computational predictions attract much attention for its convenience to provide helpful information. However, although there are a large number of computational studies in eukaryotes, predictions in bacteria are still rare. In this study, we present a new predictor of cPhosBac to predict phosphorylation serine/threonine in bacteria proteins. The predictor is developed with CKSAAP algorithm, which was combined with motif length selection to optimize the prediction, which achieves promising performance. The online service of cPhosBac is available at: http://netalign.ustc.edu.cn/cphosbac/ .

Climate impact on airborne particulate matter concentrations in California using seven year analysis periods

NASA Astrophysics Data System (ADS)

Mahmud, A.; Hixson, M.; Hu, J.; Zhao, Z.; Chen, S.-H.; Kleeman, M. J.

2010-11-01

The effect of global climate change on the annual average concentration of fine particulate matter (PM2.5) in California was studied using a climate-air quality modeling system composed of global through regional models. Output from the NCAR/DOE Parallel Climate Model (PCM) generated under the "business as usual" global emissions scenario was downscaled using the Weather Research and Forecasting (WRF) model followed by air quality simulations using the UCD/CIT airshed model. The system represents major atmospheric processes acting on gas and particle phase species including meteorological effects on emissions, advection, dispersion, chemical reaction rates, gas-particle conversion, and dry/wet deposition. The air quality simulations were carried out for the entire state of California with a resolution of 8-km for the years 2000-2006 (present climate with present emissions) and 2047-2053 (future climate with present emissions). Each of these 7-year analysis periods was analyzed using a total of 1008 simulated days to span a climatologically relevant time period with a practical computational burden. The 7-year windows were chosen to properly account for annual variability with the added benefit that the air quality predictions under the present climate could be compared to actual measurements. The climate-air quality modeling system successfully predicted the spatial pattern of present climate PM2.5 concentrations in California but the absolute magnitude of the annual average PM2.5 concentrations were under-predicted by ~4-39% in the major air basins. The majority of this under-prediction was caused by excess ventilation predicted by PCM-WRF that should be present to the same degree in the current and future time periods so that the net bias introduced into the comparison is minimized. Surface temperature, relative humidity (RH), rain rate, and wind speed were predicted to increase in the future climate while the ultra violet (UV) radiation was predicted to decrease in major urban areas in the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB). These changes lead to a predicted decrease in PM2.5 mass concentrations of ~0.3-0.7 μg m-3 in the southern portion of the SJV and ~0.3-1.1 μg m-3 along coastal regions of California including the heavily populated San Francisco Bay Area and the SoCAB surrounding Los Angeles. Annual average PM2.5 concentrations were predicted to increase at certain locations within the SJV and the Sacramento Valley (SV) due to the effects of climate change, but a corresponding analysis of the annual variability showed that these predictions are not statistically significant (i.e. the choice of a different 7-year period could produce a different outcome for these regions). Overall, virtually no region in California outside of coastal + central Los Angeles, and a small region around the port of Oakland in the San Francisco Bay Area experienced a statistically significant change in annual average PM2.5 concentrations due to the effects of climate change in the present~study. The present study employs the highest spatial resolution (8 km) and the longest analysis windows (7 years) of any climate-air quality analysis conducted for California to date, but the results still have some degree of uncertainty. Most significantly, GCM calculations have inherent uncertainty that is not fully represented in the current study since a single GCM was used as the starting point for all calculations. The PCM results used in the current study predicted greater wintertime increases in air temperature over the Pacific Ocean than over land, further motivating comparison to other GCM results. Ensembles of GCM results are usually employed to build confidence in climate calculations. The current results provide a first data-point for the climate-air quality analysis that simultaneously employ the fine spatial resolution and long time scales needed to capture the behavior of climate-PM2.5 interactions in California. Future downscaling studies should follow up with a full ensemble of GCMs as their starting point, and include aerosol feedback effects on local meteorology.

Defensive motivation and attention in anticipation of different types of predictable and unpredictable threat: A startle and event-related potential investigation.

PubMed

Nelson, Brady D; Hajcak, Greg

2017-08-01

Predictability is an important characteristic of threat that impacts defensive motivation and attentional engagement. Supporting research has primarily focused on actual threat (e.g., shocks), and it is unclear whether the predictability of less intense threat (e.g., unpleasant pictures) similarly affects motivation and attention. The present study utilized a within-subject design and examined defensive motivation (startle reflex and self-reported anxiety) and attention (probe N100 and P300) in anticipation of shocks and unpleasant pictures during a no, predictable, and unpredictable threat task. This study also examined the impact of predictability on the P300 to shocks and late positive potential (LPP) to unpleasant pictures. The startle reflex and self-reported anxiety were increased in anticipation of both types of threat relative to no threat. Furthermore, startle potentiation in anticipation of unpredictable threat was greater for shocks compared to unpleasant pictures, but there was no difference for predictable threat. The probe N100 was enhanced in anticipation of unpredictable threat relative to predictable threat and no threat, and the probe P300 was suppressed in anticipation of predictable and unpredictable threat relative to no threat. These effects did not differ between the shock and unpleasant picture trials. Finally, the P300 and early LPP component were increased in response to unpredictable relative to predictable shocks and unpleasant pictures, respectively. The present study suggests that the unpredictability of unpleasant pictures increases defensive motivation, but to a lesser degree relative to actual threat. Moreover, unpredictability enhances attentional engagement in anticipation of, and in reaction to, both types of threat. © 2017 Society for Psychophysiological Research.

Using Earth Observations to Understand and Predict Infectious Diseases

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Kiang, Richard

2015-01-01

This presentation discusses the processes from data collection and processing to analysis involved in unraveling patterns between disease outbreaks and the surrounding environment and meteorological conditions. We used these patterns to estimate when and where disease outbreaks will occur. As a case study, we will present our work on assessing the relationship between meteorological conditions and influenza in Central America. Our work represents the discovery, prescriptive and predictive aspects of data analytics.

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions.

PubMed

Saravanan, Konda Mani; Dunker, A Keith; Krishnaswamy, Sankaran

2017-12-27

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%-~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.

Comparison of two metrological approaches for the prediction of human haptic perception

NASA Astrophysics Data System (ADS)

Neumann, Annika; Frank, Daniel; Vondenhoff, Thomas; Schmitt, Robert

2016-06-01

Haptic perception is regarded as a key component of customer appreciation and acceptance for various products. The prediction of customers’ haptic perception is of interest both during product development and production phases. This paper presents the results of a multivariate analysis between perceived roughness and texture related surface measurements, to examine whether perceived roughness can be accurately predicted using technical measurements. Studies have shown that standardized measurement parameters, such as the roughness coefficients (e.g. Rz or Ra), do not show a one-dimensional linear correlation with the human perception (of roughness). Thus, an alternative measurement method was compared to standard measurements of roughness, in regard to its capability of predicting perceived roughness through technical measurements. To estimate perceived roughness, an experimental study was conducted in which 102 subjects evaluated four sets of 12 different geometrical surface structures regarding their relative perceived roughness. The two different metrological procedures were examined in relation to their capability to predict the perceived roughness of the subjects stated within the study. The standardized measurements of the surface roughness were made using a structured light 3D-scanner. As an alternative method, surface induced vibrations were measured by a finger-like sensor during robot-controlled traverse over a surface. The presented findings provide a better understanding of the predictability of human haptic perception using technical measurements.

Investigating the Relationships Between Antisocial Behaviors, Psychopathic Traits, and Moral Disengagement

PubMed Central

Risser, Scott; Eckert, Katy

2016-01-01

The present study investigated the relations between morally disengaged attitudes, psychopathic affective traits, and a variety of antisocial and risky behaviors in a sample of adults (N = 181). A second aim of the study was to examine the unique contributions of moral disengagement and psychopathic traits in predicting problematic behavior while the other construct is statistically controlled. Results indicated that whereas psychopathic traits and moral disengagement were both uniquely predictive of non-violent antisocial behaviors, only remorselessness was uniquely predictive of violence and only morally disengaged attitudes were uniquely predictive of academic cheating. Differing relationships also emerged by gender. PMID:26906015

Examining the Validity of Self-Report: Middle-Level Singers' Ability to Predict and Assess Their Sight-Singing Skills

ERIC Educational Resources Information Center

Darrow, Alice-Ann; Marsh, Kerry

2006-01-01

The purpose of the present study was to determine choral students' ability to predict and evaluate their sight-singing skills. Participants were asked to assign a rating based on how well they predicted they would sight-sing five musical examples. Following the singing of each example, participants were asked to evaluate their sight-singing…

Hope and hopelessness as predictors of suicide ideation in Hungarian college students.

PubMed

Chang, Edward C

2017-08-01

This study investigated whether hopelessness and dispositional hope predict suicide ideation in 395 Hungarian college students. Both hopelessness and hope uniquely predicted suicide ideation, a pattern that remained unchanged even after controlling for psychological symptoms. Moreover, a significant Hopelessness × Hope interaction predicted suicide ideation. Present findings highlight how hope buffers the association between hopelessness and suicide risk in college students.

Design prediction for long term stress rupture service of composite pressure vessels

NASA Technical Reports Server (NTRS)

Robinson, Ernest Y.

1992-01-01

Extensive stress rupture studies on glass composites and Kevlar composites were conducted by the Lawrence Radiation Laboratory beginning in the late 1960's and extending to about 8 years in some cases. Some of the data from these studies published over the years were incomplete or were tainted by spurious failures, such as grip slippage. Updated data sets were defined for both fiberglass and Kevlar composite stand test specimens. These updated data are analyzed in this report by a convenient form of the bivariate Weibull distribution, to establish a consistent set of design prediction charts that may be used as a conservative basis for predicting the stress rupture life of composite pressure vessels. The updated glass composite data exhibit an invariant Weibull modulus with lifetime. The data are analyzed in terms of homologous service load (referenced to the observed median strength). The equations relating life, homologous load, and probability are given, and corresponding design prediction charts are presented. A similar approach is taken for Kevlar composites, where the updated stand data do show a turndown tendency at long life accompanied by a corresponding change (increase) of the Weibull modulus. The turndown characteristic is not present in stress rupture test data of Kevlar pressure vessels. A modification of the stress rupture equations is presented to incorporate a latent, but limited, strength drop, and design prediction charts are presented that incorporate such behavior. The methods presented utilize Cartesian plots of the probability distributions (which are a more natural display for the design engineer), based on median normalized data that are independent of statistical parameters and are readily defined for any set of test data.

Tropical forecasting - Predictability perspective

NASA Technical Reports Server (NTRS)

Shukla, J.

1989-01-01

Results are presented of classical predictability studies and forecast experiments with observed initial conditions to show the nature of initial error growth and final error equilibration for the tropics and midlatitudes, separately. It is found that the theoretical upper limit of tropical circulation predictability is far less than for midlatitudes. The error growth for a complete general circulation model is compared to a dry version of the same model in which there is no prognostic equation for moisture, and diabatic heat sources are prescribed. It is found that the growth rate of synoptic-scale errors for the dry model is significantly smaller than for the moist model, suggesting that the interactions between dynamics and moist processes are among the important causes of atmospheric flow predictability degradation. Results are then presented of numerical experiments showing that correct specification of the slowly varying boundary condition of SST produces significant improvement in the prediction of time-averaged circulation and rainfall over the tropics.

Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically Based Pharmacokinetic Model.

PubMed

Yamazaki, Shinji; Johnson, Theodore R; Smith, Bill J

2015-10-01

An orally available multiple tyrosine kinase inhibitor, crizotinib (Xalkori), is a CYP3A substrate, moderate time-dependent inhibitor, and weak inducer. The main objectives of the present study were to: 1) develop and refine a physiologically based pharmacokinetic (PBPK) model of crizotinib on the basis of clinical single- and multiple-dose results, 2) verify the crizotinib PBPK model from crizotinib single-dose drug-drug interaction (DDI) results with multiple-dose coadministration of ketoconazole or rifampin, and 3) apply the crizotinib PBPK model to predict crizotinib multiple-dose DDI outcomes. We also focused on gaining insights into the underlying mechanisms mediating crizotinib DDIs using a dynamic PBPK model, the Simcyp population-based simulator. First, PBPK model-predicted crizotinib exposures adequately matched clinically observed results in the single- and multiple-dose studies. Second, the model-predicted crizotinib exposures sufficiently matched clinically observed results in the crizotinib single-dose DDI studies with ketoconazole or rifampin, resulting in the reasonably predicted fold-increases in crizotinib exposures. Finally, the predicted fold-increases in crizotinib exposures in the multiple-dose DDI studies were roughly comparable to those in the single-dose DDI studies, suggesting that the effects of crizotinib CYP3A time-dependent inhibition (net inhibition) on the multiple-dose DDI outcomes would be negligible. Therefore, crizotinib dose-adjustment in the multiple-dose DDI studies could be made on the basis of currently available single-dose results. Overall, we believe that the crizotinib PBPK model developed, refined, and verified in the present study would adequately predict crizotinib oral exposures in other clinical studies, such as DDIs with weak/moderate CYP3A inhibitors/inducers and drug-disease interactions in patients with hepatic or renal impairment. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Communication Efficacy and Couples’ Cancer Management: Applying a Dyadic Appraisal Model

PubMed Central

Magsamen-Conrad, Kate; Checton, Maria G.; Venetis, Maria K.; Greene, Kathryn

2014-01-01

The purpose of the present study was to apply Berg and Upchurch’s (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients’ confidence in their ability to talk about the cancer predicted their own cancer management. Partners’ confidence predicted their own and the patient’s ability to cope with cancer, which then predicted patients’ perceptions of their general health. Implications and future research are discussed. PMID:25983382

Communication Efficacy and Couples' Cancer Management: Applying a Dyadic Appraisal Model.

PubMed

Magsamen-Conrad, Kate; Checton, Maria G; Venetis, Maria K; Greene, Kathryn

2015-06-01

The purpose of the present study was to apply Berg and Upchurch's (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients' confidence in their ability to talk about the cancer predicted their own cancer management. Partners' confidence predicted their own and the patient's ability to cope with cancer, which then predicted patients' perceptions of their general health. Implications and future research are discussed.

Drug-therapy networks and the prediction of novel drug targets

PubMed Central

Spiro, Zoltan; Kovacs, Istvan A; Csermely, Peter

2008-01-01

A recent study in BMC Pharmacology presents a network of drugs and the therapies in which they are used. Network approaches open new ways of predicting novel drug targets and overcoming the cellular robustness that can prevent drugs from working. PMID:18710588

Effects of subordinate feedback to the supervisor and participation in decision-making in the prediction of organizational support.

DOT National Transportation Integrated Search

1992-03-01

The present study tested the hypothesis that participation in decision-making (PDM) and perceived effectiveness of subordinate feedback to the supervisor would contribute unique variance in the prediction of perceptions of organizational support. In ...

Predicting School Performance with the Early Screening Inventory.

ERIC Educational Resources Information Center

Meisels, Samuel J.; And Others

1984-01-01

Proposes criteria for defining and selecting preschool developmental screening instruments and describes the Early Screening Inventory (ESI), a developmental screening instrument designed to satisfy these criteria. Presents results of several studies demonstrating that the ESI predicts school performance with moderate to excellent accuracy through…

Development of hybrid method for the prediction of underwater propeller noise

NASA Astrophysics Data System (ADS)

Seol, Hanshin; Suh, Jung-Chun; Lee, Soogab

2005-11-01

Noise reduction and control is an important problem in the performance of underwater acoustic systems and in the habitability of the passenger ship for crew and passenger. Furthermore, sound generated by a propeller is critical in underwater detection and it is often related to the survivability of the vessel especially for military purpose. This paper presents a numerical study on the non-cavitating and blade sheet cavitation noises of the underwater propeller. A brief summary of numerical method with verification and results are presented. The noise is predicted using time-domain acoustic analogy. The flow field is analyzed with potential-based panel method, and then the time-dependent pressure and sheet cavity volume data are used as the input for Ffowcs Williams-Hawkings formulation to predict the far-field acoustics. Noise characteristics are presented according to noise sources and conditions. Through this study, the dominant noise source of the underwater propeller is analyzed, which will provide a basis for proper noise control strategies.

Probabilistic forecasting for extreme NO2 pollution episodes.

PubMed

Aznarte, José L

2017-10-01

In this study, we investigate the convenience of quantile regression to predict extreme concentrations of NO 2 . Contrarily to the usual point-forecasting, where a single value is forecast for each horizon, probabilistic forecasting through quantile regression allows for the prediction of the full probability distribution, which in turn allows to build models specifically fit for the tails of this distribution. Using data from the city of Madrid, including NO 2 concentrations as well as meteorological measures, we build models that predict extreme NO 2 concentrations, outperforming point-forecasting alternatives, and we prove that the predictions are accurate, reliable and sharp. Besides, we study the relative importance of the independent variables involved, and show how the important variables for the median quantile are different than those important for the upper quantiles. Furthermore, we present a method to compute the probability of exceedance of thresholds, which is a simple and comprehensible manner to present probabilistic forecasts maximizing their usefulness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictive factor and antihypertensive usage of tyrosine kinase inhibitor-induced hypertension in kidney cancer patients

PubMed Central

IZUMI, KOUJI; ITAI, SHINGO; TAKAHASHI, YOSHIKO; MAOLAKE, AERKEN; NAMIKI, MIKIO

2014-01-01

Hypertension (HT) is the common adverse event associated with vascular endothelial growth factor receptor-tyrosine kinase inhibitors (VEGFR-TKI). The present study was performed to identify the predictive factors of TKI-induced HT and to determine the classes of antihypertensive agents (AHTA) that demonstrate optimal efficacy against this type of HT. The charts of 50 cases of patients that had received VEGFR-TKI treatment were retrospectively examined. The association between patient background and TKI-induced HT, and the effect of administering AHTA were analyzed. High systolic blood pressure at baseline was identified to be a predictive factor for HT. In addition, there was no difference observed between calcium channel blockers (CCBs) and angiotensin receptor II blockers (ARBs) as first-line AHTA for the control of HT. The findings of the present study may aid with predicting the onset of TKI-induced HT, as well as for its management via the primary use of either CCBs or ARBs. PMID:24959266

Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

NASA Astrophysics Data System (ADS)

Narayanareddy, V. V.; Chandrasekhar, N.; Vasudevan, M.; Muthukumaran, S.; Vasantharaja, P.

2016-02-01

In the present study, artificial neural network modeling has been employed for predicting welding-induced angular distortions in autogenous butt-welded 304L stainless steel plates. The input data for the neural network have been obtained from a series of three-dimensional finite element simulations of TIG welding for a wide range of plate dimensions. Thermo-elasto-plastic analysis was carried out for 304L stainless steel plates during autogenous TIG welding employing double ellipsoidal heat source. The simulated thermal cycles were validated by measuring thermal cycles using thermocouples at predetermined positions, and the simulated distortion values were validated by measuring distortion using vertical height gauge for three cases. There was a good agreement between the model predictions and the measured values. Then, a multilayer feed-forward back propagation neural network has been developed using the numerically simulated data. Artificial neural network model developed in the present study predicted the angular distortion accurately.

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

ERIC Educational Resources Information Center

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2011-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

Daddy's Little Girl Goes to College: An Investigation of Females' Perceived Closeness with Fathers and Later Risky Behaviors

ERIC Educational Resources Information Center

Rostad, Whitney L.; Silverman, Paul; McDonald, Molly K.

2014-01-01

Objective: The present study investigated the extent to which father-daughter relationships predicted risk-taking in a sample of female college students. Specifically, this study examined whether female adolescents' models of father psychological presence predicted substance use and sexual risk-taking, over and above impulsivity, depression,…

Using Neural Network and Logistic Regression Analysis to Predict Prospective Mathematics Teachers' Academic Success upon Entering Graduate Education

ERIC Educational Resources Information Center

Bahadir, Elif

2016-01-01

The ability to predict the success of students when they enter a graduate program is critical for educational institutions because it allows them to develop strategic programs that will help improve students' performances during their stay at an institution. In this study, we present the results of an experimental comparison study of Logistic…

The Role of Socio-Cognitive Variables in Predicting Learning Satisfaction in Smart Schools

ERIC Educational Resources Information Center

Firoozi, Mohammad Reza; Kazemi, Ali; Jokar, Maryam

2017-01-01

The present study aimed to investigate the role of Socio-Cognitive variables in predicting learning satisfaction in Smart Schools. The population was all the primary school students studying in smart schools in the city of Shiraz in the school year 2014-2015. The sample, randomly chosen through multi-stage cluster sampling, was 383 primary school…

Predicting Computer Science Ph.D. Completion: A Case Study

ERIC Educational Resources Information Center

Cox, G. W.; Hughes, W. E., Jr.; Etzkorn, L. H.; Weisskopf, M. E.

2009-01-01

This paper presents the results of an analysis of indicators that can be used to predict whether a student will succeed in a Computer Science Ph.D. program. The analysis was conducted by studying the records of 75 students who have been in the Computer Science Ph.D. program of the University of Alabama in Huntsville. Seventy-seven variables were…

Temporal prediction restores the evaluative processing of delayed action feedback: an electrophysiological study.

PubMed

Kimura, Kenta; Kimura, Motohiro

2016-09-28

The evaluative processing of the valence of action feedback is reflected by an event-related brain potential component called feedback-related negativity (FRN) or reward positivity (RewP). Recent studies have shown that FRN/RewP is markedly reduced when the action-feedback interval is long (e.g. 6000 ms), indicating that an increase in the action-feedback interval can undermine the evaluative processing of the valence of action feedback. The aim of the present study was to investigate whether or not such undermined evaluative processing of delayed action feedback could be restored by improving the accuracy of the prediction in terms of the timing of action feedback. With a typical gambling task in which the participant chose one of two cards and received an action feedback indicating monetary gain or loss, the present study showed that FRN/RewP was significantly elicited even when the action-feedback interval was 6000 ms, when an auditory stimulus sequence was additionally presented during the action-feedback interval as a temporal cue. This result suggests that the undermined evaluative processing of delayed action feedback can be restored by increasing the accuracy of the prediction on the timing of the action feedback.

Predictive and postdictive mechanisms jointly contribute to visual awareness.

PubMed

Soga, Ryosuke; Akaishi, Rei; Sakai, Katsuyuki

2009-09-01

One of the fundamental issues in visual awareness is how we are able to perceive the scene in front of our eyes on time despite the delay in processing visual information. The prediction theory postulates that our visual system predicts the future to compensate for such delays. On the other hand, the postdiction theory postulates that our visual awareness is inevitably a delayed product. In the present study we used flash-lag paradigms in motion and color domains and examined how the perception of visual information at the time of flash is influenced by prior and subsequent visual events. We found that both types of event additively influence the perception of the present visual image, suggesting that our visual awareness results from joint contribution of predictive and postdictive mechanisms.

Validation of CRASH Model in Prediction of 14-day Mortality and 6-month Unfavorable Outcome of Head Trauma Patients

PubMed Central

Hashemi, Behrooz; Amanat, Mahnaz; Baratloo, Alireza; Forouzanfar, Mohammad Mehdi; Rahmati, Farhad; Motamedi, Maryam; Safari, Saeed

2016-01-01

Introduction: To date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. External validation of these models in different populations is of great importance for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic model in prediction of 14-day mortality (14-DM) and 6-month unfavorable outcome (6-MUO) of patients with traumatic brain injury. Methods: In the present prospective diagnostic test study, calibration and discrimination of CRASH model were evaluated in head trauma patients referred to the emergency department. Variables required for calculating CRASH expected risks (ER), and observed 14-DM and 6-MUO were gathered. Then ER of 14-DM and 6-MUO were calculated. The patients were followed for 6 months and their 14-DM and 6-MUO were recorded. Finally, the correlation of CRASH ER and the observed outcome of the patients was evaluated. The data were analyzed using STATA version 11.0. Results: In this study, 323 patients with the mean age of 34.0 ± 19.4 years were evaluated (87.3% male). Calibration of the basic and CT models in prediction of 14-day and 6-month outcome were in the desirable range (P < 0.05). Area under the curve in the basic model for prediction of 14-DM and 6-MUO were 0.92 (95% CI: 0.89-0.96) and 0.92 (95% CI: 0.90-0.95), respectively. In addition, area under the curve in the CT model for prediction of 14-DM and 6-MUO were 0.93 (95% CI: 0.91-0.97) and 0.93 (95% CI: 0.91-0.96), respectively. There was no significant difference between the discriminations of the two models in prediction of 14-DM (p = 0.11) and 6-MUO (p = 0.1). Conclusion: The results of the present study showed that CRASH prediction model has proper discrimination and calibration in predicting 14-DM and 6-MUO of head trauma patients. Since there was no difference between the values of the basic and CT models, using the basic model is recommended to simplify the risk calculations. PMID:27800540

Predictive value of cervical length in women with twin pregnancy presenting with threatened preterm labor.

PubMed

Melamed, N; Hiersch, L; Gabbay-Benziv, R; Bardin, R; Meizner, I; Wiznitzer, A; Yogev, Y

2015-07-01

To assess the accuracy and determine the optimal threshold of sonographic cervical length (CL) for the prediction of preterm delivery (PTD) in women with twin pregnancies presenting with threatened preterm labor (PTL). This was a retrospective study of women with twin pregnancies who presented with threatened PTL and underwent sonographic measurement of CL in a tertiary center. The accuracy of CL in predicting PTD in women with twin pregnancies was compared with that in a control group of women with singleton pregnancies. Overall, 218 women with a twin pregnancy and 1077 women with a singleton pregnancy, who presented with PTL, were included in the study. The performance of CL as a predictive test for PTD was similar in twins and singletons, as reflected by the similar correlation between CL and the examination-to-delivery interval (r, 0.30 vs 0.29; P = 0.9), the similar association of CL with risk of PTD, and the similar areas under the receiver-operating characteristics curves for differing delivery outcomes (range, 0.653-0.724 vs 0.620-0.682, respectively; P = 0.3). The optimal threshold of CL for any given target sensitivity or specificity was lower in twin than in singleton pregnancies. However, in order to achieve a negative predictive value of 95%, a higher threshold (28-30 mm) should be used in twin pregnancies. Using this twin-specific CL threshold, women with twins who present with PTL are more likely to have a positive CL test, and therefore to require subsequent interventions, than are women with singleton pregnancies with PTL (55% vs 4.2%, respectively). In women with PTL, the performance of CL as a test for the prediction of PTD is similar in twin and singleton pregnancies. However, the optimal threshold of CL for the prediction of PTD appears to be higher in twin pregnancies, mainly owing to the higher baseline risk for PTD in these pregnancies. Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.

The role of cervical length in women with threatened preterm labor: is it a valid predictor at any gestational age?

PubMed

Hiersch, Liran; Yogev, Yariv; Domniz, Noam; Meizner, Israel; Bardin, Ron; Melamed, Nir

2014-11-01

To determine whether the predictive accuracy of sonographic cervical length (CL) for preterm delivery (PTD) in women with threatened preterm labor (PTL) is related to gestational age (GA) at presentation. A retrospective cohort study of all women with singleton pregnancies who presented with PTL at less than 34 + 0 weeks and underwent sonographic measurement of CL in a tertiary medical center between 2007 and 2012. The predictive accuracy of CL for PTD was stratified by GA at presentation. Overall, 1077 women who presented with PTL have had sonographic measurement of CL and met the study inclusion criteria. Of those, 223 (20.7%) presented at 24 + 0-26 + 6 weeks (group 1), 274 (25.4%) at 27 + 0-29 + 6 weeks (group 2), 283 (26.3%) at 30 + 0-31 + 6 weeks (group 3), and 297 (27.6%) at 32 + 0-33 + 6 weeks (group 4). The overall performance CL as a predictive test for PTD was similar in the 4 GA groups, as reflected by the similar degree of correlation between CL with the examination to delivery interval (r = 0.27, r = 0.26, r = 0.28, and r = 0.29, respectively, P = .8), the similar area under the receiver-operator characteristic curve (0.641-0.690, 0.631-0.698, 0.643-0.654, and 0.678-0.698, respectively, P = .7), and a similar decrease in the risk of PTD of 5-10% for each additional millimeter of CL. The optimal cutoff of CL, however, was affected by GA at presentation, so that a higher cutoff of CL was needed to achieve a target negative predictive value for delivery within 14 days from presentation for women who presented later in pregnancy. The optimal thresholds to maximize the negative predictive value for delivery within 14 days were 36 mm, 32.5 mm, 24 mm and 20.5 mm for women who presented at 32 + 0 to 33 + 6 weeks, 30 + 0 to 31 + 6 weeks, 27 + 0 to 29 + 6 weeks and 24 + 0 to 26 + 6, respectively. CL has modest predictive accuracy in women with threatened PTL, regardless of GA at presentation. However, the optimal cutoff of CL for the purpose of clinical decision making in women with PTL needs to be adjusted based on GA at presentation. Copyright © 2014 Elsevier Inc. All rights reserved.

The stratosphere: Present and future

NASA Technical Reports Server (NTRS)

Hudson, R. D. (Editor); Reed, E. I. (Editor)

1979-01-01

The present status of stratospheric science is discussed. The three basic elements of stratospheric science-laboratory measurements, atmospheric observations, and theoretical studies are presented along with an attempt to predict, with reasonable confidence, the effect on ozone of particular anthropogenic sources of pollution.

Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

PubMed

Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

2014-12-01

Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement.

PubMed

Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E

2017-01-01

The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students ( N = 597) vs. second-year students ( N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students.

Adaptive Neuro-Fuzzy Inference system analysis on adsorption studies of Reactive Red 198 from aqueous solution by SBA-15/CTAB composite

NASA Astrophysics Data System (ADS)

Aghajani, Khadijeh; Tayebi, Habib-Allah

2017-01-01

In this study, the Mesoporous material SBA-15 were synthesized and then, the surface was modified by the surfactant Cetyltrimethylammoniumbromide (CTAB). Finally, the obtained adsorbent was used in order to remove Reactive Red 198 (RR 198) from aqueous solution. Transmission electron microscope (TEM), Fourier transform infra-red spectroscopy (FTIR), Thermogravimetric analysis (TGA), X-ray diffraction (XRD), and BET were utilized for the purpose of examining the structural characteristics of obtained adsorbent. Parameters affecting the removal of RR 198 such as pH, the amount of adsorbent, and contact time were investigated at various temperatures and were also optimized. The obtained optimized condition is as follows: pH = 2, time = 60 min and adsorbent dose = 1 g/l. Moreover, a predictive model based on ANFIS for predicting the adsorption amount according to the input variables is presented. The presented model can be used for predicting the adsorption rate based on the input variables include temperature, pH, time, dosage, concentration. The error between actual and approximated output confirm the high accuracy of the proposed model in the prediction process. This fact results in cost reduction because prediction can be done without resorting to costly experimental efforts. SBA-15, CTAB, Reactive Red 198, adsorption study, Adaptive Neuro-Fuzzy Inference systems (ANFIS).

Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows.

PubMed

McParland, S; Lewis, E; Kennedy, E; Moore, S G; McCarthy, B; O'Donovan, M; Butler, S T; Pryce, J E; Berry, D P

2014-09-01

Interest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (REX) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (REX=0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (REX=0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predicting MCAT Examination Scores.

ERIC Educational Resources Information Center

Dawson-Saunders, Beth; And Others

Acceptable performance on the Medical College Admissions Test (MCAT) is necessary for acceptance into medical school; therefore, students planning a career in medicine and their advisors would benefit by having information useful in predicting performance on this examination. The present study examined the validity of the ACT Assessment as such a…

Energy prediction using spatiotemporal pattern networks

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

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

PubMed

Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

2011-06-01

Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

The Role of Multimodel Combination in Improving Streamflow Prediction

NASA Astrophysics Data System (ADS)

Arumugam, S.; Li, W.

2008-12-01

Model errors are the inevitable part in any prediction exercise. One approach that is currently gaining attention to reduce model errors is by optimally combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictability. In this study, we present a new approach to combine multiple hydrological models by evaluating their predictability contingent on the predictor state. We combine two hydrological models, 'abcd' model and Variable Infiltration Capacity (VIC) model, with each model's parameter being estimated by two different objective functions to develop multimodel streamflow predictions. The performance of multimodel predictions is compared with individual model predictions using correlation, root mean square error and Nash-Sutcliffe coefficient. To quantify precisely under what conditions the multimodel predictions result in improved predictions, we evaluate the proposed algorithm by testing it against streamflow generated from a known model ('abcd' model or VIC model) with errors being homoscedastic or heteroscedastic. Results from the study show that streamflow simulated from individual models performed better than multimodels under almost no model error. Under increased model error, the multimodel consistently performed better than the single model prediction in terms of all performance measures. The study also evaluates the proposed algorithm for streamflow predictions in two humid river basins from NC as well as in two arid basins from Arizona. Through detailed validation in these four sites, the study shows that multimodel approach better predicts the observed streamflow in comparison to the single model predictions.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-01

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation.

PubMed

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-14

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

PubMed

Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-03-14

Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A hierarchical anatomical classification schema for prediction of phenotypic side effects

PubMed Central

Kanji, Rakesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708

A hierarchical anatomical classification schema for prediction of phenotypic side effects.

PubMed

Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.

Performance study of the application of Artificial Neural Networks to the completion and prediction of data retrieved by underwater sensors.

PubMed

Baladrón, Carlos; Aguiar, Javier M; Calavia, Lorena; Carro, Belén; Sánchez-Esguevillas, Antonio; Hernández, Luis

2012-01-01

This paper presents a proposal for an Artificial Neural Network (ANN)-based architecture for completion and prediction of data retrieved by underwater sensors. Due to the specific conditions under which these sensors operate, it is not uncommon for them to fail, and maintenance operations are difficult and costly. Therefore, completion and prediction of the missing data can greatly improve the quality of the underwater datasets. A performance study using real data is presented to validate the approach, concluding that the proposed architecture is able to provide very low errors. The numbers show as well that the solution is especially suitable for cases where large portions of data are missing, while in situations where the missing values are isolated the improvement over other simple interpolation methods is limited.

A Self-determination Theory approach to the study of body image concerns, self-presentation and self-perceptions in a sample of aerobic instructors.

PubMed

Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos

2007-03-01

This study examined motivational predictors of body image concerns, self-presentation and self-perceptions using Self-determination Theory as a guiding framework. Aerobic instructors (N = 149) completed questionnaires measuring general need satisfaction, exercise motivational regulations, body image concerns, social physique anxiety and self-perceptions. Introjected regulation predicted all outcome variables in the expected direction. Intrinsic motivation positively predicted physical self-worth. Further, autonomy need satisfaction negatively predicted body image concerns. Finally, differences existed in need satisfaction, introjected regulation, self-perceptions and social physique anxiety between those at risk of developing eating disorders and those not at risk. The results underline the importance of overall and exercise-specific feelings of self-determination in dealing with body image concerns and low self-perceptions of aerobics instructors.

Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

PubMed

Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Ogunseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

2017-09-01

Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in a more cost-effective manner than traditional approaches. The present article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents 4 recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA, adopting a stepwise process to employing predictive toxicology in AA beginning with prioritization of chemicals of concern, leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting transdisciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. Integr Environ Assess Manag 2017;13:915-925. © 2017 SETAC. © 2017 SETAC.

A New Approach to Predict user Mobility Using Semantic Analysis and Machine Learning.

PubMed

Fernandes, Roshan; D'Souza G L, Rio

2017-10-19

Mobility prediction is a technique in which the future location of a user is identified in a given network. Mobility prediction provides solutions to many day-to-day life problems. It helps in seamless handovers in wireless networks to provide better location based services and to recalculate paths in Mobile Ad hoc Networks (MANET). In the present study, a framework is presented which predicts user mobility in presence and absence of mobility history. Naïve Bayesian classification algorithm and Markov Model are used to predict user future location when user mobility history is available. An attempt is made to predict user future location by using Short Message Service (SMS) and instantaneous Geological coordinates in the absence of mobility patterns. The proposed technique compares the performance metrics with commonly used Markov Chain model. From the experimental results it is evident that the techniques used in this work gives better results when considering both spatial and temporal information. The proposed method predicts user's future location in the absence of mobility history quite fairly. The proposed work is applied to predict the mobility of medical rescue vehicles and social security systems.

Expression, purification and epitope analysis of Pla a 2 allergen from Platanus acerifolia pollen.

PubMed

Wang, De-Wang; Ni, Wei-Wei; Zhou, Yan-Jun; Huang, Wen; Cao, Meng-Da; Meng, Ling; Wei, Ji-Fu

2018-01-01

Platanus acerifolia is one of the major sources of outdoor allergens to humans, and can induce allergic asthma, rhinitis, dermatitis and other allergic diseases. Pla a 2 is a polygalacturonase and represents the major allergen identified in P. acerifolia pollen. The aim of the present study was to express and purify Pla a 2, and to predict B and T cell epitopes of Pla a 2. The gene encoding Pla a 2 was cloned into the pET28a vector and subsequently transfected into ArcticExpress™ (DE3) Escherichia coli cells; purified Pla a 2 was analyzed by western blot analysis. The results of the present study revealed that the Pla a 2 allergen has the ability to bind immunoglobulin E within the sera of patients allergic to P. acerifolia pollen. In addition, the B cell epitopes of Pla a 2 were predicted using the DNAStar Protean system, Bioinformatics Predicted Antigenic Peptides and BepiPred 1.0 software; T cell epitopes were predicted using NetMHCIIpan ‑3.0 and ‑2.2. In total, eight B cell epitopes (15‑24, 60‑66, 78‑86, 109‑124, 232‑240, 260‑269, 298‑306 and 315‑322) and five T cell epitopes (62‑67, 86‑91, 125‑132, 217‑222 and 343‑350) were predicted in the present study. These findings may be used to improve allergen immunotherapies and reduce the frequency of pollen‑associated allergic reactions.

The 2 × 2 Standpoints Model of Achievement Goals

PubMed Central

Korn, Rachel M.; Elliot, Andrew J.

2016-01-01

In the present research, we proposed and tested a 2 × 2 standpoints model of achievement goals grounded in the development-demonstration and approach-avoidance distinctions. Three empirical studies are presented. Study 1 provided evidence supporting the structure and psychometric properties of a newly developed measure of the goals of the 2 × 2 standpoints model. Study 2 documented the predictive utility of these goal constructs for intrinsic motivation: development-approach and development-avoidance goals were positive predictors, and demonstration-avoidance goals were a negative predictor of intrinsic motivation. Study 3 documented the predictive utility of these goal constructs for performance attainment: Demonstration-approach goals were a positive predictor and demonstration-avoidance goals were a negative predictor of exam performance. The conceptual and empirical contributions of the present research were discussed within the broader context of existing achievement goal theory and research. PMID:27242641

Contextual match and cue-independence of retrieval-induced forgetting: Testing the prediction of the model by Norman, Newman, and Detre (2007).

PubMed

Hanczakowski, Maciej; Mazzoni, Giuliana

2013-05-01

Retrieval-induced forgetting (RIF) is the finding of impaired memory performance for information stored in long-term memory due to retrieval of a related set of information. This phenomenon is often assigned to operations of a specialized mechanism recruited to resolve interference during retrieval by deactivating competing memory representations. This inhibitory account is supported by, among others, findings showing that RIF occurs with independent cues not used during retrieval practice. However, these findings are not always consistent. Recently, Norman, Newman, and Detre (2007) have proposed a model that aims at resolving discrepancies concerning cue-independence of RIF. The model predicts that RIF should be present with independent cues when episodic associations are created between independent cues and their targets in the same episodic context that is later used to cue memory during retrieval practice. In the present study we aimed to test this prediction. We associated studied items with semantically unrelated words during the main study phase of the retrieval practice paradigm, and we tested memory with both cues used during retrieval practice (Experiment 2) and episodic associates serving as independent cues (Experiments 3a and 3b). Although RIF was present when the same cues were used during retrieval practice and a final test, contrary to the prediction formulated by Norman et al., RIF failed to emerge when episodic associates were employed as independent cues.

Air pollution exposure prediction approaches used in air pollution epidemiology studies.

PubMed

Özkaynak, Halûk; Baxter, Lisa K; Dionisio, Kathie L; Burke, Janet

2013-01-01

Epidemiological studies of the health effects of outdoor air pollution have traditionally relied upon surrogates of personal exposures, most commonly ambient concentration measurements from central-site monitors. However, this approach may introduce exposure prediction errors and misclassification of exposures for pollutants that are spatially heterogeneous, such as those associated with traffic emissions (e.g., carbon monoxide, elemental carbon, nitrogen oxides, and particulate matter). We review alternative air quality and human exposure metrics applied in recent air pollution health effect studies discussed during the International Society of Exposure Science 2011 conference in Baltimore, MD. Symposium presenters considered various alternative exposure metrics, including: central site or interpolated monitoring data, regional pollution levels predicted using the national scale Community Multiscale Air Quality model or from measurements combined with local-scale (AERMOD) air quality models, hybrid models that include satellite data, statistically blended modeling and measurement data, concentrations adjusted by home infiltration rates, and population-based human exposure model (Stochastic Human Exposure and Dose Simulation, and Air Pollutants Exposure models) predictions. These alternative exposure metrics were applied in epidemiological applications to health outcomes, including daily mortality and respiratory hospital admissions, daily hospital emergency department visits, daily myocardial infarctions, and daily adverse birth outcomes. This paper summarizes the research projects presented during the symposium, with full details of the work presented in individual papers in this journal issue.

Building protein-protein interaction networks for Leishmania species through protein structural information.

PubMed

Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

2018-03-06

Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

PubMed

Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo

2014-01-01

Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.

Socioeconomic Status, Parent Report of Children's Early Language Skills, and Late Literacy Skills: A Long Term Follow-Up Study among Chinese Children

ERIC Educational Resources Information Center

Pan, Jinger; Kong, Yan; Song, Shuang; McBride, Catherine; Liu, Hongyun; Shu, Hua

2017-01-01

Previous research on the longitudinal prediction of literacy development has focused mainly on the relationship between early cognitive/language skills and late literacy skills. The present study aimed to test the reliability of a number of measures reported by parents as compared to measuring cognitive and language skills in predicting subsequent…

Application of a functional mathematical index (FMI) for predicting effects of the composition of jujube fruit on nutritional quality and health

USDA-ARS?s Scientific Manuscript database

In the present study, we extend the concept of a Functional Mathematical Index (FMI) for the assessment and prediction of food quality and safety of jujube fruit, a medicinal food widely consumed in Asian countries. In this study the index has been applied to one field-grown jujube fruit harvested a...

Model for Predicting Passage of Invasive Fish Species Through Culverts

NASA Astrophysics Data System (ADS)

Neary, V.

2010-12-01

Conservation efforts to promote or inhibit fish passage include the application of simple fish passage models to determine whether an open channel flow allows passage of a given fish species. Derivations of simple fish passage models for uniform and nonuniform flow conditions are presented. For uniform flow conditions, a model equation is developed that predicts the mean-current velocity threshold in a fishway, or velocity barrier, which causes exhaustion at a given maximum distance of ascent. The derivation of a simple expression for this exhaustion-threshold (ET) passage model is presented using kinematic principles coupled with fatigue curves for threatened and endangered fish species. Mean current velocities at or above the threshold predict failure to pass. Mean current velocities below the threshold predict successful passage. The model is therefore intuitive and easily applied to predict passage or exclusion. The ET model’s simplicity comes with limitations, however, including its application only to uniform flow, which is rarely found in the field. This limitation is addressed by deriving a model that accounts for nonuniform conditions, including backwater profiles and drawdown curves. Comparison of these models with experimental data from volitional swimming studies of fish indicates reasonable performance, but limitations are still present due to the difficulty in predicting fish behavior and passage strategies that can vary among individuals and different fish species.

Aerodynamic Performance Predictions of Single and Twin Jet Afterbodies

NASA Technical Reports Server (NTRS)

Carlson, John R.; Pao, S. Paul; Abdol-Hamid, Khaled S.; Jones, William T.

1995-01-01

The multiblock three-dimensional Navier-Stokes method PAB3D was utilized by the Component Integration Branch (formerly Propulsion Aerodynamics Branch) at the NASA-Langley Research Center in an international study sponsored by AGARD Working Group #17 for the assessment of the state-of-the-art of propulsion-airframe integration testing techniques and CFD prediction technologies. Three test geometries from ONERA involving fundamental flow physics and four geometries from NASA-LaRC involving realistic flow interactions of wing, body, tail, and jet plumes were chosen by the Working Group. An overview of results on four (1 ONERA and 3 LaRC) of the seven test cases is presented. External static pressures, integrated pressure drag and total drag were calculated for the Langley test cases and jet plume velocity profiles and turbulent viscous stresses were calculated for the ONERA test case. Only selected data from these calculations are presented in this paper. The complete data sets calculated by the participants will be presented in an AGARD summary report. Predicted surface static pressures compared favorably with experimental data for the Langley geometries. Predicted afterbody drag compared well with experiment. Predicted nozzle drag was typically low due to over-compression of the flow near the trailing edge. Total drag was typically high. Predicted jet plume quantities on the ONERA case compared generally well with data.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

PubMed

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Bilingual Control: Sequential Memory in Language Switching

ERIC Educational Resources Information Center

Declerck, Mathieu; Philipp, Andrea M.; Koch, Iring

2013-01-01

To investigate bilingual language control, prior language switching studies presented visual objects, which had to be named in different languages, typically indicated by a visual cue. The present study examined language switching of predictable responses by introducing a novel sequence-based language switching paradigm. In 4 experiments,…

Development of a prediction tool for patients presenting with acute cough in primary care: a prognostic study spanning six European countries.

PubMed

Bruyndonckx, Robin; Hens, Niel; Verheij, Theo Jm; Aerts, Marc; Ieven, Margareta; Butler, Christopher C; Little, Paul; Goossens, Herman; Coenen, Samuel

2018-05-01

Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <45 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <85 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68). The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results. © British Journal of General Practice 2018.

Prediction of Daily Flow Duration Curves and Streamflow for Ungauged Catchments Using Regional Flow Duration Curves

EPA Science Inventory

This study presents a method to predict flow duration curves (FDCs) and streamflow for ungauged catchments in the Mid-Atlantic Region, USA. We selected 29 catchments from the Appalachian Plateau, Ridge and Valley, and Piedmont physiographic provinces to develop and test the propo...

The Rangeland Hydrology and Erosion Model: A dynamic approach for predicting soil loss on rangelands

USDA-ARS?s Scientific Manuscript database

In this study we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed agains...

Improving Outcomes for Workers with Mental Retardation

ERIC Educational Resources Information Center

Fornes, Sandra; Rocco, Tonette S.; Rosenberg, Howard

2008-01-01

This research presents an analysis of factors predicting job retention, job satisfaction, and job performance of workers with mental retardation. The findings highlight self-determination as a critical skill in predicting the three important employee outcomes. The study examined a hypothesized job retention model and the outcome of the three…

Predicting Reasoning from Memory

ERIC Educational Resources Information Center

Heit, Evan; Hayes, Brett K.

2011-01-01

In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the…

Perceived Marginalization and the Prediction of Romantic Relationship Stability

ERIC Educational Resources Information Center

Lehmiller, Justin J.; Agnew, Christopher R.

2007-01-01

The present research examined how perceived marginalization of one's romantic relationship is associated with level of future commitment to and stability of that involvement. Results from a 7-month longitudinal study of romantically involved individuals (N = 215) revealed that perceived social network marginalization at Time 1 predicted breakup…

Examining Factors Predicting Students' Digital Competence

ERIC Educational Resources Information Center

Hatlevik, Ove Edvard; Guðmundsdóttir, Gréta Björk; Loi, Massimo

2015-01-01

The purpose of this study was to examine factors predicting lower secondary school students' digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what…

Eyetracking Reveals Multiple-Category Use in Induction

ERIC Educational Resources Information Center

Chen, Stephanie Y.; Ross, Brian H.; Murphy, Gregory L.

2016-01-01

Category information is used to predict properties of new category members. When categorization is uncertain, people often rely on only one, most likely category to make predictions. Yet studies of perception and action often conclude that people combine multiple sources of information near-optimally. We present a perception-action analog of…

Dangerous Mindsets: How Beliefs about Intelligence Predict Motivational Change

ERIC Educational Resources Information Center

Haimovitz, Kyla; Wormington, Stephanie V.; Corpus, Jennifer Henderlong

2011-01-01

The present study examined how beliefs about intelligence, as mediated by ability-validation goals, predicted whether students lost or maintained levels of intrinsic motivation over the course of a single academic year. 978 third- through eighth-grade students were surveyed in the fall about their theories concerning the malleability of…

Longitudinal Associations between Parental Rejection and Bullying/Victimization

ERIC Educational Resources Information Center

Stavrinides, Panayiotis; Tantaros, Spyridon; Georgiou, Stelios; Tricha, Loukia

2018-01-01

The present study investigated the direction of the relationship between parental rejection and children's engagement in bullying and victimization. Using a cross-lagged design, we examined whether (a) bullying and victimization predict an increase in parental rejection six months later, (b) parental rejection predicts an increase in bullying and…

Prediction and Stability of Mathematics Skill and Difficulty

ERIC Educational Resources Information Center

Martin, Rebecca B.; Cirino, Paul T.; Barnes, Marcia A.; Ewing-Cobbs, Linda; Fuchs, Lynn S.; Stuebing, Karla K.; Fletcher, Jack M.

2013-01-01

The present study evaluated the stability of math learning difficulties over a 2-year period and investigated several factors that might influence this stability (categorical vs. continuous change, liberal vs. conservative cut point, broad vs. specific math assessment); the prediction of math performance over time and by performance level was also…

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

Predicting agricultural impacts of large-scale drought: 2012 and the case for better modeling

USDA-ARS?s Scientific Manuscript database

We present an example of a simulation-based forecast for the 2012 U.S. maize growing season produced as part of a high-resolution, multi-scale, predictive mechanistic modeling study designed for decision support, risk management, and counterfactual analysis. The simulations undertaken for this analy...

Prediction of mechanical property loss in polyamide during immersion in sea water

NASA Astrophysics Data System (ADS)

Le Gac, Pierre Yves; Arhant, Mael; Le Gall, Maelenn; Burtin, Christian; Davies, Peter

2016-05-01

It is well known that the water absorption in polyamide leads to a large reduction in the mechanical properties of the polymer, which is induced by the plasticization of the amorphous phase. However, predicting such a loss in a marine environment is not straightforward, especially when thick samples are considered. This study presents a modeling study of the water absorption in polyamide 6 based on the free volume theory. Using this modeling coupled with a description of the stress yield changes with Tg, it is possible to predict the long term behavior of thick samples when immersed in sea water. Reliability of the prediction is checked by a comparison with experimental results.

Children's construction task performance and spatial ability: controlling task complexity and predicting mathematics performance.

PubMed

Richardson, Miles; Hunt, Thomas E; Richardson, Cassandra

2014-12-01

This paper presents a methodology to control construction task complexity and examined the relationships between construction performance and spatial and mathematical abilities in children. The study included three groups of children (N = 96); ages 7-8, 10-11, and 13-14 years. Each group constructed seven pre-specified objects. The study replicated and extended previous findings that indicated that the extent of component symmetry and variety, and the number of components for each object and available for selection, significantly predicted construction task difficulty. Results showed that this methodology is a valid and reliable technique for assessing and predicting construction play task difficulty. Furthermore, construction play performance predicted mathematical attainment independently of spatial ability.

The predictive value of physical examination findings in patients with suspected acute heart failure syndrome.

PubMed

Jang, Timothy B; Aubin, Chandra; Naunheim, Rosanne; Lewis, Lawrence M; Kaji, Amy H

2012-06-01

It can be difficult to differentiate acute heart failure syndrome (AHFS) from other causes of acute dyspnea, especially when patients present in extremis. The objective of the study was to determine the predictive value of physical examination findings for pulmonary edema and elevated B-type natriuretic peptide (BNP) levels in patients with suspected AHFS. This was a secondary analysis of a previously reported prospective study of jugular vein ultrasonography in patients with suspected AHFS. Charts were reviewed for physical examination findings, which were then compared to pulmonary edema on chest radiography (CXR) read by radiologists blinded to clinical information and BNP levels measured at presentation. The predictive value of every sign and combination of signs for pulmonary edema on CXR or an elevated BNP was poor. Since physical examination findings alone are not predictive of pulmonary edema or an elevated BNP, clinicians should have a low threshold for using CXR or BNP in clinical evaluation. This brief research report suggests that no physical examination finding or constellation of findings can be used to reliably predict pulmonary edema or an elevated BNP in patients with suspected AHFS.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

Noninvasive scoring system for significant inflammation related to chronic hepatitis B

NASA Astrophysics Data System (ADS)

Hong, Mei-Zhu; Ye, Linglong; Jin, Li-Xin; Ren, Yan-Dan; Yu, Xiao-Fang; Liu, Xiao-Bin; Zhang, Ru-Mian; Fang, Kuangnan; Pan, Jin-Shui

2017-03-01

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.

Predictors of the transition from acute to persistent musculoskeletal pain in children and adolescents: a prospective study

PubMed Central

Holley, Amy Lewandowski; Wilson, Anna C.; Palermo, Tonya M.

2016-01-01

Strategies directed at the prevention of disabling pain have been suggested as a public health priority, making early identification of youth at risk for poor outcomes critical. At present limited information is available to predict which youth presenting with acute pain are at risk for persistence. The aims of this prospective longitudinal study were to identify biopsychosocial factors in the acute period that predict the transition to persistent pain in youth with new-onset musculoskeletal (MSK) pain complaints. Participants were 88 children and adolescents (age 10–17 years) presenting to the emergency department (n=47) or orthopedic clinic (n=41) for evaluation of a new MSK pain complaint (< 1 month duration). Youth presented for two study visits (T1 = <1 month post pain onset; T2 = 4 month follow-up) during which they completed questionnaires (assessing pain characteristics, psychological factors, sleep quality) and participated in a lab task assessing conditioned pain modulation (CPM). Regression analyses tested T1 predictors of longitudinal pain outcomes (pain persistence, pain-related disability, quality of life). Results revealed approximately 35% of youth had persistent pain at 4-month follow-up, with persistent pain predicted by poorer CPM and female sex. Higher depressive symptoms at T1 were associated with higher pain-related disability and poorer quality of life at T2. Findings highlight the roles of depressive symptoms and pain modulation in longitudinally predicting pain persistence in treatment-seeking youth with acute MSK pain, and suggest potential mechanisms in the transition from acute to chronic MSK pain in children and adolescents. PMID:28151835

Predictive Factors for Death After Snake Envenomation in Myanmar.

PubMed

Aye, Kyi-Phyu; Thanachartwet, Vipa; Soe, Chit; Desakorn, Varunee; Chamnanchanunt, Supat; Sahassananda, Duangjai; Supaporn, Thanom; Sitprija, Visith

2018-06-01

Factors predictive for death from snake envenomation vary between studies, possibly due to variation in host genetic factors and venom composition. This study aimed to evaluate predictive factors for death from snake envenomation in Myanmar. A prospective study was performed among adult patients with snakebite admitted to tertiary hospitals in Yangon, Myanmar, from May 2015 to August 2016. Data including clinical variables and laboratory parameters, management, and outcomes were evaluated. Multivariate regression analysis was performed to evaluate factors predictive for death at the time of presentation to the hospital. Of the 246 patients with snake envenomation recruited into the study, 225 (92%) survived and 21 (8%) died during hospitalization. The snake species responsible for a bite was identified in 74 (30%) of the patients; the majority of bites were from Russell's vipers (63 patients, 85%). The independent factors predictive for death included 1) duration from bite to arrival at the hospital >1 h (odds ratio [OR]: 9.0, 95% confidence interval [CI]: 1.1-75.2; P=0.04); 2) white blood cell counts >20 ×10 3 cells·μL -1 (OR: 8.9, 95% CI: 2.3-33.7; P=0.001); and 3) the presence of capillary leakage (OR: 3.7, 95% CI: 1.2-11.2; P=0.02). A delay in antivenom administration >4 h increases risk of death (11/21 deaths). Patients who present with these independent predictive factors should be recognized and provided with early appropriate intervention to reduce the mortality rate among adults with snake envenomation in Myanmar. Copyright © 2018 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

Sexy online self-presentation on social network sites and the willingness to engage in sexting: A comparison of gender and age.

PubMed

van Oosten, Johanna M F; Vandenbosch, Laura

2017-01-01

The present study investigated whether engaging in sexy self-presentations on social network sites (SNSs) or exposure to sexy self-presentations on SNSs predicts the willingness to engage in sexting. A second aim of the present study was to investigate whether adolescent girls demonstrate stronger relationships between (exposure to) sexy online self-presentations on SNSs and willingness to sext than adolescent boys and young adult men and women. A two-wave panel survey among 953 Dutch adolescents (13-17 years old, 50.7% male) and 899 Dutch young adults (18-25 years old, 43.9% male) showed that engaging in sexy self-presentations on SNSs increased the willingness to engage in sexting, but only among adolescent girls. Exposure to sexy self-presentations of others did not predict the willingness to engage in sexting. The findings call for more research on the role of gender and age in the link between sexy self-presentation and sexting. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Do lifestyle factors and general health predict dropout among recently qualified eldercare workers? A two-year follow-up study.

PubMed

Giver, Hanne; Faber, Anne; Strøyer, Jesper; Hannerz, Harald; Albertsen, Karen

2011-05-01

The eldercare sector in Denmark as in many industrialised countries is characterised by difficulties in retaining labour. Research suggests a possible imbalance between lifestyle and health among eldercare trainees and the demanding work encountered as eldercare employees. The aim of the present study was to determine the predictive effect of lifestyle and self-rated health on dropout from the Danish eldercare sector two years after qualification. We included 4,526 female eldercare trainees in the analyses of lifestyle parameters and 5,023 in the analyses of self-rated health. The participants in this prospective study were recruited from 27 of the 28 Danish colleges for eldercare. We linked survey data with national register data to obtain information about labour market attachment two years after qualification. The results of the present study showed that the poorer self-rated health, the higher the risk for dropout from the labour market (p < 0.0001). However, the results were less consistent regarding the predictive effect of a detrimental lifestyle. We found that overweight/obesity (p = 0.0021 and p = 0.0012) as well as smoking (p = 0.0017) decreased the risk of dropout from eldercare into education. We found no support for increased likelihood of dropout among physically inactive. The results of the present study show that a poorer self-rated health is a predictor for dropout, not only from the eldercare two years after qualification, but from the labour market as a whole. However, the results were less consistent regarding the predictive effect of a detrimental lifestyle on dropout.

Teaching neurophysiology, neuropharmacology, and experimental design using animal models of psychiatric and neurological disorders.

PubMed

Morsink, Maarten C; Dukers, Danny F

2009-03-01

Animal models have been widely used for studying the physiology and pharmacology of psychiatric and neurological diseases. The concepts of face, construct, and predictive validity are used as indicators to estimate the extent to which the animal model mimics the disease. Currently, we used these three concepts to design a theoretical assignment to integrate the teaching of neurophysiology, neuropharmacology, and experimental design. For this purpose, seven case studies were developed in which animal models for several psychiatric and neurological diseases were described and in which neuroactive drugs used to treat or study these diseases were introduced. Groups of undergraduate students were assigned to one of these case studies and asked to give a classroom presentation in which 1) the disease and underlying pathophysiology are described, 2) face and construct validity of the animal model are discussed, and 3) a pharmacological experiment with the associated neuroactive drug to assess predictive validity is presented. After evaluation of the presentations, we found that the students had gained considerable insight into disease phenomenology, its underlying neurophysiology, and the mechanism of action of the neuroactive drug. Moreover, the assignment was very useful in the teaching of experimental design, allowing an in-depth discussion of experimental control groups and the prediction of outcomes in these groups if the animal model were to display predictive validity. Finally, the highly positive responses in the student evaluation forms indicated that the assignment was of great interest to the students. Hence, the currently developed case studies constitute a very useful tool for teaching neurophysiology, neuropharmacology, and experimental design.

Predictive model for risk of cesarean section in pregnant women after induction of labor.

PubMed

Hernández-Martínez, Antonio; Pascual-Pedreño, Ana I; Baño-Garnés, Ana B; Melero-Jiménez, María R; Tenías-Burillo, José M; Molina-Alarcón, Milagros

2016-03-01

To develop a predictive model for risk of cesarean section in pregnant women after induction of labor. A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room. The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively. These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural

PubMed Central

Douglas, Karen M.; De Inocencio, Clara

2017-01-01

Abstract A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs. PMID:29695889

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural.

PubMed

van Prooijen, Jan-Willem; Douglas, Karen M; De Inocencio, Clara

2018-04-01

A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs.

Recent research related to prediction of stall/spin characteristics of fighter aircraft

NASA Technical Reports Server (NTRS)

Nguyen, L. T.; Anglin, E. L.; Gilbert, W. P.

1976-01-01

The NASA Langley Research Center is currently engaged in a stall/spin research program to provide the fundamental information and design guidelines required to predict the stall/spin characteristics of fighter aircraft. The prediction methods under study include theoretical spin prediction techniques and piloted simulation studies. The paper discusses the overall status of theoretical techniques including: (1) input data requirements, (2) math model requirements, and (3) correlation between theoretical and experimental results. The Langley Differential Maneuvering Simulator (DMS) facility has been used to evaluate the spin susceptibility of several current fighters during typical air combat maneuvers and to develop and evaluate the effectiveness of automatic departure/spin prevention concepts. The evaluation procedure is described and some of the more significant results of the studies are presented.

Prediction of XV-15 tilt rotor discrete frequency aeroacoustic noise with WOPWOP

NASA Technical Reports Server (NTRS)

Coffen, Charles D.; George, Albert R.

1990-01-01

The results, methodology, and conclusions of noise prediction calculations carried out to study several possible discrete frequency harmonic noise mechanisms of the XV-15 Tilt Rotor Aircraft in hover and helicopter mode forward flight are presented. The mechanisms studied were thickness and loading noise. In particular, the loading noise caused by flow separation and the fountain/ground plane effect were predicted with calculations made using WOPWOP, a noise prediction program developed by NASA Langley. The methodology was to model the geometry and aerodynamics of the XV-15 rotor blades in hover and steady level flight and then create corresponding FORTRAN subroutines which were used an input for WOPWOP. The models are described and the simplifying assumptions made in creating them are evaluated, and the results of the computations are presented. The computations lead to the following conclusions: The fountain/ground plane effect is an important source of aerodynamic noise for the XV-15 in hover. Unsteady flow separation from the airfoil passing through the fountain at high angles of attack significantly affects the predicted sound spectra and may be an important noise mechanism for the XV-15 in hover mode. The various models developed did not predict the sound spectra in helicopter forward flight. The experimental spectra indicate the presence of blade vortex interactions which were not modeled in these calculations. A need for further study and development of more accurate aerodynamic models, including unsteady stall in hover and blade vortex interactions in forward flight.

Cloud prediction of protein structure and function with PredictProtein for Debian.

PubMed

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

PubMed Central

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

Action perception as hypothesis testing.

PubMed

Donnarumma, Francesco; Costantini, Marcello; Ambrosini, Ettore; Friston, Karl; Pezzulo, Giovanni

2017-04-01

We present a novel computational model that describes action perception as an active inferential process that combines motor prediction (the reuse of our own motor system to predict perceived movements) and hypothesis testing (the use of eye movements to disambiguate amongst hypotheses). The system uses a generative model of how (arm and hand) actions are performed to generate hypothesis-specific visual predictions, and directs saccades to the most informative places of the visual scene to test these predictions - and underlying hypotheses. We test the model using eye movement data from a human action observation study. In both the human study and our model, saccades are proactive whenever context affords accurate action prediction; but uncertainty induces a more reactive gaze strategy, via tracking the observed movements. Our model offers a novel perspective on action observation that highlights its active nature based on prediction dynamics and hypothesis testing. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

Mechanics of train collision

DOT National Transportation Integrated Search

1976-04-30

A simple and a more detailed mathematical model for the simulation of train collisions are presented. The study presents considerable insight as to the causes and consequences of train motions on impact. Comparison of model predictions with two full ...

Toxicity prediction of compounds from turmeric (Curcuma longa L).

PubMed

Balaji, S; Chempakam, B

2010-10-01

Turmeric belongs to the ginger family Zingiberaceae. Currently, cheminformatics approaches are not employed in any of the spices to study the medicinal properties traditionally attributed to them. The aim of this study is to find the most efficacious molecule which does not have any toxic effects. In the present study, toxicity of 200 chemical compounds from turmeric were predicted (includes bacterial mutagenicity, rodent carcinogenicity and human hepatotoxicity). The study shows out of 200 compounds, 184 compounds were predicted as toxigenic, 136 compounds are mutagenic, 153 compounds are carcinogenic and 64 compounds are hepatotoxic. To cross validate our results, we have chosen the popular curcumin and found that curcumin and its derivatives may cause dose dependent hepatotoxicity. The results of these studies indicate that, in contrast to curcumin, few other compounds in turmeric which are non-mutagenic, non-carcinogenic, non-hepatotoxic, and do not have any side-effects. Hence, the cost-effective approach presented in this paper could be used to filter toxic compounds from the drug discovery lifecycle. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Evaluating the Predictive Validity of the Computerized Comprehension Task: Comprehension Predicts Production

PubMed Central

Friend, Margaret; Schmitt, Sara A.; Simpson, Adrianne M.

2017-01-01

Until recently, the challenges inherent in measuring comprehension have impeded our ability to predict the course of language acquisition. The present research reports on a longitudinal assessment of the convergent and predictive validity of the CDI: Words and Gestures and the Computerized Comprehension Task (CCT). The CDI: WG and the CCT evinced good convergent validity however the CCT better predicted subsequent parent reports of language production. Language sample data in the third year confirm this finding: the CCT accounted for 24% of the variance in unique word use. These studies provide evidence for the utility of a behavior-based approach to predicting the course of language acquisition into production. PMID:21928878

Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms.

PubMed

Gudayol-Ferré, Esteve; Herrera-Guzmán, Ixchel; Camarena, Beatriz; Cortés-Penagos, Carlos; Herrera-Abarca, Jorge E; Martínez-Medina, Patricia; Asbun-Bojalil, Juan; Lira-Islas, Yuridia; Reyes-Ponce, Celia; Guàrdia-Olmos, Joan

2012-11-01

The aim of our work is to study the possible role of clinical variables, neuropsychological performance, and the 5HTTLPR, rs25531, and val108/58Met COMT polymorphisms on the prediction of depression remission after 12 weeks' treatment with fluoxetine. These variables have been studied as potential predictors of depression remission, but they present poor prognostic sensitivity and specificity by themselves. Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluxetine treatment. Only the La allele of rs25531 polymorphism and the GG and AA forms of the val 108/158 Met polymorphism predict major depressive disorder remission after 12 weeks' treatment with fluoxetine. None of the clinical and neuropsychological variables studied predicted remission. Our results suggest that clinical and neuropsychological variables can initially predict early response to fluoxetine and mask the predictive role of genetic variables; but in remission, where clinical and neuropsychological symptoms associated with depression tend to disappear thanks to the treatment administered, the polymorphisms studied are the only variables in our model capable of predicting remission. However, placebo effects that are difficult to control require cautious interpretation of the results.

Aeroelastic loads and stability investigation of a full-scale hingeless rotor

NASA Technical Reports Server (NTRS)

Peterson, Randall L.; Johnson, Wayne

1991-01-01

An analytical investigation was conducted to study the influence of various parameters on predicting the aeroelastic loads and stability of a full-scale hingeless rotor in hover and forward flight. The CAMRAD/JA (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics, Johnson Aeronautics) analysis code is used to obtain the analytical predictions. Data are presented for rotor blade bending and torsional moments as well as inplane damping data obtained for rotor operation in hover at a constant rotor rotational speed of 425 rpm and thrust coefficients between 0.0 and 0.12. Experimental data are presented from a test in the wind tunnel. Validation of the rotor system structural model with experimental rotor blade loads data shows excellent correlation with analytical results. Using this analysis, the influence of different aerodynamic inflow models, the number of generalized blade and body degrees of freedom, and the control-system stiffness at predicted stability levels are shown. Forward flight predictions of the BO-105 rotor system for 1-G thrust conditions at advance ratios of 0.0 to 0.35 are presented. The influence of different aerodynamic inflow models, dynamic inflow models and shaft angle variations on predicted stability levels are shown as a function of advance ratio.

Post-buckling of a pressured biopolymer spherical shell with the mode interaction

NASA Astrophysics Data System (ADS)

Zhang, Lei; Ru, C. Q.

2018-03-01

Imperfection sensitivity is essential for mechanical behaviour of biopolymer shells characterized by high geometric heterogeneity. The present work studies initial post-buckling and imperfection sensitivity of a pressured biopolymer spherical shell based on non-axisymmetric buckling modes and associated mode interaction. Our results indicate that for biopolymer spherical shells with moderate radius-to-thickness ratio (say, less than 30) and smaller effective bending thickness (say, less than 0.2 times average shell thickness), the imperfection sensitivity predicted based on the axisymmetric mode without the mode interaction is close to the present results based on non-axisymmetric modes with the mode interaction with a small (typically, less than 10%) relative errors. However, for biopolymer spherical shells with larger effective bending thickness, the maximum load an imperfect shell can sustain predicted by the present non-axisymmetric analysis can be significantly (typically, around 30%) lower than those predicted based on the axisymmetric mode without the mode interaction. In such cases, a more accurate non-axisymmetric analysis with the mode interaction, as given in the present work, is required for imperfection sensitivity of pressured buckling of biopolymer spherical shells. Finally, the implications of the present study to two specific types of biopolymer spherical shells (viral capsids and ultrasound contrast agents) are discussed.

The motivation to stay abstinent in ex-smokers: comparing the present with the past.

PubMed

Dijkstra, Arie; Borland, Ron; Buunk, Bram P

2007-10-01

Little is known about the motivation of ex-smokers to stay abstinent. In the present study we argue that ex-smokers compare their present to their past when they still smoked to conclude whether they make good progress towards a satisfactory state of continued abstinence. These temporal comparisons are thought to be central in the motivation to stay abstinent in ex-smokers. The power of temporal comparisons to predict relapse was tested in two related samples of ex-smokers (N=152 and N=197), together with two other relevant psychological factors; positive outcome expectations of smoking and self-efficacy expectations. In the first sample of ex-smokers, only temporal comparisons predicted relapse after 2 months. In the second sample of ex-smokers, temporal comparisons mediated the relation between perceived positive outcomes of smoking and relapse after 6 months. In addition, in predicting relapse after 6 months, temporal comparisons interacted with self-efficacy. The present study suggests that temporal comparisons comprise the cognitive aspect of the motivation of ex-smokers to stay abstinent. This conceptualization of the motivation in ex-smokers can be used in practice to prevent relapse.

Exploring associations between exposure to sexy online self-presentations and adolescents' sexual attitudes and behavior.

PubMed

van Oosten, Johanna M F; Peter, Jochen; Boot, Inge

2015-05-01

Previous research suggests that adolescents' social network site use is related to their sexual development. However, the associations between adolescents' exposure to sexy self-presentations of others on social network sites and their sexual attitudes and experience have not yet been empirically supported. This study investigated reciprocal longitudinal relationships between adolescents' exposure to others' sexy self-presentations on social network sites and their sexual attitudes (i.e., sexual objectification of girls and instrumental attitudes towards sex) and sexual experience. We further tested whether these associations depended on adolescents' age and gender. Results from a representative two-wave panel study among 1,636 Dutch adolescents (aged 13-17, 51.5 % female) showed that exposure to sexy online self-presentations of others predicted changes in adolescents' experience with oral sex and intercourse 6 months later, but did not influence their sexual attitudes. Adolescents' instrumental attitudes towards sex, in turn, did predict their exposure to others' sexy online self-presentations. Sexual objectification increased such exposure for younger adolescents, but decreased exposure for older adolescents. In addition, adolescents' experience with genital touching as well as oral sex (only for adolescents aged 13-15) predicted their exposure to sexy self-presentations of others. These findings tentatively suggest that the influence on adolescents' sexual attitudes previously found for sexual media content may not hold for sexy self-presentations on social network sites. However, exposure to sexy self-presentations on social network sites is motivated by adolescents' sexual attitudes and behavior, especially among young adolescents.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients.

PubMed

Aguiar, Fabio S; Almeida, Luciana L; Ruffino-Netto, Antonio; Kritski, Afranio Lineu; Mello, Fernanda Cq; Werneck, Guilherme L

2012-08-07

Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Evaluation of performance of seasonal precipitation prediction at regional scale over India

NASA Astrophysics Data System (ADS)

Mohanty, U. C.; Nageswararao, M. M.; Sinha, P.; Nair, A.; Singh, A.; Rai, R. K.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, K.; Rathore, L. S.; Sharma, R.; Kumar, A.; Dhekale, B. S.; Maurya, R. K. S.; Sahoo, R. K.; Dash, G. P.

2018-03-01

The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982-2008) as well as independent predictions for the period 2009-2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions as well as India as a whole during all the four seasons.

Addressing criticisms of existing predictive bias research: cognitive ability test scores still overpredict African Americans' job performance.

PubMed

Berry, Christopher M; Zhao, Peng

2015-01-01

Predictive bias studies have generally suggested that cognitive ability test scores overpredict job performance of African Americans, meaning these tests are not predictively biased against African Americans. However, at least 2 issues call into question existing over-/underprediction evidence: (a) a bias identified by Aguinis, Culpepper, and Pierce (2010) in the intercept test typically used to assess over-/underprediction and (b) a focus on the level of observed validity instead of operational validity. The present study developed and utilized a method of assessing over-/underprediction that draws on the math of subgroup regression intercept differences, does not rely on the biased intercept test, allows for analysis at the level of operational validity, and can use meta-analytic estimates as input values. Therefore, existing meta-analytic estimates of key parameters, corrected for relevant statistical artifacts, were used to determine whether African American job performance remains overpredicted at the level of operational validity. African American job performance was typically overpredicted by cognitive ability tests across levels of job complexity and across conditions wherein African American and White regression slopes did and did not differ. Because the present study does not rely on the biased intercept test and because appropriate statistical artifact corrections were carried out, the present study's results are not affected by the 2 issues mentioned above. The present study represents strong evidence that cognitive ability tests generally overpredict job performance of African Americans. (c) 2015 APA, all rights reserved.

Mechanism of Void Prediction in Flip Chip Packages with Molded Underfill

NASA Astrophysics Data System (ADS)

Wu, Kuo-Tsai; Hwang, Sheng-Jye; Lee, Huei-Huang

2017-08-01

Voids have always been present using the molded underfill (MUF) package process, which is a problem that needs further investigation. In this study, the process was studied using the Moldex3D numerical analysis software. The effects of gas (air vent effect) on the overall melt front were also considered. In this isothermal process containing two fluids, the gas and melt colloid interact in the mold cavity. Simulation enabled an appropriate understanding of the actual situation to be gained, and, through analysis, the void region and exact location of voids were predicted. First, the global flow end area was observed to predict the void movement trend, and then the local flow ends were observed to predict the location and size of voids. In the MUF 518 case study, simulations predicted the void region as well as the location and size of the voids. The void phenomenon in a flip chip ball grid array underfill is discussed as part of the study.

Evaluating Perceived Probability of Threat-Relevant Outcomes and Temporal Orientation in Flying Phobia.

PubMed

Mavromoustakos, Elena; Clark, Gavin I; Rock, Adam J

2016-01-01

Probability bias regarding threat-relevant outcomes has been demonstrated across anxiety disorders but has not been investigated in flying phobia. Individual temporal orientation (time perspective) may be hypothesised to influence estimates of negative outcomes occurring. The present study investigated whether probability bias could be demonstrated in flying phobia and whether probability estimates of negative flying events was predicted by time perspective. Sixty flying phobic and fifty-five non-flying-phobic adults were recruited to complete an online questionnaire. Participants completed the Flight Anxiety Scale, Probability Scale (measuring perceived probability of flying-negative events, general-negative and general positive events) and the Past-Negative, Future and Present-Hedonistic subscales of the Zimbardo Time Perspective Inventory (variables argued to predict mental travel forward and backward in time). The flying phobic group estimated the probability of flying negative and general negative events occurring as significantly higher than non-flying phobics. Past-Negative scores (positively) and Present-Hedonistic scores (negatively) predicted probability estimates of flying negative events. The Future Orientation subscale did not significantly predict probability estimates. This study is the first to demonstrate probability bias for threat-relevant outcomes in flying phobia. Results suggest that time perspective may influence perceived probability of threat-relevant outcomes but the nature of this relationship remains to be determined.

Evaluating Perceived Probability of Threat-Relevant Outcomes and Temporal Orientation in Flying Phobia

PubMed Central

Mavromoustakos, Elena; Clark, Gavin I.; Rock, Adam J.

2016-01-01

Probability bias regarding threat-relevant outcomes has been demonstrated across anxiety disorders but has not been investigated in flying phobia. Individual temporal orientation (time perspective) may be hypothesised to influence estimates of negative outcomes occurring. The present study investigated whether probability bias could be demonstrated in flying phobia and whether probability estimates of negative flying events was predicted by time perspective. Sixty flying phobic and fifty-five non-flying-phobic adults were recruited to complete an online questionnaire. Participants completed the Flight Anxiety Scale, Probability Scale (measuring perceived probability of flying-negative events, general-negative and general positive events) and the Past-Negative, Future and Present-Hedonistic subscales of the Zimbardo Time Perspective Inventory (variables argued to predict mental travel forward and backward in time). The flying phobic group estimated the probability of flying negative and general negative events occurring as significantly higher than non-flying phobics. Past-Negative scores (positively) and Present-Hedonistic scores (negatively) predicted probability estimates of flying negative events. The Future Orientation subscale did not significantly predict probability estimates. This study is the first to demonstrate probability bias for threat-relevant outcomes in flying phobia. Results suggest that time perspective may influence perceived probability of threat-relevant outcomes but the nature of this relationship remains to be determined. PMID:27557054

Predictive validity of childhood oppositional defiant disorder and conduct disorder: implications for the DSM-V.

PubMed

Burke, Jeffrey D; Waldman, Irwin; Lahey, Benjamin B

2010-11-01

Data are presented from 3 studies of children and adolescents to evaluate the predictive validity of childhood oppositional defiant disorder (ODD) and conduct disorder (CD) as defined in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; American Psychiatric Association, 1994) and the International Classification of Diseases, Version 10 (ICD-10; World Health Organization, 1992). The present analyses strongly support the predictive validity of these diagnoses by showing that they predict both future psychopathology and enduring functional impairment. Furthermore, the present findings generally support the hierarchical developmental hypothesis in DSM-IV that some children with ODD progress to childhood-onset CD, and some youth with CD progress to antisocial personality disorder (APD). Nonetheless, they reveal that CD does not always co-occur with ODD, particularly during adolescence. Importantly, the present findings suggest that ICD-10 diagnostic criteria for ODD, which treat CD symptoms as ODD symptoms when diagnostic criteria for CD are not met, identify more functionally impaired children than the more restrictive DSM-IV definition of ODD. Filling this "hole" in the DSM-IV criteria for ODD should be a priority for the DSM-V. In addition, the present findings suggest that although the psychopathic trait of interpersonal callousness in childhood independently predicts future APD, these findings do not confirm the hypothesis that callousness distinguishes a subset of children with CD with an elevated risk for APD. PsycINFO Database Record (c) 2010 APA, all rights reserved

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference

PubMed Central

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference (p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information. PMID:29479312

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference.

PubMed

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-Ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference ( p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information.

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning

PubMed Central

Sutphin, George L.; Mahoney, J. Matthew; Sheppard, Keith; Walton, David O.; Korstanje, Ron

2016-01-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species—humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/. PMID:27812085

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PubMed

Sutphin, George L; Mahoney, J Matthew; Sheppard, Keith; Walton, David O; Korstanje, Ron

2016-11-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species-humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/.

Understanding and Predicting the Process of Software Maintenance Releases

NASA Technical Reports Server (NTRS)

Basili, Victor; Briand, Lionel; Condon, Steven; Kim, Yong-Mi; Melo, Walcelio L.; Valett, Jon D.

1996-01-01

One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

An integrated uncertainty analysis and data assimilation approach for improved streamflow predictions

NASA Astrophysics Data System (ADS)

Hogue, T. S.; He, M.; Franz, K. J.; Margulis, S. A.; Vrugt, J. A.

2010-12-01

The current study presents an integrated uncertainty analysis and data assimilation approach to improve streamflow predictions while simultaneously providing meaningful estimates of the associated uncertainty. Study models include the National Weather Service (NWS) operational snow model (SNOW17) and rainfall-runoff model (SAC-SMA). The proposed approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. An ensemble Kalman filter (EnKF) is configured with the DREAM-identified uncertainty structure and applied to assimilating snow water equivalent data into the SNOW17 model for improved snowmelt simulations. Snowmelt estimates then serves as an input to the SAC-SMA model to provide streamflow predictions at the basin outlet. The robustness and usefulness of the approach is evaluated for a snow-dominated watershed in the northern Sierra Mountains. This presentation describes the implementation of DREAM and EnKF into the coupled SNOW17 and SAC-SMA models and summarizes study results and findings.

A study on the influence of corona on currents and electromagnetic fields predicted by a nonlinear lightning return-stroke model

NASA Astrophysics Data System (ADS)

De Conti, Alberto; Silveira, Fernando H.; Visacro, Silvério

2014-05-01

This paper investigates the influence of corona on currents and electromagnetic fields predicted by a return-stroke model that represents the lightning channel as a nonuniform transmission line with time-varying (nonlinear) resistance. The corona model used in this paper allows the calculation of corona currents as a function of the radial electric field in the vicinity of the channel. A parametric study is presented to investigate the influence of corona parameters, such as the breakdown electric field and the critical electric field for the stable propagation of streamers, on predicted currents and electromagnetic fields. The results show that, regardless of the assumed corona parameters, the incorporation of corona into the nonuniform and nonlinear transmission line model under investigation modifies the model predictions so that they consistently reproduce most of the typical features of experimentally observed lightning electromagnetic fields and return-stroke speed profiles. In particular, it is shown that the proposed model leads to close vertical electric fields presenting waveforms, amplitudes, and decay with distance in good agreement with dart leader electric field changes measured in triggered lightning experiments. A comparison with popular engineering return-stroke models further confirms the model's ability to predict consistent electric field waveforms in the close vicinity of the channel. Some differences observed in the field amplitudes calculated with the different models can be related to the fact that current distortion, while present in the proposed model, is ultimately neglected in the considered engineering return-stroke models.

Pathways to aggression and violence among African American adolescent males: the influence of normative beliefs, neighborhood, and depressive symptomatology.

PubMed

Robinson, W Lavome; Paxton, Keisha C; Jonen, Lynn P

2011-01-01

Youth violence continues to present a serious public health challenge in the United States, particularly so for African American adolescent males. The present study utilized a multilevel approach to predict aggression within a community sample of low-income, urban African American adolescent males (n = 80). Participants' self-report data on normative beliefs about aggression, exposure to community violence, and depressive symptoms were used in multiple regression equations to predict (a) self-reported interpersonal aggression and (b) self-reported aggressive response style when angered. Results of this study indicate that all three of the independent variables contributed significantly to the prediction of interpersonal aggression and aggressive response style when angered. The findings are important for increasing our understanding of pathways to various types of youth aggression and guiding the development of evidence-based approaches to violence prevention among African American adolescent males.

Quantitative analysis and predictive engineering of self-rolling of nanomembranes under anisotropic mismatch strain

NASA Astrophysics Data System (ADS)

Chen, Cheng; Song, Pengfei; Meng, Fanchao; Li, Xiao; Liu, Xinyu; Song, Jun

2017-12-01

The present work presents a quantitative modeling framework for investigating the self-rolling of nanomembranes under different lattice mismatch strain anisotropy. The effect of transverse mismatch strain on the roll-up direction and curvature has been systematically studied employing both analytical modeling and numerical simulations. The bidirectional nature of the self-rolling of nanomembranes and the critical role of transverse strain in affecting the rolling behaviors have been demonstrated. Two fabrication strategies, i.e., third-layer deposition and corner geometry engineering, have been proposed to predictively manipulate the bidirectional rolling competition of strained nanomembranes, so as to achieve controlled, unidirectional roll-up. In particular for the strategy of corner engineering, microfabrication experiments have been performed to showcase its practical application and effectiveness. Our study offers new mechanistic knowledge towards understanding and predictive engineering of self-rolling of nanomembranes with improved roll-up yield.

Individual differences in episodic memory abilities predict successful prospective memory output monitoring.

PubMed

Hunter Ball, B; Pitães, Margarida; Brewer, Gene A

2018-02-07

Output monitoring refers to memory for one's previously completed actions. In the context of prospective memory (PM) (e.g., remembering to take medication), failures of output monitoring can result in repetitions and omissions of planned actions (e.g., over- or under-medication). To be successful in output monitoring paradigms, participants must flexibly control attention to detect PM cues as well as engage controlled retrieval of previous actions whenever a particular cue is encountered. The current study examined individual differences in output monitoring abilities in a group of younger adults differing in attention control (AC) and episodic memory (EM) abilities. The results showed that AC ability uniquely predicted successful cue detection on the first presentation, whereas EM ability uniquely predicted successful output monitoring on the second presentation. The current study highlights the importance of examining external correlates of PM abilities and contributes to the growing body of research on individual differences in PM.

Correlation tracking study for meter-class solar telescope on space shuttle. [solar granulation

NASA Technical Reports Server (NTRS)

Smithson, R. C.; Tarbell, T. D.

1977-01-01

The theory and expected performance level of correlation trackers used to control the pointing of a solar telescope in space using white light granulation as a target were studied. Three specific trackers were modeled and their performance levels predicted for telescopes of various apertures. The performance of the computer model trackers on computer enhanced granulation photographs was evaluated. Parametric equations for predicting tracker performance are presented.

Predicting the At Risk Status of College Students: Males and Students with Disabilities. Final Report Presented to PAREA, Spring 2009

ERIC Educational Resources Information Center

Jorgensen, Shirley; Fichten, Catherine; Havel, Alice

2009-01-01

The main aim of this study was to gain a better understanding of why students abandon their studies, or perform less well than expected given their high school grades, and to develop predictive models that can help identify those students most at-risk at the time they enter college. This will allow teachers and those responsible for student…

Income reliably predicts daily sadness, but not happiness: A replication and extension of Kushlev, Dunn, & Lucas (2015)

PubMed Central

Hudson, Nathan W.; Lucas, Richard E.; Donnellan, M. Brent; Kushlev, Kostadin

2017-01-01

Kushlev, Dunn, and Lucas (2015) found that income predicts less daily sadness—but not greater happiness—among Americans. The present study used longitudinal data from an approximately representative German sample to replicate and extend these findings. Our results largely replicated Kushlev and colleagues’: income predicted less daily sadness (albeit with a smaller effect size), but was unrelated to happiness. Moreover, the association between income and sadness could not be explained by demographics, stress, or daily time-use. Extending Kushlev and colleagues’ findings, new analyses indicated that only between-persons variance in income (but not within-persons variance) predicted daily sadness—perhaps because there was relatively little within-persons variance in income. Finally, income predicted less daily sadness and worry, but not less anger or frustration—potentially suggesting that income predicts less “internalizing” but not less “externalizing” negative emotions. Together, our study and Kushlev and colleagues’ provide evidence that income robustly predicts select daily negative emotions—but not positive ones. PMID:29250303

A model for prediction of color change after tooth bleaching based on CIELAB color space

NASA Astrophysics Data System (ADS)

Herrera, Luis J.; Santana, Janiley; Yebra, Ana; Rivas, María. José; Pulgar, Rosa; Pérez, María. M.

2017-08-01

An experimental study aiming to develop a model based on CIELAB color space for prediction of color change after a tooth bleaching procedure is presented. Multivariate linear regression models were obtained to predict the L*, a*, b* and W* post-bleaching values using the pre-bleaching L*, a*and b*values. Moreover, univariate linear regression models were obtained to predict the variation in chroma (C*), hue angle (h°) and W*. The results demonstrated that is possible to estimate color change when using a carbamide peroxide tooth-bleaching system. The models obtained can be applied in clinic to predict the colour change after bleaching.

Stock market index prediction using neural networks

NASA Astrophysics Data System (ADS)

Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

1994-03-01

A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

PubMed

Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

2016-08-01

Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of initial plasma lactate values as a predictor of gastric necrosis and initial and subsequent plasma lactate values as a predictor of survival in dogs with gastric dilatation-volvulus: 84 dogs (2003-2007).

PubMed

Green, Tiffany I; Tonozzi, Caroline C; Kirby, Rebecca; Rudloff, Elke

2011-02-01

To test whether an initial plasma lactate ≥ 6.0 mmol/L is associated with the presence of macroscopic gastric wall necrosis and overall survival in dogs presenting with gastric dilatation-volvulus (GDV). Additionally, if no association was identified we sought to identify a different predictive initial plasma lactate concentration and to examine whether serial plasma lactate concentrations provide better prediction of survival. Retrospective study over a 5-year period (2003-2007). Urban private referral small animal teaching hospital. Eighty-four client-owned dogs with a diagnosis of GDV and plasma lactate measurements. None. There was no statistically significant relationship found between survival and the presence of macroscopic gastric wall necrosis with the initial plasma lactate ≥ 6 mmol/L. There was a significant relationship between the initial plasma lactate >2.9 mmol/L for predicting necrosis and <4.1 mmol/L for predicting survival to discharge. Forty dogs that had an increased initial plasma lactate (>2.5 mmol/L) also had a subsequent plasma lactate measured within 12 hours of presentation, with 37/40 dogs surviving and 70% of these surviving dogs having the subsequent lactate decrease by ≥ 50% within 12 hours. The 3/40 that died failed to decrease their plasma lactate by ≥ 50% from the initial blood lactate. The results of this study indicate that an initial presenting plasma lactate concentration ≥ 6.0 mmol/L is not predictive of macroscopic gastric wall necrosis or survival in dogs presenting with GDV. A decrease in plasma lactate concentrations ≥ 50% within 12 hours may be a good indicator for survival. Limitations to the study include its retrospective nature, the small number of patients, and the number of dogs that were euthanized rather than allowed to progress to a natural outcome. © Veterinary Emergency and Critical Care Society 2011.

Evaluation of predictive capacities of biomarkers based on research synthesis.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-10

The objective of diagnostic studies or prognostic studies is to evaluate and compare predictive capacities of biomarkers. Suppose we are interested in evaluation and comparison of predictive capacities of continuous biomarkers for a binary outcome based on research synthesis. In analysis of each study, subjects are often classified into two groups of the high-expression and low-expression groups according to a cut-off value, and statistical analysis is based on a 2 × 2 table defined by the response and the high expression or low expression of the biomarker. Because the cut-off is study specific, it is difficult to interpret a combined summary measure such as an odds ratio based on the standard meta-analysis techniques. The summary receiver operating characteristic curve is a useful method for meta-analysis of diagnostic studies in the presence of heterogeneity of cut-off values to examine discriminative capacities of biomarkers. We develop a method to estimate positive or negative predictive curves, which are alternative to the receiver operating characteristic curve based on information reported in published papers of each study. These predictive curves provide a useful graphical presentation of pairs of positive and negative predictive values and allow us to compare predictive capacities of biomarkers of different scales in the presence of heterogeneity in cut-off values among studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Visual Motion Prediction and Verbal False Memory Performance in Autistic Children.

PubMed

Tewolde, Furtuna G; Bishop, Dorothy V M; Manning, Catherine

2018-03-01

Recent theoretical accounts propose that atypical predictive processing can explain the diverse cognitive and behavioral features associated with autism, and that difficulties in making predictions may be related to reduced contextual processing. In this pre-registered study, 30 autistic children aged 6-14 years and 30 typically developing children matched in age and non-verbal IQ completed visual extrapolation and false memory tasks to assess predictive abilities and contextual processing, respectively. In the visual extrapolation tasks, children were asked to predict when an occluded car would reach the end of a road and when an occluded set of lights would fill up a grid. Autistic children made predictions that were just as precise as those made by typically developing children, across a range of occlusion durations. In the false memory task, autistic and typically developing children did not differ significantly in their discrimination between items presented in a list and semantically related, non-presented items, although the data were insensitive, suggesting the need for larger samples. Our findings help to refine theoretical accounts by challenging the notion that autism is caused by pervasively disordered prediction abilities. Further studies will be required to assess the relationship between predictive processing and context use in autism, and to establish the conditions under which predictive processing may be impaired. Autism Res 2018, 11: 509-518. © 2017 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc. It has been suggested that autistic individuals have difficulties making predictions and perceiving the overall gist of things. Yet, here we found that autistic children made similar predictions about hidden objects as non-autistic children. In a memory task, autistic children were slightly less confused about whether they had heard a word before, when words were closely related in meaning. We conclude that autistic children do not show difficulties with this type of prediction. © 2017 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc.

Accuracy of the Surgeons' Clinical Prediction of Postoperative Major Complications Using a Visual Analog Scale.

PubMed

Woodfield, John C; Sagar, Peter M; Thekkinkattil, Dinesh K; Gogu, Praveen; Plank, Lindsay D; Burke, Dermot

2017-01-01

Although the risk factors that contribute to postoperative complications are well recognized, prediction in the context of a particular patient is more difficult. We were interested in using a visual analog scale (VAS) to capture surgeons' prediction of the risk of a major complication and to examine whether this could be improved. The study was performed in 3 stages. In phase I, the surgeon assessed the risk of a major complication on a 100-mm VAS immediately before and after surgery. A quality control questionnaire was designed to check if the VAS was being scored as a linear scale. In phase II, a VAS with 6 subscales for different areas of clinical risk was introduced. In phase III, predictions were completed following the presentation of detailed feedback on the accuracy of prediction of complications. In total, 1295 predictions were made by 58 surgeons in 859 patients. Eight surgeons did not use a linear scale (6 logarithmic, 2 used 4 categories of risk). Surgeons made a meaningful prediction of major complications (preoperative median score 40 mm for complications v. 22 mm for no complication, P < 0.001; postoperative 46 mm v. 21 mm, P < 0.001). In phase I, the discrimination of prediction for preoperative (0.778), postoperative (0.810), and POSSUM (Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity) morbidity (0.750) prediction was similar. Although there was no improvement in prediction with a multidimensional VAS, there was a significant improvement in the discrimination of prediction after feedback (preoperative, 0.895; postoperative, 0.918). Awareness of different ways a VAS is scored is important when designing and interpreting studies. Clinical assessment of major complications by the surgeon was initially comparable to the prediction of the POSSUM morbidity score and improved significantly following the presentation of clinically relevant feedback. © The Author(s) 2016.

[Metacarpophalangeal and carpal numeric indices to calculate bone age and predict adult size].

PubMed

Ebrí Torné, B; Ebrí Verde, I

2012-04-01

This work presents new numerical methods from the meta-carpal-phalangeal and carpal indexes, for calculating bone age. In addition, these new methods enable the adult height to be predicted using multiple regression equations. The longitudinal case series studied included 160 healthy children from Zaragoza, of both genders, aged between 6 months and 20 years, and studied annually, including the radiological study. For the statistical analysis the statistical package "Statistix", as well as the Excel program, was used. The new indexes are closely co-related to the chronological age, thus leading to predictive equations for the calculation of the bone age of children up to 20 years of age. In addition, it presents particular equations for up to 4 years of age, in order to optimise the diagnosis at these early ages. The resulting bones ages can be applied to numerical standard deviation tables, as well as to an equivalences chart, which directly gives us the ossification diagnosis. The predictive equations of adult height allow a reliable forecast of the future height of the studied child. These forecasts, analysed by the Student test did not show significant differences as regards the adult height that children of the case series finally achieved. The results can be obtained with a pocket calculator or through free software available for the reader. For the first time, and using a centre-developed and non-foreign methods, bones age standards and adult height predictive equations for the study of children, are presented. We invite the practitioner to use these meta-carpal-phalangeal and carpal methods in order to achieve the necessary experience to apply it to a healthy population and those with different disorders. Copyright © 2011 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement

PubMed Central

Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E.

2017-01-01

The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students (N = 597) vs. second-year students (N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students. PMID:28326043

A statistical model including age to predict passenger postures in the rear seats of automobiles.

PubMed

Park, Jangwoon; Ebert, Sheila M; Reed, Matthew P; Hallman, Jason J

2016-06-01

Few statistical models of rear seat passenger posture have been published, and none has taken into account the effects of occupant age. This study developed new statistical models for predicting passenger postures in the rear seats of automobiles. Postures of 89 adults with a wide range of age and body size were measured in a laboratory mock-up in seven seat configurations. Posture-prediction models for female and male passengers were separately developed by stepwise regression using age, body dimensions, seat configurations and two-way interactions as potential predictors. Passenger posture was significantly associated with age and the effects of other two-way interaction variables depended on age. A set of posture-prediction models are presented for women and men, and the prediction results are compared with previously published models. This study is the first study of passenger posture to include a large cohort of older passengers and the first to report a significant effect of age for adults. The presented models can be used to position computational and physical human models for vehicle design and assessment. Practitioner Summary: The significant effects of age, body dimensions and seat configuration on rear seat passenger posture were identified. The models can be used to accurately position computational human models or crash test dummies for older passengers in known rear seat configurations.

A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

EPA Science Inventory

The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

Courage in the Classroom: Exploring a New Framework Predicting Academic Performance and Engagement

ERIC Educational Resources Information Center

Martin, Andrew J.

2011-01-01

In the context of 7,637 high school students, the present study explored an hypothesized formulation of academic courage (defined as perseverance in the face of academic difficulty and fear) and its role in predicting academic performance (literacy and arithmetic) and various academic engagement measures (planning, task management,…

Emotional Clarity as a Mechanism Linking Emotional Neglect and Depressive Symptoms during Early Adolescence

ERIC Educational Resources Information Center

Jessar, Allison J.; Hamilton, Jessica L.; Flynn, Megan; Abramson, Lyn Y.; Alloy, Lauren B.

2017-01-01

The present study examined whether emotional abuse and neglect differentially predicted decreases in emotional clarity, and whether emotional clarity, in turn, predicted increases in depressive symptoms. Participants included 204 early adolescents (52% African American; 54% female; M age = 12.85 years) who completed four assessments with measures…

Predicting Early Spelling: The Contribution of Children's Early Literacy, Private Speech during Spelling, Behavioral Regulation, and Parental Spelling Support

ERIC Educational Resources Information Center

Aram, Dorit; Abiri, Shimrit; Elad, Lili

2014-01-01

The present study aimed to extend understanding of preschoolers' early spelling using the Vygotskian ("Mind in society: the development of higher psychological processes," Cambridge, Harvard University Press, 1978) paradigm of child development. We assessed the contribution of maternal spelling support in predicting children's word…

Improving Marital Prediction: A Model and a Pilot Study.

ERIC Educational Resources Information Center

Dean, Dwight G.; Lucas, Wayne L.

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

Predicting Adolescent Drug Abuse: A Review of Issues, Methods and Correlates. Research Issues 11.

ERIC Educational Resources Information Center

Lettieri, Dan J., Ed.

Presented are 18 papers on predicting adolescent drug abuse. The papers have the following titles: "Current Issues in the Epidemiology of Drug Abuse as Related to Psychosocial Studies of Adolescent Drug Use"; "The Quest for Interpersonal Predictors of Marihuana Abuse in Adolescents"; "Assessing the Interpersonal Determinants of Adolescent Drug…

Memory for Textual Conflicts Predicts Sourcing When Adolescents Read Multiple Expository Texts

ERIC Educational Resources Information Center

Stang Lund, Elisabeth; Bråten, Ivar; Brante, Eva W.; Strømsø, Helge I.

2017-01-01

This study investigated whether memory for conflicting information predicted mental representation of source-content links (i.e., who said what) in a sample of 86 Norwegian adolescent readers. Participants read four texts presenting conflicting claims about sun exposure and health. With differences in gender, prior knowledge, and interest…

Statistical Power for a Simultaneous Test of Factorial and Predictive Invariance

ERIC Educational Resources Information Center

Olivera-Aguilar, Margarita; Millsap, Roger E.

2013-01-01

A common finding in studies of differential prediction across groups is that although regression slopes are the same or similar across groups, group differences exist in regression intercepts. Building on earlier work by Birnbaum (1979), Millsap (1998) presented an invariant factor model that would explain such intercept differences as arising due…

EFFECTS OF USING THE CB05 VS SAPRC 99 VS CB4 CHEMICAL MECHANISMS ON MODEL PREDICTIONS

EPA Science Inventory

In this study, we examine differences in predictions of ozone, other oxidants, and ozone precursors for 3 chemical mechanisms: the CB4, CB05 and SAPRC99 mechanism (CMAQ/Models3 version). We present results for current conditions and differences among the mechanisms with emission...

The Use of the Position Analysis Questionnaire in Selecting Correlates of Job Performance Among Mentally Retarded Workers

ERIC Educational Resources Information Center

And Others; Townsend, J. William

1974-01-01

The present study investigated the efficiency of various existing measures, mainly psychological tests, for predicting job performance of mentally retarded workers in a sheltered occupational shop. Results indicated that existing measures are predictive of performance on some but not all jobs in a sheltered workshop. (Author)

The Utility of the Prototype/Willingness Model in Predicting Alcohol Use among North American Indigenous Adolescents

ERIC Educational Resources Information Center

Armenta, Brian E.; Hautala, Dane S.; Whitbeck, Les B.

2015-01-01

In the present study, we considered the utility of the prototype/willingness model in predicting alcohol use among North-American Indigenous adolescents. Specifically, using longitudinal data, we examined the associations among subjective drinking norms, positive drinker prototypes, drinking expectations (as a proxy of drinking willingness), and…

Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: the PALMS study protocol

PubMed Central

2014-01-01

Background Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. Methods/Design In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. Discussion This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions. PMID:24507749

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

Relationships between racial-ethnic identity, self-esteem and in-group attitudes among First Nation children.

PubMed

Corenblum, Barry

2014-03-01

Positive in-group distinctiveness has been associated with self-esteem increases among adolescents and adults. To examine whether in-group biases are associated with self-esteem enhancement among minority group children, Native Canadian children (N = 414, 209 female) age 6-11 completed each year for 5 years, measures assessing their level of concrete operational thought, racial-ethnic identity, racial-ethnic centrality, implicit and explicit self-esteem, and implicit and explicit in-group attitudes. According to cognitive developmental theory, increases in the level of concrete operational thought will predict increases in racial-ethnic identity, and increases in identity should, in turn, predict more favorable in-group attitudes. Social identity theory predicts that more favorable in-group attitudes should predict increases in self-esteem. Multi-level structural equation modelling revealed support for these hypotheses. Cognitively mature children who identify closely with their group enhanced their level of self-esteem by positively differentiating between group members on dimensions that favor their group. Limitations of the present study and suggestions for future studies are also presented.

Optimism/pessimism and future orientation as predictors of suicidal ideation: Are there ethnic differences?

PubMed

Yu, Elizabeth A; Chang, Edward C

2016-10-01

The present study sought to test the generalizability of Chang et al.'s (2013) model, which suggests that optimism/pessimism and future orientation function as additive and interactive predictors of suicidal risk, to specific ethnic minority college student groups (i.e., Asian Americans, African Americans, and Latino Americans). The present study used Chang et al.'s (2013) model to predict suicidal ideation among 81 (34 male and 47 female) Asian-American, 71 (22 male and 49 female) African-American adults, and 83 (34 male and 49 female) Latino-American college students. Our results indicated that this model did not predict suicidal ideation well for Asian-American college students; however, it did work well to predict suicidal ideation for African-American and Latino-American college students. Our findings indicate that optimism/pessimism and future orientation are important positive cognitions involved with suicidal ideation for African-American and Latino-American college students. Further research is needed to better understand the cultural underpinnings of how these positive cognitions work to predict suicide-related outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The theory of planned behavior applied to young people's use of social networking Web sites.

PubMed

Pelling, Emma L; White, Katherine M

2009-12-01

Despite the increasing popularity of social networking Web sites (SNWs), very little is known about the psychosocial variables that predict people's use of these Web sites. The present study used an extended model of the theory of planned behavior (TPB), including the additional variables of self-identity and belongingness, to predict high-level SNW use intentions and behavior in a sample of young people ages 17 to 24 years. Additional analyses examined the impact of self-identity and belongingness on young people's addictive tendencies toward SNWs. University students (N = 233) completed measures of the standard TPB constructs (attitude, subjective norm, and perceived behavioral control), the additional predictor variables (self-identity and belongingness), demographic variables (age, gender, and past behavior), and addictive tendencies. One week later, they reported their engagement in high-level SNW use during the previous week. Regression analyses partially supported the TPB: attitude and subjective norm significantly predicted intentions to engage in high-level SNW use with intention significantly predicting behavior. Self-identity, but not belongingness, significantly contributed to the prediction of intention and, unexpectedly, behavior. Past behavior also significantly predicted intention and behavior. Self-identity and belongingness significantly predicted addictive tendencies toward SNWs. Overall, the present study revealed that high-level SNW use is influenced by attitudinal, normative, and self-identity factors, findings that can be used to inform strategies that aim to modify young people's high levels of use or addictive tendencies for SNWs.

Predictive modelling of grain-size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; Müller, H.; von Dobeneck, T.

2018-07-01

In this work, we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine-learning techniques. Non-negative matrix factorization is used to determine grain-size end-members from sediment surface samples. Four end-members were found, which well represent the variety of sediments in the study area. A radial basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Software for predictive microbiology and risk assessment: a description and comparison of tools presented at the ICPMF8 Software Fair.

PubMed

Tenenhaus-Aziza, Fanny; Ellouze, Mariem

2015-02-01

The 8th International Conference on Predictive Modelling in Food was held in Paris, France in September 2013. One of the major topics of this conference was the transfer of knowledge and tools between academics and stakeholders of the food sector. During the conference, a "Software Fair" was held to provide information and demonstrations of predictive microbiology and risk assessment software. This article presents an overall description of the 16 software tools demonstrated at the session and provides a comparison based on several criteria such as the modeling approach, the different modules available (e.g. databases, predictors, fitting tools, risk assessment tools), the studied environmental factors (temperature, pH, aw, etc.), the type of media (broth or food) and the number and type of the provided micro-organisms (pathogens and spoilers). The present study is a guide to help users select the software tools which are most suitable to their specific needs, before they test and explore the tool(s) in more depth. Copyright © 2014 Elsevier Ltd. All rights reserved.

A food-predictive cue attributed with incentive salience engages subcortical afferents and efferents of the paraventricular nucleus of the thalamus.

PubMed

Haight, Joshua L; Fuller, Zachary L; Fraser, Kurt M; Flagel, Shelly B

2017-01-06

The paraventricular nucleus of the thalamus (PVT) has been implicated in behavioral responses to reward-associated cues. However, the precise role of the PVT in these behaviors has been difficult to ascertain since Pavlovian-conditioned cues can act as both predictive and incentive stimuli. The "sign-tracker/goal-tracker" rat model has allowed us to further elucidate the role of the PVT in cue-motivated behaviors, identifying this structure as a critical component of the neural circuitry underlying individual variation in the propensity to attribute incentive salience to reward cues. The current study assessed differences in the engagement of specific PVT afferents and efferents in response to presentation of a food-cue that had been attributed with only predictive value or with both predictive and incentive value. The retrograde tracer fluorogold (FG) was injected into the PVT or the nucleus accumbens (NAc) of rats, and cue-induced c-Fos in FG-labeled cells was quantified. Presentation of a predictive stimulus that had been attributed with incentive value elicited c-Fos in PVT afferents from the lateral hypothalamus, medial amygdala (MeA), and the prelimbic cortex (PrL), as well as posterior PVT efferents to the NAc. PVT afferents from the PrL also showed elevated c-Fos levels following presentation of a predictive stimulus alone. Thus, presentation of an incentive stimulus results in engagement of subcortical brain regions; supporting a role for the hypothalamic-thalamic-striatal axis, as well as the MeA, in mediating responses to incentive stimuli; whereas activity in the PrL to PVT pathway appears to play a role in processing the predictive qualities of reward-paired stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

A food-predictive cue attributed with incentive salience engages subcortical afferents and efferents of the paraventricular nucleus of the thalamus

PubMed Central

Haight, Joshua L.; Fuller, Zachary L.; Fraser, Kurt M.; Flagel, Shelly B.

2016-01-01

The paraventricular nucleus of the thalamus (PVT) has been implicated in behavioral responses to reward-associated cues. However, the precise role of the PVT in these behaviors has been difficult to ascertain since Pavlovian-conditioned cues can act as both predictive and incentive stimuli. The “sign-tracker/goal-tracker” animal model has allowed us to further elucidate the role of the PVT in cue-motivated behaviors, identifying this structure as a critical component of the neural circuitry underlying individual variation in the propensity to attribute incentive salience to reward cues. The current study assessed differences in the engagement of specific PVT afferents and efferents in response to presentation of a food-cue that had been attributed with only predictive value or with both predictive and incentive value. The retrograde tracer fluorogold (FG) was injected into the PVT or the nucleus accumbens (NAc), and cue-induced c-Fos in FG-labeled cells was quantified. Presentation of a predictive stimulus that had been attributed with incentive value elicited c-Fos in PVT afferents from the lateral hypothalamus, medial amygdala (MeA), and the prelimbic cortex (PrL), as well as posterior PVT efferents to the NAc. PVT afferents from the PrL also showed elevated c-Fos levels following presentation of a predictive stimulus alone. Thus, presentation of an incentive stimulus results in engagement of subcortical brain regions; supporting a role for the hypothalamic-thalamic-striatal axis, as well as the MeA, in mediating responses to incentive stimuli; whereas activity in the PrL to PVT pathway appears to play a role in processing the predictive qualities of reward-paired stimuli. PMID:27793779

A new software for prediction of femoral neck fractures.

PubMed

Testi, Debora; Cappello, Angelo; Sgallari, Fiorella; Rumpf, Martin; Viceconti, Marco

2004-08-01

Femoral neck fractures are an important clinical, social and economic problem. Even if many different attempts have been carried out to improve the accuracy predicting the fracture risk, it was demonstrated in retrospective studies that the standard clinical protocol achieves an accuracy of about 65%. A new procedure was developed including for the prediction not only bone mineral density but also geometric and femoral strength information and achieving an accuracy of about 80% in a previous retrospective study. Aim of the present work was to re-engineer research-based procedures and develop a real-time software for the prediction of the risk for femoral fracture. The result was efficient, repeatable and easy to use software for the evaluation of the femoral neck fracture risk to be inserted in the daily clinical practice providing a useful tool for the improvement of fracture prediction.

Comparison of models for predicting the changes in phytoplankton community composition in the receiving water system of an inter-basin water transfer project.

PubMed

Zeng, Qinghui; Liu, Yi; Zhao, Hongtao; Sun, Mingdong; Li, Xuyong

2017-04-01

Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water transfer projects have rarely been studied. In the present study, we used machine learning models to predict the total algal cell densities and changes in phytoplankton community composition in Miyun reservoir caused by the middle route of the South-to-North Water Transfer Project (SNWTP). The model performances of four machine learning models, including regression trees (RT), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) were evaluated and the best model was selected for further prediction. The results showed that the predictive accuracies (Pearson's correlation coefficient) of the models were RF (0.974), ANN (0.951), SVM (0.860), and RT (0.817) in the training step and RF (0.806), ANN (0.734), SVM (0.730), and RT (0.692) in the testing step. Therefore, the RF model was the best method for estimating total algal cell densities. Furthermore, the predicted accuracies of the RF model for dominant phytoplankton phyla (Cyanophyta, Chlorophyta, and Bacillariophyta) in Miyun reservoir ranged from 0.824 to 0.869 in the testing step. The predicted proportions with water transfer of the different phytoplankton phyla ranged from -8.88% to 9.93%, and the predicted dominant phyla with water transfer in each season remained unchanged compared to the phytoplankton succession without water transfer. The results of the present study provide a useful tool for predicting the changes in phytoplankton community caused by water transfer. The method is transferrable to other locations via establishment of models with relevant data to a particular area. Our findings help better understanding the possible changes in aquatic ecosystems influenced by inter-basin water transfer. Copyright © 2017 Elsevier Ltd. All rights reserved.

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

PubMed

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

PubMed Central

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly. PMID:23967112

Approaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling.

PubMed Central

Yang, R S; Thomas, R S; Gustafson, D L; Campain, J; Benjamin, S A; Verhaar, H J; Mumtaz, M M

1998-01-01

Systematic toxicity testing, using conventional toxicology methodologies, of single chemicals and chemical mixtures is highly impractical because of the immense numbers of chemicals and chemical mixtures involved and the limited scientific resources. Therefore, the development of unconventional, efficient, and predictive toxicology methods is imperative. Using carcinogenicity as an end point, we present approaches for developing predictive tools for toxicologic evaluation of chemicals and chemical mixtures relevant to environmental contamination. Central to the approaches presented is the integration of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) and quantitative structure--activity relationship (QSAR) modeling with focused mechanistically based experimental toxicology. In this development, molecular and cellular biomarkers critical to the carcinogenesis process are evaluated quantitatively between different chemicals and/or chemical mixtures. Examples presented include the integration of PBPK/PD and QSAR modeling with a time-course medium-term liver foci assay, molecular biology and cell proliferation studies. Fourier transform infrared spectroscopic analyses of DNA changes, and cancer modeling to assess and attempt to predict the carcinogenicity of the series of 12 chlorobenzene isomers. Also presented is an ongoing effort to develop and apply a similar approach to chemical mixtures using in vitro cell culture (Syrian hamster embryo cell transformation assay and human keratinocytes) methodologies and in vivo studies. The promise and pitfalls of these developments are elaborated. When successfully applied, these approaches may greatly reduce animal usage, personnel, resources, and time required to evaluate the carcinogenicity of chemicals and chemical mixtures. Images Figure 6 PMID:9860897

Don't panic: interpretation bias is predictive of new onsets of panic disorder.

PubMed

Woud, Marcella L; Zhang, Xiao Chi; Becker, Eni S; McNally, Richard J; Margraf, Jürgen

2014-01-01

Psychological models of panic disorder postulate that interpretation of ambiguous material as threatening is an important maintaining factor for the disorder. However, demonstrations of whether such a bias predicts onset of panic disorder are missing. In the present study, we used data from the Dresden Prediction Study, in which a epidemiologic sample of young German women was tested at two time points approximately 17 months apart, allowing the study of biased interpretation as a potential risk factor. At time point one, participants completed an Interpretation Questionnaire including two types of ambiguous scenarios: panic-related and general threat-related. Analyses revealed that a panic-related interpretation bias predicted onset of panic disorder, even after controlling for two established risk factors: anxiety sensitivity and fear of bodily sensations. This is the first prospective study demonstrating the incremental validity of interpretation bias as a predictor of panic disorder onset. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ecology-centered experiences among children and adolescents: A qualitative and quantitative analysis

NASA Astrophysics Data System (ADS)

Orton, Judy

The present research involved two studies that considered ecology-centered experiences (i.e., experiences with living things) as a factor in children's environmental attitudes and behaviors and adolescents' ecological understanding. The first study (Study 1) examined how a community garden provides children in an urban setting the opportunity to learn about ecology through ecology-centered experiences. To do this, I carried out a yearlong ethnographic study at an urban community garden located in a large city in the Southeastern United States. Through participant observations and informal interviews of community garden staff and participants, I found children had opportunities to learn about ecology through ecology-centered experiences (e.g., interaction with animals) along with other experiences (e.g., playing games, reading books). In light of previous research that shows urban children have diminished ecological thought---a pattern of thought that privileges the relationship between living things---because of their lack of ecology-centered experiences (Coley, 2012), the present study may have implications for urban children to learn about ecology. As an extension of Study 1, I carried out a second study (Study 2) to investigate how ecology-centered experiences contribute to adolescents' environmental attitudes and behaviors in light of other contextual factors, namely environmental responsibility support, ecological thought, age and gender. Study 2 addressed three research questions. First, does ecological thought---a pattern of thought that privileges the relationship between living things---predict environmental attitudes and behaviors (EAB)? Results showed ecological thought did not predict EAB, an important finding considering the latent assumptions of previous research about the relationship between these two factors (e.g., Brugger, Kaiser, & Roczen, 2011). Second, do two types of contextual support, ecology-centered experiences (i.e., experiences with living things) and environmental responsibility support (i.e., support through the availability of environmentally responsible models) predict EAB? As predicted, results showed that ecology-centered experiences predicted EAB; yet, when environmental responsibility support was taken into consideration, ecology-centered experiences no longer predicted EAB. These findings suggested environmental responsibility support was a stronger predictor than ecology-centered experiences. Finally, do age and gender predict EAB? Consistent with previous research (e.g., Alp, Ertepiner, Tekkaya, & Yilmaz, 2006), age and gender significantly predicted EAB.

Reliability Estimation for Single-unit Ceramic Crown Restorations

PubMed Central

Lekesiz, H.

2014-01-01

The objective of this study was to evaluate the potential of a survival prediction method for the assessment of ceramic dental restorations. For this purpose, fast-fracture and fatigue reliabilities for 2 bilayer (metal ceramic alloy core veneered with fluorapatite leucite glass-ceramic, d.Sign/d.Sign-67, by Ivoclar; glass-infiltrated alumina core veneered with feldspathic porcelain, VM7/In-Ceram Alumina, by Vita) and 3 monolithic (leucite-reinforced glass-ceramic, Empress, and ProCAD, by Ivoclar; lithium-disilicate glass-ceramic, Empress 2, by Ivoclar) single posterior crown restorations were predicted, and fatigue predictions were compared with the long-term clinical data presented in the literature. Both perfectly bonded and completely debonded cases were analyzed for evaluation of the influence of the adhesive/restoration bonding quality on estimations. Material constants and stress distributions required for predictions were calculated from biaxial tests and finite element analysis, respectively. Based on the predictions, In-Ceram Alumina presents the best fast-fracture resistance, and ProCAD presents a comparable resistance for perfect bonding; however, ProCAD shows a significant reduction of resistance in case of complete debonding. Nevertheless, it is still better than Empress and comparable with Empress 2. In-Ceram Alumina and d.Sign have the highest long-term reliability, with almost 100% survivability even after 10 years. When compared with clinical failure rates reported in the literature, predictions show a promising match with clinical data, and this indicates the soundness of the settings used in the proposed predictions. PMID:25048249

Numerical description of cavitation on axisymmetric bodies

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

Hickox, C.E.; Hailey, C.E.; Wolfe, W.P.

1988-01-01

This paper reports on ongoing studies which are directed toward the development of predictive techniques for the modeling of steady cavitation on axisymmetric bodies. The primary goal of the modeling effort is the prediction of cavity shape and pressure distribution from which forces and moments can be calculated. Here we present an overview of the modeling techniques developed and compare predictions with experimental data obtained from water tunnel tests for both limited and supercavitation. 14 refs., 4 figs.

Serious conditions for ED elderly fall patients: a secondary analysis of the Basel Non-Specific Complaints study.

PubMed

Liu, Shan W; Sri-On, Jiraporn; Tirrell, Gregory Philip; Nickel, Christian; Bingisser, Roland

2016-08-01

Falls among older adults are a public health problem and are multifactorial. We sought to determine whether falls predict more serious conditions in older adult patients presenting to the emergency department (ED) with a "nonspecific complaint" (NSC). A secondary objective was to examine what factors predicted serious conditions among older adult patients with a fall. This study was a secondary analysis of a prospective delayed-type cross-sectional diagnostic study that included a 30-day follow-up. We included patients 65 years and older who presented to the ED from May 2007 and July 2011 with a NSC and had an Emergency Severity Index score of 2 or 3. We then compared the serious conditions among older adults who presented to the ED with a fall with those who did not fall in a cohort of patients with NSC. We had 1111 patients enrolled in our study; 518 (47%) of them had fallen. We found that 310 (60%) of elderly fall patients vs 349 (59%) of nonfall patients had a 30-day serious condition (P=.74). In multiple logistic regression analysis, falls did not predict serious conditions or 30-day mortality among all NSC patients. Among fall patients, male sex, diuretic use, and generalized weakness predicted serious conditions. Fall patients share many features with nonfall NSC patient. However, falls did not increase the risk of serious conditions. Falls in the elderly could be considered under the broader entity of NSC. Copyright © 2016 Elsevier Inc. All rights reserved.

[Determination of prognostic value of the OESIL risk score at 6 months in a Colombian cohort with syncope evaluated in the emergency department; first Latin American experience].

PubMed

Díaz-Tribaldos, Diana Carolina; Mora, Guillermo; Olaya, Alejandro; Marín, Jorge; Sierra Matamoros, Fabio

2017-07-14

To establish the prognostic value, with sensitivity, specificity, positive predictive value, and negative predictive value for the OESIL syncope risk score to predict the presentation of severe outcomes (death, invasive interventions, and readmission) after 6 months of observation in adults who consulted the emergency department due to syncope. Observational, prospective, and multicentre study with enrolment of subjects older than 18 years, who consulted in the emergency department due to syncope. A record was mad of the demographic and clinical information of all patients. The OESIL risk score was calculated, and severe patient outcomes were followed up during a 6 month period using telephone contact. A total of 161 patients met the inclusion criteria and were followed up for 6 months. A score above or equal to 2 in the risk score, classified as high risk, was present in 72% of the patients. The characteristics of the risk score to predict the combined outcome of mortality, invasive interventions, and readmission for a score above or equal to 2 were 75.7, 30.5, 43.1, and 64.4% for sensitivity, specificity, positive predictive value, and negative predictive value, respectively. A score above or equal to 2 in the OESIL risk score applied in Colombian population was of limited use to predict the studied severe outcomes. This score will be unable to discriminate between patients that benefit of early admission and further clinical studies. Copyright © 2017 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

Prediction of iron oxide contents using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Marques, José, Jr.; Arantes Camargo, Livia

2015-04-01

Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.

Predictors of self-rated health: a 12-month prospective study of IT and media workers.

PubMed

Hasson, Dan; Arnetz, Bengt B; Theorell, Töres; Anderberg, Ulla Maria

2006-07-31

The aim of the present study was to determine health-related risk and salutogenic factors and to use these to construct prediction models for future self-rated health (SRH), i.e. find possible characteristics predicting individuals improving or worsening in SRH over time (0-12 months). A prospective study was conducted with measurements (physiological markers and self-ratings) at 0, 6 and 12 months, involving 303 employees (187 men and 116 women, age 23-64) from four information technology and two media companies. There were a multitude of statistically significant cross-sectional correlations (Spearman's Rho) between SRH and other self-ratings as well as physiological markers. Predictors of future SRH were baseline ratings of SRH, self-esteem and social support (logistic regression), and SRH, sleep quality and sense of coherence (linear regression). The results of the present study indicate that baseline SRH and other self-ratings are predictive of future SRH. It is cautiously implied that SRH, self-esteem, social support, sleep quality and sense of coherence might be predictors of future SRH and therefore possibly also of various future health outcomes.

The Effect of Basis Selection on Static and Random Acoustic Response Prediction Using a Nonlinear Modal Simulation

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Przekop, Adam

2005-01-01

An investigation of the effect of basis selection on geometric nonlinear response prediction using a reduced-order nonlinear modal simulation is presented. The accuracy is dictated by the selection of the basis used to determine the nonlinear modal stiffness. This study considers a suite of available bases including bending modes only, bending and membrane modes, coupled bending and companion modes, and uncoupled bending and companion modes. The nonlinear modal simulation presented is broadly applicable and is demonstrated for nonlinear quasi-static and random acoustic response of flat beam and plate structures with isotropic material properties. Reduced-order analysis predictions are compared with those made using a numerical simulation in physical degrees-of-freedom to quantify the error associated with the selected modal bases. Bending and membrane responses are separately presented to help differentiate the bases.

Shuttle data book: SRM fragment velocity model. Presented to the SRB Fragment Model Review Panel

NASA Technical Reports Server (NTRS)

1989-01-01

This study was undertaken to determine the velocity of fragments generated by the range safety destruction (RSD) or random failure of a Space Transportation System (STS) Solid Rocket Motor (SRM). The specific requirement was to provide a fragment model for use in those Galileo and Ulysses RTG safety analyses concerned with possible fragment impact on the spacecraft radioisotope thermoelectric generators (RTGS). Good agreement was obtained between predictions and observations for fragment velocity, velocity distributions, azimuths, and rotation rates. Based on this agreement with the entire data base, the model was used to predict the probable fragment environments which would occur in the event of an STS-SRM RSD or randon failure at 10, 74, 84 and 110 seconds. The results of these predictions are the basis of the fragment environments presented in the Shuttle Data Book (NSTS-08116). The information presented here is in viewgraph form.

Exploring simple, transparent, interpretable and predictive QSAR models for classification and quantitative prediction of rat toxicity of ionic liquids using OECD recommended guidelines.

PubMed

Das, Rudra Narayan; Roy, Kunal; Popelier, Paul L A

2015-11-01

The present study explores the chemical attributes of diverse ionic liquids responsible for their cytotoxicity in a rat leukemia cell line (IPC-81) by developing predictive classification as well as regression-based mathematical models. Simple and interpretable descriptors derived from a two-dimensional representation of the chemical structures along with quantum topological molecular similarity indices have been used for model development, employing unambiguous modeling strategies that strictly obey the guidelines of the Organization for Economic Co-operation and Development (OECD) for quantitative structure-activity relationship (QSAR) analysis. The structure-toxicity relationships that emerged from both classification and regression-based models were in accordance with the findings of some previous studies. The models suggested that the cytotoxicity of ionic liquids is dependent on the cationic surfactant action, long alkyl side chains, cationic lipophilicity as well as aromaticity, the presence of a dialkylamino substituent at the 4-position of the pyridinium nucleus and a bulky anionic moiety. The models have been transparently presented in the form of equations, thus allowing their easy transferability in accordance with the OECD guidelines. The models have also been subjected to rigorous validation tests proving their predictive potential and can hence be used for designing novel and "greener" ionic liquids. The major strength of the present study lies in the use of a diverse and large dataset, use of simple reproducible descriptors and compliance with the OECD norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Performance prediction: A case study using a multi-ring KSR-1 machine

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhu, Jianping

1995-01-01

While computers with tens of thousands of processors have successfully delivered high performance power for solving some of the so-called 'grand-challenge' applications, the notion of scalability is becoming an important metric in the evaluation of parallel machine architectures and algorithms. In this study, the prediction of scalability and its application are carefully investigated. A simple formula is presented to show the relation between scalability, single processor computing power, and degradation of parallelism. A case study is conducted on a multi-ring KSR1 shared virtual memory machine. Experimental and theoretical results show that the influence of topology variation of an architecture is predictable. Therefore, the performance of an algorithm on a sophisticated, heirarchical architecture can be predicted and the best algorithm-machine combination can be selected for a given application.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A mathematical model for the interactive behavior of sulfate-reducing bacteria and methanogens during anaerobic digestion.

PubMed

Ahammad, S Ziauddin; Gomes, James; Sreekrishnan, T R

2011-09-01

Anaerobic degradation of waste involves different classes of microorganisms, and there are different types of interactions among them for substrates, terminal electron acceptors, and so on. A mathematical model is developed based on the mass balance of different substrates, products, and microbes present in the system to study the interaction between methanogens and sulfate-reducing bacteria (SRB). The performance of major microbial consortia present in the system, such as propionate-utilizing acetogens, butyrate-utilizing acetogens, acetoclastic methanogens, hydrogen-utilizing methanogens, and SRB were considered and analyzed in the model. Different substrates consumed and products formed during the process also were considered in the model. The experimental observations and model predictions showed very good prediction capabilities of the model. Model prediction was validated statistically. It was observed that the model-predicted values matched the experimental data very closely, with an average error of 3.9%.

Statistical mechanics of ribbons under bending and twisting torques.

PubMed

Sinha, Supurna; Samuel, Joseph

2013-11-20

We present an analytical study of ribbons subjected to an external torque. We first describe the elastic response of a ribbon within a purely mechanical framework. We then study the role of thermal fluctuations in modifying its elastic response. We predict the moment-angle relation of bent and twisted ribbons. Such a study is expected to shed light on the role of twist in DNA looping and on bending elasticity of twisted graphene ribbons. Our quantitative predictions can be tested against future single molecule experiments.

Predicting Behavior Assessment System for Children-Second Edition Self-Report of Personality Child Form Results Using the Behavioral and Emotional Screening System Student Form: A Replication Study with an Urban, Predominantly Latino/a Sample

ERIC Educational Resources Information Center

Kiperman, Sarah; Black, Mary S.; McGill, Tia M.; Harrell-Williams, Leigh M.; Kamphaus, Randy W.

2014-01-01

This study assesses the ability of a brief screening form, the Behavioral and Emotional Screening System-Student Form (BESS-SF), to predict scores on the much longer form from which it was derived: the Behavior Assessment System for Children-Second Edition Self-Report of Personality-Child Form (BASC-2-SRP-C). The present study replicates a former…

Coregistration of Eye Movements and EEG in Natural Reading: Analyses and Review

ERIC Educational Resources Information Center

Dimigen, Olaf; Sommer, Werner; Hohlfeld, Annette; Jacobs, Arthur M.; Kliegl, Reinhold

2011-01-01

Brain-electric correlates of reading have traditionally been studied with word-by-word presentation, a condition that eliminates important aspects of the normal reading process and precludes direct comparisons between neural activity and oculomotor behavior. In the present study, we investigated effects of word predictability on eye movements (EM)…

Building Links between Early Socioeconomic Status, Cognitive Ability, and Math and Science Achievement

ERIC Educational Resources Information Center

Blums, Angela; Belsky, Jay; Grimm, Kevin; Chen, Zhe

2017-01-01

The present study examined whether and how socioeconomic status (SES) predicts school achievement in science, technology, engineering, and math (STEM) using structural equation modeling and data from the National Institute of Child Health and Human Development Study of Child Care and Youth Development. The present inquiry addresses gaps in…

Efficacy of changing physics misconceptions held by ninth grade students at varying developmental levels through teacher addition of a prediction phase to the learning cycle

NASA Astrophysics Data System (ADS)

Oglesby, Michael L.

This study examines the efficacy in correcting student misconceptions about science concepts by using the pedagogical method of asking students to make a prediction in science laboratory lessons for students within pre-formal, transitional, or formal stages of cognitive development. The subjects were students (n = 235) enrolled in ninth grade physical science classes (n=15) in one high school of an urban profile school district. The four freshmen physical science teachers who were part of the study routinely taught the concepts in the study as a part of the normal curriculum during the time of the school year in which the research was conducted. Classrooms representing approximately half of the students were presented with a prediction phase at the start of each of ten learning cycle lesson. The other classrooms were not presented with a prediction phase. Students were pre and post tested using a 40 question instrument based on the Force Concept Inventory augmented with questions on the concepts taught during the period of the study. Students were also tested using the Test of Scientific Reasoning to determine their cognitive developmental level. Results showed 182 of the students to be cognitively pre-formal, 50 to be transitional, and only 3 to be cognitively formal. There were significantly higher gains (p < .05) for the formal group over the transitional group and for the transitional group over the Pre-formal group. However, there were not significantly higher gains (p > .05) for the total students having a prediction phase compared to those not having a prediction phase. Neither were there significant gains (p > .05) within the pre-formal group or within the transitional group. There were too few students within the formal group for meaningful results.

Motivated reasoning in the prediction of sports outcomes and the belief in the "hot hand".

PubMed

Braga, João P N; Mata, André; Ferreira, Mário B; Sherman, Steven J

2017-12-01

The present paper explores the role of motivation to observe a certain outcome in people's predictions, causal attributions, and beliefs about a streak of binary outcomes (basketball scoring shots). In two studies we found that positive streaks (points scored by the participants' favourite team) lead participants to predict the streak's continuation (belief in the hot hand), but negative streaks lead to predictions of its end (gambler's fallacy). More importantly, these wishful predictions are supported by strategic attributions and beliefs about how and why a streak might unfold. Results suggest that the effect of motivation on predictions is mediated by a serial path via causal attributions to the teams at play and belief in the hot hand.

Brief report: a cost analysis of neuraxial anesthesia to facilitate external cephalic version for breech fetal presentation.

PubMed

Carvalho, Brendan; Tan, Jonathan M; Macario, Alex; El-Sayed, Yasser Y; Sultan, Pervez

2013-07-01

In this study, we sought to determine whether neuraxial anesthesia to facilitate external cephalic version (ECV) increased delivery costs for breech fetal presentation. Using a computer cost model, which considers possible outcomes and probability uncertainties at the same time, we estimated total expected delivery costs for breech presentation managed by a trial of ECV with and without neuraxial anesthesia. From published studies, the average probability of successful ECV with neuraxial anesthesia was 60% (with individual studies ranging from 44% to 87%) compared with 38% (with individual studies ranging from 31% to 58%) without neuraxial anesthesia. The mean expected total delivery costs, including the cost of attempting/performing ECV with anesthesia, equaled $8931 (2.5th-97.5th percentile prediction interval $8541-$9252). The cost was $9207 (2.5th-97.5th percentile prediction interval $8896-$9419) if ECV was attempted/performed without anesthesia. The expected mean incremental difference between the total cost of delivery that includes ECV with anesthesia and ECV without anesthesia was $-276 (2.5th-97.5th percentile prediction interval $-720 to $112). The total cost of delivery in women with breech presentation may be decreased (up to $720) or increased (up to $112) if ECV is attempted/performed with neuraxial anesthesia compared with ECV without neuraxial anesthesia. Increased ECV success with neuraxial anesthesia and the subsequent reduction in breech cesarean delivery rate offset the costs of providing anesthesia to facilitate ECV.

A theoretical and experimental technique to measure fracture properties in viscoelastic solids

NASA Astrophysics Data System (ADS)

Freitas, Felipe Araujo Colares De

Prediction of crack growth in engineering structures is necessary for better analysis and design. However, this prediction becomes quite complex for certain materials in which the fracture behavior is both rate and path dependent. Asphaltic materials used in pavements have that intrinsic complexity in their behavior. A lot of research effort has been devoted to better understanding viscoelastic behavior and fracture in such materials. This dissertation presents a further refinement of an experimental test setup, which is significantly different from standard testing protocols, to measure viscoelastic and fracture properties of nonlinear viscoelastic solids, such as asphaltic materials. The results presented herein are primarily for experiments with asphalt, but the test procedure can be used for other viscoelastic materials as well. Even though the test is designed as a fracture test, experiments on the investigated materials have uncovered very complex phenomena prior to fracture. Viscoelasticity and micromechanics are used to explain some of the physical phenomena observed in the tests. The material behavior prior to fracture includes both viscoelastic behavior and a necking effect, which is further discussed in the appendix of the present study. The dissertation outlines a theoretical model for the prediction of tractions ahead of the crack tip. The major contribution herein lies in the development of the experimental procedure for evaluating the material parameters necessary for deploying the model in the prediction of ductile crack growth. Finally, predictions of crack growth in a double cantilever beam specimens and asphalt concrete samples are presented in order to demonstrate the power of this approach for predicting crack growth in viscoelastic media.

OP007. PLGF in combination with other commonly utilised tests and other biomarkers for predicting need for delivery for pre-eclampsia within 14days in women presenting prior to 35weeks' gestation.

PubMed

Lucy, Chappell; Suzy, Duckworth; Melanie, Griffin; Paul, Seed; Christopher, Redman; Andrew, Shennan

2013-04-01

Current means of assessing women presenting with suspected pre-eclampsia using BP and proteinuria are of limited use in predicting need for imminent delivery. We undertook a prospective multicentre study to determine diagnostic accuracy of PlGF <5th centile (Triage assay) and other candidate biomarkers in women presenting with suspected pre-eclampsia at 20-35weeks' gestation, in determining need for delivery for pre-eclampsia within 14days. We calculated ROC curves for predictive potential and undertook principal factor analysis to determine additional predictive ability for biomarker combinations. In 287 women enrolled prior to 35weeks, ROC area (0.88, SE 0.03) for PlGF <5th centile for pre-eclampsia requiring delivery within 14days was greater than all other commonly utilised tests (systolic and diastolic BP, urate, ALT), either singly (range 0.58-0.68), or in combination (0.69) (p<0.001 for all comparisons), and was greater than that of all other biomarkers; addition of 2 other biomarker panels (either procalcitonin, nephrin and BNP; or cystatin and PAPP-A) increased ROC area to 0.90 but these biomarkers had limited predictive ability on their own. In women presenting prior to 35weeks' gestation with suspected pre-eclampsia, low PlGF has a greater ROC area than other commonly utilised tests. Additional biomarkers add only a small increment to the predictive value of a single PlGF measurement. Copyright © 2013. Published by Elsevier B.V.

A Point System for Predicting 10-Year Risk of Developing Type 2 Diabetes Mellitus in Japanese Men: Aichi Workers' Cohort Study.

PubMed

Yatsuya, Hiroshi; Li, Yuanying; Hirakawa, Yoshihisa; Ota, Atsuhiko; Matsunaga, Masaaki; Haregot, Hilawe Esayas; Chiang, Chifa; Zhang, Yan; Tamakoshi, Koji; Toyoshima, Hideaki; Aoyama, Atsuko

2018-03-17

Relatively little evidence exists for type 2 diabetes mellitus (T2DM) prediction models from long-term follow-up studies in East Asians. This study aims to develop a point-based prediction model for 10-year risk of developing T2DM in middle-aged Japanese men. We followed 3,540 male participants of Aichi Workers' Cohort Study, who were aged 35-64 years and were free of diabetes in 2002, until March 31, 2015. Baseline age, body mass index (BMI), smoking status, alcohol consumption, regular exercise, medication for dyslipidemia, diabetes family history, and blood levels of triglycerides (TG), high density lipoprotein cholesterol (HDLC) and fasting blood glucose (FBG) were examined using Cox proportional hazard model. Variables significantly associated with T2DM in univariable models were simultaneously entered in a multivariable model for determination of the final model using backward variable selection. Performance of an existing T2DM model when applied to the current dataset was compared to that obtained in the present study's model. During the median follow-up of 12.2 years, 342 incident T2DM cases were documented. The prediction system using points assigned to age, BMI, smoking status, diabetes family history, and TG and FBG showed reasonable discrimination (c-index: 0.77) and goodness-of-fit (Hosmer-Lemeshow test, P = 0.22). The present model outperformed the previous one in the present subjects. The point system, once validated in the other populations, could be applied to middle-aged Japanese male workers to identify those at high risk of developing T2DM. In addition, further investigation is also required to examine whether the use of this system will reduce incidence.

Relationships between the decoupled and coupled transfer functions: Theoretical studies and experimental validation

NASA Astrophysics Data System (ADS)

Wang, Zengwei; Zhu, Ping; Liu, Zhao

2018-01-01

A generalized method for predicting the decoupled transfer functions based on in-situ transfer functions is proposed. The method allows predicting the decoupled transfer functions using coupled transfer functions, without disassembling the system. Two ways to derive relationships between the decoupled and coupled transfer functions are presented. Issues related to immeasurability of coupled transfer functions are also discussed. The proposed method is validated by numerical and experimental case studies.

Investigating Students' Attitude and Intention to Use Social Software in Higher Institution of Learning in Malaysia

ERIC Educational Resources Information Center

Shittu, Ahmed Tajudeen; Basha, Kamal Madarsha; AbdulRahman, Nik Suryani Nik; Ahmad, Tunku Badariah Tunku

2011-01-01

Purpose: Social software usage is growing at an exponential rate among the present generation of students. Yet, there is paucity of empirical study to understand the determinant of its use in the present setting of this study. This study, therefore, seeks to investigate factors that predict students' attitudes and intentions to use this…

Collaboratory for the Study of Earthquake Predictability

NASA Astrophysics Data System (ADS)

Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

2006-12-01

Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

Helicopter Rotor Noise Prediction: Background, Current Status, and Future Direction

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1997-01-01

Helicopter noise prediction is increasingly important. The purpose of this viewgraph presentation is to: 1) Put into perspective the recent progress; 2) Outline current prediction capabilities; 3) Forecast direction of future prediction research; 4) Identify rotorcraft noise prediction needs. The presentation includes an historical perspective, a description of governing equations, and the current status of source noise prediction.

Do proposed facial expressions of contempt, shame, embarrassment, and compassion communicate the predicted emotion?

PubMed

Widen, Sherri C; Christy, Anita M; Hewett, Kristen; Russell, James A

2011-08-01

Shame, embarrassment, compassion, and contempt have been considered candidates for the status of basic emotions on the grounds that each has a recognisable facial expression. In two studies (N=88, N=60) on recognition of these four facial expressions, observers showed moderate agreement on the predicted emotion when assessed with forced choice (58%; 42%), but low agreement when assessed with free labelling (18%; 16%). Thus, even though some observers endorsed the predicted emotion when it was presented in a list, over 80% spontaneously interpreted these faces in a way other than the predicted emotion.

Neurocognition and community outcome in schizophrenia: long-term predictive validity.

PubMed

Fujii, Daryl E; Wylie, A Michael

2003-02-01

The present study examined the predictive validity of neuropsychological measures to functional outcome in 26 schizophrenic patients 15-plus year post-testing. Outcome measures included score on the Resource Associated Functional Level Scale (RAFLS), number of state hospital admissions, and total duration of state hospital inpatient stay. Results of several stepwise multiple regressions revealed that verbal memory significantly predicted RAFLS score, accounting for nearly half of the variance. Trails B significantly predicted duration of state hospital inpatient status. Discussion focused on the utility of these measures for clinicians and system planners. Copyright 2002 Elsevier Science B.V.

Predicting school sense of community: students' perceptions at two Catholic universities.

PubMed

Bottom, Todd L; Ferrari, Joseph R; Matteo, Elizabeth; Todd, Nathan R

2013-01-01

Understanding the factors that predict sense of community (SOC) among college students has important implications for higher education policy and practice. The present study determined whether perceptions of inclusion and religious pluralism across 2,199 university students' (1,442 women, 757 men; M age = 23.42, SD =7.84) at two Catholic universities predicted levels of school sense of community (SSOC). As expected, results indicated that perceptions of both inclusion and religious pluralism significantly predicted SSOC. However, mixed results were found regarding the interaction of university setting with inclusion and religious pluralism. Limitations and future directions for research are discussed.

The accuracy with which adults who do not stutter predict stuttering-related communication attitudes.

PubMed

Logan, Kenneth J; Willis, Julie R

2011-12-01

The purpose of this study was to examine the extent to which adults who do not stutter can predict communication-related attitudes of adults who do stutter. 40 participants (mean age of 22.5 years) evaluated speech samples from an adult with mild stuttering and an adult with severe stuttering via audio-only (n=20) or audio-visual (n=20) modes to predict how the adults had responded on the S24 scale of communication attitudes. Participants correctly predicted which speaker had the more favorable S24 score, and the predicted scores were significantly different between the severity conditions. Across the four subgroups, predicted S24 scores differed from actual scores by 4-9 points. Predicted values were greater than the actual values for 3 of 4 subgroups, but still relatively positive in relation to the S24 norm sample. Stimulus presentation mode interacted with stuttering severity to affect prediction accuracy. The participants predicted the speakers' negative self-attributions more accurately than their positive self-attributions. Findings suggest that adults who do not stutter estimate the communication-related attitudes of specific adults who stutter in a manner that is generally accurate, though, in some conditions, somewhat less favorable than the speaker's actual ratings. At a group level, adults who do not stutter demonstrate the ability to discern minimal versus average levels of attitudinal impact for speakers who stutter. The participants' complex prediction patterns are discussed in relation to stereotype accuracy and classic views of negative stereotyping. The reader will be able to (a) summarize main findings on research related to listeners' attitudes toward people who stutter, (b) describe the extent to which people who do not stutter can predict the communication attitudes of people who do stutter; and (c) discuss how findings from the present study relate to previous findings on stereotypes about people who stutter. Copyright © 2011 Elsevier Inc. All rights reserved.

The emergency department prediction of disposition (EPOD) study.

PubMed

Vaghasiya, Milan R; Murphy, Margaret; O'Flynn, Daniel; Shetty, Amith

2014-11-01

Emergency departments (ED) continue to evolve models of care and streaming as interventions to tackle the effects of access block and overcrowding. Tertiary ED may be able to design patient-flow based on predicted dispositions in the department. Segregating discharge-stream patients may help develop patient-flows within the department, which is less affected by availability of beds in a hospital. We aim to determine if triage nurses and ED doctors can predict disposition outcomes early in the patient journey and thus lead to successful streaming of patients in the ED. During this study, triage nurses and ED doctors anonymously predicted disposition outcomes for patients presenting to triage after their brief assessments. Patient disposition at the 24-h post ED presentation was considered as the actual outcome and compared against predicted outcomes. Triage nurses were able to predict actual discharges of 445 patients out of 490 patients with a positive predictive value (PPV) of 90.8% (95% CI 87.8-93.2%). ED registrars were able to predict actual discharges of 85 patients out of 93 patients with PPV of 91.4% (95% CI 83.3-95.9%). ED consultants were able to predict actual discharges of 111 patients out of 118 patients with PPV 94.1% (95% CI 87.7-97.4%). PPVs for admission among ED consultants, ED registrars and Triage nurses were 59.7%, 54.4% and 48.5% respectively. Triage nurses, ED consultants and ED registrars are able to predict a patient's discharge disposition at triage with high levels of confidence. Triage nurses, ED consultants, and ED registrars can predict patients who are likely to be admitted with equal ability. This data may be used to develop specific admission and discharge streams based on early decision-making in EDs by triage nurses, ED registrars or ED consultants. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Tile prediction schemes for wide area motion imagery maps in GIS

NASA Astrophysics Data System (ADS)

Michael, Chris J.; Lin, Bruce Y.

2017-11-01

Wide-area surveillance, traffic monitoring, and emergency management are just several of many applications benefiting from the incorporation of Wide-Area Motion Imagery (WAMI) maps into geographic information systems. Though the use of motion imagery as a GIS base map via the Web Map Service (WMS) standard is not a new concept, effectively streaming imagery is particularly challenging due to its large scale and the multidimensionally interactive nature of clients that use WMS. Ineffective streaming from a server to one or more clients can unnecessarily overwhelm network bandwidth and cause frustratingly large amounts of latency in visualization to the user. Seamlessly streaming WAMI through GIS requires good prediction to accurately guess the tiles of the video that will be traversed in the near future. In this study, we present an experimental framework for such prediction schemes by presenting a stochastic interaction model that represents a human user's interaction with a GIS video map. We then propose several algorithms by which the tiles of the stream may be predicted. Results collected both within the experimental framework and using human analyst trajectories show that, though each algorithm thrives under certain constraints, the novel Markovian algorithm yields the best results overall. Furthermore, we make the argument that the proposed experimental framework is sufficient for the study of these prediction schemes.

Estimating thermal performance curves from repeated field observations

USGS Publications Warehouse

Childress, Evan; Letcher, Benjamin H.

2017-01-01

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

Genomic selection in sugar beet breeding populations

PubMed Central

2013-01-01

Background Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. Results We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. Conclusions The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding. PMID:24047500

Numerical study of combustion processes in afterburners

NASA Technical Reports Server (NTRS)

Zhou, Xiaoqing; Zhang, Xiaochun

1986-01-01

Mathematical models and numerical methods are presented for computer modeling of aeroengine afterburners. A computer code GEMCHIP is described briefly. The algorithms SIMPLER, for gas flow predictions, and DROPLET, for droplet flow calculations, are incorporated in this code. The block correction technique is adopted to facilitate convergence. The method of handling irregular shapes of combustors and flameholders is described. The predicted results for a low-bypass-ratio turbofan afterburner in the cases of gaseous combustion and multiphase spray combustion are provided and analyzed, and engineering guides for afterburner optimization are presented.

A Bayesian network model for predicting pregnancy after in vitro fertilization.

PubMed

Corani, G; Magli, C; Giusti, A; Gianaroli, L; Gambardella, L M

2013-11-01

We present a Bayesian network model for predicting the outcome of in vitro fertilization (IVF). The problem is characterized by a particular missingness process; we propose a simple but effective averaging approach which improves parameter estimates compared to the traditional MAP estimation. We present results with generated data and the analysis of a real data set. Moreover, we assess by means of a simulation study the effectiveness of the model in supporting the selection of the embryos to be transferred. © 2013 Elsevier Ltd. All rights reserved.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-01-20

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-02-01

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-06

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD)

PubMed Central

Reitsma, Johannes B.; Altman, Douglas G.; Moons, Karel G.M.

2015-01-01

Background— Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. Methods— The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. Results— The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. Conclusions— To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). PMID:25561516

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement

PubMed Central

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-01-01

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). PMID:25562432

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-02-01

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 Royal College of Obstetricians and Gynaecologists.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-13

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 The Authors.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-06

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-02-01

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). Copyright © 2015 Elsevier Inc. All rights reserved.

The study on the new approach to the prediction of the solar flares: The statistical relation from the SOHO archive

NASA Astrophysics Data System (ADS)

Lee, S.; Oh, S.; Lee, J.; Hong, S.

2013-12-01

We have investigated the statistical relationship of the solar active region to predict the solar flare event analyzing the sunspot catalogue, which has been newly constructed from the SOHO MDI observation data during the period from 1996 to 2011 (Solar Cycle 23 & 24) by ASSA(Automatic Solar Synoptic Analyzer) algorithms. The prediction relation has been made by machine-learning algorithms to establish a short- term flare prediction model for operational use in near future. In this study, continuum and magnetogram images observed by SOHO has been processed to yield 15-year sunspot group catalogue that contains various physical parameters such as sunspot area, extent, asymmetry measure of largest penumbral sunspot, roughness of magnetic neutral line as well as McIntosh and Mt. Wilson classification results.The latest result of our study will be presented and the new approach to the prediction of the solar flare will be discussed.

Application of backpropagation artificial neural network prediction model for the PAH bioremediation of polluted soil.

PubMed

Olawoyin, Richard

2016-10-01

The backpropagation (BP) artificial neural network (ANN) is a renowned and extensively functional mathematical tool used for time-series predictions and approximations; which also define results for non-linear functions. ANNs are vital tools in the predictions of toxicant levels, such as polycyclic aromatic hydrocarbons (PAH) potentially derived from anthropogenic activities in the microenvironment. In the present work, BP ANN was used as a prediction tool to study the potential toxicity of PAH carcinogens (PAHcarc) in soils. Soil samples (16 × 4 = 64) were collected from locations in South-southern Nigeria. The concentration of PAHcarc in laboratory cultivated white melilot, Melilotus alba roots grown on treated soils was predicted using ANN model training. Results indicated the Levenberg-Marquardt back-propagation training algorithm converged in 2.5E+04 epochs at an average RMSE value of 1.06E-06. The averagedR(2) comparison between the measured and predicted outputs was 0.9994. It may be deduced from this study that, analytical processes involving environmental risk assessment as used in this study can successfully provide prompt prediction and source identification of major soil toxicants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Individual differences in fluid intelligence predicts inattentional blindness in a sample of older adults: a preliminary study.

PubMed

O'Shea, Deirdre M; Fieo, Robert A

2015-07-01

Previous research has shown that aging increases susceptibility to inattentional blindness (Graham and Burke, Psychol Aging 26:162, 2011) as well as individual differences in cognitive ability related to working memory and executive functions in separate studies. Therefore, the present study was conducted in an attempt to bridge a gap that involved investigating 'age-sensitive' cognitive abilities that may predict inattentional blindness in a sample of older adults. We investigated whether individual differences in general fluid intelligence and speed of processing would predict inattentional blindness in our sample of older adults. Thirty-six healthy older adults took part in the study. Using the inattentional blindness paradigm developed by Most et al. (Psychol Rev 112:217, 2005), we investigated whether rates of inattentional blindness could be predicted by participant's performance on the Raven's Advanced Progressive Matrices and a choice-reaction time task. A Mann-Whitney U test revealed that a higher score on the Raven's Advanced Progressive Matrices was significantly associated with lower incidences of inattentional blindness. However, a t test revealed that choice-reaction times were not significantly associated with inattentional blindness. Preliminary results from the present study suggest that individual differences in general fluid intelligence are predictive of inattentional blindness in older adults but not speed of processing. Moreover, our findings are consistent with previous studies that have suggested executive attention control may be the source of these individual differences. These findings also highlight the association between attention and general fluid intelligence and how it may impact environmental awareness. Future research would benefit from repeating these analyses in a larger sample and also including a younger comparison group.

Remote sensing for prediction of 1-year post-fire ecosystem condition

Treesearch

Leigh B. Lentile; Alistair M. S. Smith; Andrew T. Hudak; Penelope Morgan; Michael J. Bobbitt; Sarah A. Lewis; Peter R. Robichaud

2009-01-01

Appropriate use of satellite data in predicting >1 year post-fire effects requires remote measurement of surface properties that can be mechanistically related to ground measures of post-fire condition. The present study of burned ponderosa pine (Pinus ponderosa) forests in the Black Hills of South Dakota evaluates whether immediate fractional cover estimates of...

The Bidirectional Nature of Narrative Scaffolding: Latino Caregivers' Elaboration While Creating Stories from a Picture Book

ERIC Educational Resources Information Center

Schick, Adina R.; Melzi, Gigliana; Obregón, Javanna

2017-01-01

Although caregiver narrative elaboration is seen as a critical dimension for children's development of narrative skills, research has yet to show a predictive relation between caregiver elaboration and child outcomes for low-income Latino children. The present study explored whether specific types of narrative elaboration were predicted by and…

Extreme Appraisals of Internal States and Bipolar Symptoms: The Hypomanic Attitudes and Positive Predictions Inventory

ERIC Educational Resources Information Center

Dodd, Alyson L.; Mansell, Warren; Morrison, Anthony P.; Tai, Sara

2011-01-01

The Hypomanic Attitudes and Positive Predictions Inventory (HAPPI; W. Mansell, 2006) was developed to assess multiple, extreme, self-relevant appraisals of internal states. The present study aimed to validate the HAPPI in a clinical sample. Participants (N = 50) with a diagnosis of bipolar disorder (confirmed by a structured clinical interview)…

A Comparison of Three Strategies for Scale Construction to Predict a Specific Behavioral Outcome

ERIC Educational Resources Information Center

Garb, Howard N.; Wood, James M.; Fiedler, Edna R.

2011-01-01

Using 65 items from a mental health screening questionnaire, the History Opinion Inventory-Revised (HOI-R), the present study compared three strategies of scale construction--(1) internal (based on factor analysis), (2) external (based on empirical performance) and (3) intuitive (based on clinicians' opinion)--to predict whether 203,595 U.S. Air…

Stages of Change or Changes of Stage? Predicting Transitions in Transtheoretical Model Stages in Relation to Healthy Food Choice

ERIC Educational Resources Information Center

Armitage, Christopher J.; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A.

2004-01-01

Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N=787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that…

Cumulative Psychosocial and Medical Risk as Predictors of Early Infant Development and Parenting Stress in an African-American Preterm Sample

ERIC Educational Resources Information Center

Candelaria, Margo A.; O'Connell, Melissa A.; Teti, Douglas M.

2006-01-01

The present study examined predictive linkages between cumulative psychosocial and medical risk, assessed neonatally, and infant development and parenting stress at 4 months of infant corrected age. Predominantly low-income, African-American mothers and their preterm infants served as participants. Cumulative psychosocial risk predicted early…

Predicting Students' Homework Environment Management at the Secondary School Level

ERIC Educational Resources Information Center

Xu, Jianzhong

2012-01-01

The present study examined empirical models of variables posited to predict students' homework environment management at the secondary school level. The participants were 866 8th graders from 61 classes and 745 11th graders from 46 classes. Most of the variance in homework environment management occurred at the student level, with classmates'…

Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

USDA-ARS?s Scientific Manuscript database

Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

The Impact of the Learning Environment on Student Engagement in High School Classrooms

ERIC Educational Resources Information Center

Shernoff, David J.; Tonks, Stephen M.; Anderson, Brett

2014-01-01

This chapter presents a study that investigated characteristics of the learning environment predicting for student engagement in public high school classrooms. Students in seven high school classrooms in five different subject areas were observed and videoed in order to predict their engagement as measured by the experience sampling method (ESM).…

Predicting Student Satisfaction with an Emphasis on Campus Recreational Sports and Cultural Facilities in a Turkish University

ERIC Educational Resources Information Center

Çelik, Ali Kemal; Akyol, Kübra

2015-01-01

The main purpose of this paper was to determine the predictors of student satisfaction focusing on campus recreational sports and cultural facilities. The present study utilized data from a written-questionnaire administered to one thousand adult undergraduate students. The dependent variable used in predicting student satisfaction was…

Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

ERIC Educational Resources Information Center

Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

2011-01-01

In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

Problems Inhibiting Attentional Capture by Irrelevant Stimuli in Patients with Frontotemporal Dementia

ERIC Educational Resources Information Center

Piquard, Ambre; Lacomblez, Lucette; Derouesne, Christian; Sieroff, Eric

2009-01-01

We studied the role of the frontal lobes in orienting spatial attention and inhibiting attentional capture by goal-irrelevant stimuli, using a spatial cueing method in patients with frontotemporal dementia (FTD). Two blocks of trials were presented, one with non-predictive cues and the other with counter-predictive cues. FTD patients showed a…

Predicting Success Using HESI A2 Entrance Tests in an Associate Degree Nursing Program

ERIC Educational Resources Information Center

Bodman, Susan

2012-01-01

A challenge presented to nurse educators is retention of nursing students. This has led nursing faculty to review admission requirements and question how well entrance tests predict success in Associate Degree Nursing Programs. The purpose of this study was to investigate the relationship between the HESI Admission Assessment Exam (HESI A2) and…

The Role of Personality Factors in Predicting the Reported Physical Health Symptoms of Turkish College Students

ERIC Educational Resources Information Center

Ustundag-Budak, Meltem; Mocan-Aydin, Gul

2005-01-01

This study investigates the role of optimism, health control beliefs, perceived health competence, and medical help-seeking variables in predicting the frequency of reported physical symptoms. A total of 345 college students (207 male and 138 female) were presented with the Life Orientation Test, Multidimensional Health Locus of Control, Perceived…

Predicting the Filial Behaviors of Chinese-Malaysian Adolescents from Perceived Parental Investments, Filial Emotions, and Parental Warmth and Support

ERIC Educational Resources Information Center

Cheah, Charissa S. L.; Ozdemir, Sevgi Bayram; Leung, Christy Y. Y.

2012-01-01

The present study examined the mediating role of perceived parental warmth and support in predicting Chinese Malaysian adolescents' filial behaviors from their age, perceived parental investments, and positive filial emotions toward their parents. The effects of these predictors were examined separately for mothers and fathers. Participants…

Determination of parameters of a new method for predicting alloy properties

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Ferrante, John

1992-01-01

Recently, a semiempirical method for alloys based on equivalent crystal theory was introduced. The method successfully predicts the concentration dependence of the heat of formation and lattice parameter of binary alloys. A study of the parameters of the method is presented, along with new results for (gamma)Fe-Pd and (gamma)Fe-Ni alloys.

EEG Estimates of Cognitive Workload and Engagement Predict Math Problem Solving Outcomes

ERIC Educational Resources Information Center

Beal, Carole R.; Galan, Federico Cirett

2012-01-01

In the present study, the authors focused on the use of electroencephalography (EEG) data about cognitive workload and sustained attention to predict math problem solving outcomes. EEG data were recorded as students solved a series of easy and difficult math problems. Sequences of attention and cognitive workload estimates derived from the EEG…

Neural Correlates of Encoding Predict Infants' Memory in the Paired-Comparison Procedure

ERIC Educational Resources Information Center

Snyder, Kelly A.

2010-01-01

The present study used event-related potentials (ERPs) to monitor infant brain activity during the initial encoding of a previously novel visual stimulus, and examined whether ERP measures of encoding predicted infants' subsequent performance on a visual memory task (i.e., the paired-comparison task). A late slow wave component of the ERP measured…

A Model-Based Approach to Predicting Graduate-Level Performance Using Indicators of Undergraduate-Level Performance

ERIC Educational Resources Information Center

Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M.

2015-01-01

The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…

Trajectories of Anxiety during Elementary-School Years and the Prediction of High School Noncompletion

ERIC Educational Resources Information Center

Duchesne, Stephane; Vitaro, Frank; Larose, Simon; Tremblay, Richard E.

2008-01-01

Previous research has provided mixed results regarding the effect of anxiety on academic achievement. Building on this body of research, the present longitudinal study pursued two goals. The first goal was to describe trajectories of anxiety during elementary-school years. The second goal was to determine the predictive value of these trajectories…

Predicting Students' Academic Achievement: Contributions of Perceptions of Classroom Assessment Tasks and Motivated Learning Strategies

ERIC Educational Resources Information Center

Alkharusi, Hussain

2016-01-01

Introduction: Students are daily exposed to a variety of assessment tasks in the classroom. It has long been recognized that students' perceptions of the assessment tasks may influence student academic achievement. The present study aimed at predicting academic achievement in mathematics from perceptions of the assessment tasks after controlling…

Contingencies in Mother-Child Teaching Interactions and Behavioral Regulation and Dysregulation in Early Childhood

ERIC Educational Resources Information Center

Lunkenheimer, Erika S.; Kemp, Christine J.; Albrecht, Erin C.

2013-01-01

Predictable patterns in early parent-child interactions may help lay the foundation for how children learn to self-regulate. The present study examined contingencies between maternal teaching and directives and child compliance in mother-child problem-solving interactions at age 3.5 and whether they predicted children's behavioral regulation and…

When Paths Diverge: "Errors of Prediction" From Preschool Test Scores to Later Cognitive and Academic Measures

ERIC Educational Resources Information Center

Dale, P. S.; Mills, P. E.; Cole, K. N.; Jenkins, J. R.

2004-01-01

Long-term follow-up information on children who have participated in early childhood special education (ECSE) has seldom been available. In the present study, the cognitive and academic performance of 171 thirteen-year-old graduates of 2 ECSE curricula is examined. Although preschool cognitive measures continued to predict later performance…

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…

Ultrasound waiting lists: rational queue or extended capacity?

PubMed

Brasted, Christopher

2008-06-01

The features and issues regarding clinical waiting lists in general and general ultrasound waiting lists in particular are reviewed, and operational aspects of providing a general ultrasound service are also discussed. A case study is presented describing a service improvement intervention in a UK NHS hospital's ultrasound department, from which arises requirements for a predictive planning model for an ultrasound waiting list. In the course of this, it becomes apparent that a booking system is a more appropriate way of describing the waiting list than a conventional queue. Distinctive features are identified from the literature and the case study as the basis for a predictive model, and a discrete event simulation model is presented which incorporates the distinctive features.

Intra- and intermolecular effects on the Compton profile of the ionic liquid 1,3-dimethylimidazolium chloride

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

Koskelo, J., E-mail: jaakko.koskelo@helsinki.fi; Juurinen, I.; Ruotsalainen, K. O.

2014-12-28

We present a comprehensive simulation study on the solid-liquid phase transition of the ionic liquid 1,3-dimethylimidazolium chloride in terms of the changes in the atomic structure and their effect on the Compton profile. The structures were obtained by using ab initio molecular dynamics simulations. Chosen radial distribution functions of the liquid structure are presented and found generally to be in good agreement with previous ab initio molecular dynamics and neutron scattering studies. The main contributions to the predicted difference Compton profile are found to arise from intermolecular changes in the phase transition. This prediction can be used for interpreting futuremore » experiments.« less

The upper bounds of reduced axial and shear moduli in cross-ply laminates with matrix cracks

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, D. H.; Harris, C. E.

1991-01-01

The present study proposes a mathematical model utilizing the internal state variable concept for predicting the upper bounds of the reduced axial and shear stiffnesses in cross-ply laminates with matrix cracks. The displacement components at the matrix crack surfaces are explicitly expressed in terms of the observable axial and shear strains and the undamaged material properties. The reduced axial and shear stiffnesses are predicted for glass/epoxy and graphite/epoxy laminates. Comparison of the model with other theoretical and experimental studies is also presented to confirm direct applicability of the model to angle-ply laminates with matrix cracks subjected to general in-plane loading.

Height prediction equations for even-aged upland oak stands

Treesearch

Donald E. Hilt; Martin E. Dale

1982-01-01

Forest growth models that use predicted tree diameters or diameter distributions require a reliable height-prediction model to obtain volume estimates because future height-diameter relationships will not necessarily be the same as the present height-diameter relationship. A total tree height prediction equation for even-aged upland oak stands is presented. Predicted...

Bankruptcy prediction for credit risk using neural networks: a survey and new results.

PubMed

Atiya, A F

2001-01-01

The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

Key Questions in Building Defect Prediction Models in Practice

NASA Astrophysics Data System (ADS)

Ramler, Rudolf; Wolfmaier, Klaus; Stauder, Erwin; Kossak, Felix; Natschläger, Thomas

The information about which modules of a future version of a software system are defect-prone is a valuable planning aid for quality managers and testers. Defect prediction promises to indicate these defect-prone modules. However, constructing effective defect prediction models in an industrial setting involves a number of key questions. In this paper we discuss ten key questions identified in context of establishing defect prediction in a large software development project. Seven consecutive versions of the software system have been used to construct and validate defect prediction models for system test planning. Furthermore, the paper presents initial empirical results from the studied project and, by this means, contributes answers to the identified questions.

Swimming Associated Disease Outbreaks.

ERIC Educational Resources Information Center

Cabelli, V. J.

1978-01-01

Presents a literature review of recreational waterborne outbreaks and cases of disease, covering publications of 1976-77. This review includes: (1) retrospective and prospective epidemiological studies; (2) predictive models of the risk of recreational waterborn disease. A list of 35 references is also presented. (HM)

Predicting basal metabolic rates in Malaysian adult elite athletes.

PubMed

Wong, Jyh Eiin; Poh, Bee Koon; Nik Shanita, Safii; Izham, Mohd Mohamad; Chan, Kai Quin; Tai, Meng De; Ng, Wei Wei; Ismail, Mohd Noor

2012-11-01

This study aimed to measure the basal metabolic rate (BMR) of elite athletes and develop a gender specific predictive equation to estimate their energy requirements. 92 men and 33 women (aged 18-31 years) from 15 sports, who had been training six hours daily for at least one year, were included in the study. Body composition was measured using the bioimpedance technique, and BMR by indirect calorimetry. The differences between measured and estimated BMR using various predictive equations were calculated. The novel equation derived from stepwise multiple regression was evaluated using Bland and Altman analysis. The predictive equations of Cunningham and the Food and Agriculture Organization/World Health Organization/United Nations University either over- or underestimated the measured BMR by up to ± 6%, while the equations of Ismail et al, developed from the local non-athletic population, underestimated the measured BMR by 14%. The novel predictive equation for the BMR of athletes was BMR (kcal/day) = 669 + 13 (weight in kg) + 192 (gender: 1 for men and 0 for women) (R2 0.548; standard error of estimates 163 kcal). Predicted BMRs of elite athletes by this equation were within 1.2% ± 9.5% of the measured BMR values. The novel predictive equation presented in this study can be used to calculate BMR for adult Malaysian elite athletes. Further studies may be required to validate its predictive capabilities for other sports, nationalities and age groups.

Classification Studies in an Advanced Air Classifier

NASA Astrophysics Data System (ADS)

Routray, Sunita; Bhima Rao, R.

2016-10-01

In the present paper, experiments are carried out using VSK separator which is an advanced air classifier to recover heavy minerals from beach sand. In classification experiments the cage wheel speed and the feed rate are set and the material is fed to the air cyclone and split into fine and coarse particles which are collected in separate bags. The size distribution of each fraction was measured by sieve analysis. A model is developed to predict the performance of the air classifier. The objective of the present model is to predict the grade efficiency curve for a given set of operating parameters such as cage wheel speed and feed rate. The overall experimental data with all variables studied in this investigation is fitted to several models. It is found that the present model is fitting good to the logistic model.

Thin-slice vision: inference of confidence measure from perceptual video quality

NASA Astrophysics Data System (ADS)

Hameed, Abdul; Balas, Benjamin; Dai, Rui

2016-11-01

There has been considerable research on thin-slice judgments, but no study has demonstrated the predictive validity of confidence measures when assessors watch videos acquired from communication systems, in which the perceptual quality of videos could be degraded by limited bandwidth and unreliable network conditions. This paper studies the relationship between high-level thin-slice judgments of human behavior and factors that contribute to perceptual video quality. Based on a large number of subjective test results, it has been found that the confidence of a single individual present in all the videos, called speaker's confidence (SC), could be predicted by a list of features that contribute to perceptual video quality. Two prediction models, one based on artificial neural network and the other based on a decision tree, were built to predict SC. Experimental results have shown that both prediction models can result in high correlation measures.

A prediction of 3-D viscous flow and performance of the NASA Low-Speed Centrifugal Compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1990-01-01

A prediction of the three-dimensional turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation of high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modeling. Recommendations are made for future flow studies in the NASA impeller.

A prediction of 3-D viscous flow and performance of the NASA low-speed centrifugal compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1989-01-01

A prediction of the 3-D turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation for high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modelling. Recommendations are made for future flow studies in the NASA impeller.

Towards Actionable Waterborne and Vector-borne Disease Forecasts

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.

2015-12-01

Numerous studies have shown that remote sensing (RS) and Earth System Models (ESM) can make important contributions to the analysis, monitoring and prediction of waterborne and vector-borne illnesses. Unsurprisingly, however, the great majority of these studies have been proof-of-concept investigations, and vanishingly few have been translated into operational and utilized disease early warning systems. To some extent this is simply an example of the general challenge of translating research findings into decision-relevant operations. Disease early warning, however, entails specific challenges that distinguish it from many other fields of environmental monitoring and prediction. Some of these challenges stem from predictability and data constraints, while others relate to the difficulty of communicating predictions and the particularly high price of false alarms. This presentation will review progress on the translation of analysis to decision making, identify avenues for enhancing forecast utility, and propose priorities for future RS and ESM investments in disease monitoring and prediction.

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli

PubMed Central

Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli. PMID:27875575

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli.

PubMed

Necciari, Thibaud; Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli.

Processing Speed Predicts Behavioral Treatment Outcomes in Children with Attention-Deficit/Hyperactivity Disorder Predominantly Inattentive Type.

PubMed

Adalio, Christopher J; Owens, Elizabeth B; McBurnett, Keith; Hinshaw, Stephen P; Pfiffner, Linda J

2018-05-01

Neuropsychological functioning underlies behavioral symptoms of attention-deficit/hyperactivity disorder (ADHD). Children with all forms of ADHD are vulnerable to working memory deficits and children presenting with the inattentive form of ADHD (ADHD-I) appear particularly vulnerable to processing speed deficits. As ADHD-I is the most common form of ADHD presented by children in community settings, it is important to consider how treatment interventions for children with ADHD-I may be affected by deficits in processing speed and working memory. We utilize data collected from 199 children with ADHD-I, aged 7 to 11 years, who participated in a randomized clinical trial of a psychosocial-behavioral intervention. Our aims are first to determine whether processing speed or working memory predict treatment outcomes in ADHD-I symptom severity, and second whether they moderate treatment effects on ADHD-I symptom severity. Results of linear regression analyses reveal that baseline processing speed significantly predicts posttreatment ADHD-I symptom severity when controlling for baseline ADHD-I symptom severity, such that better processing speed is associated with greater symptom improvement. However, predictive effects of working memory and moderation effects of both working memory and processing speed are not supported in the present study. We discuss study limitations and implications of the relation between processing speed and treatment benefits from psychosocial treatments for children with ADHD-I.

Fertility biomarkers to estimate metabolic risks in women with polycystic ovary syndrome.

PubMed

Detti, Laura; Jeffries-Boyd, Heather E; Williams, Lucy J; Diamond, Michael P; Uhlmann, Rebecca A

2015-12-01

We sought to evaluate the relationship between the polycystic ovary syndrome (PCOS)-defining characteristics and the risk of developing metabolic complications in women presenting with complaints of infertility and/or menstrual irregularities and subsequently diagnosed with PCOS. This was a cross-sectional study. Women presenting with complaints of infertility and/or irregular menses and diagnosed with PCOS by the Rotterdam criteria, underwent endocrine, metabolic, and ultrasound assessment in the early follicular phase. Reproductive and metabolic parameters were included in regression analysis models with the PCOS-defining characteristics; ROC curves were calculated for the significant predictors. Three hundred and seventy-four women with PCOS were included in our study. Oligo-anovulation, menstrual irregularities, and hirsutism were not predictive of any of the variables. Ovarian volume, follicle count, and biochemical hyperandrogenism were predictors for hormonal, metabolic, and endometrial complications. The relationships were independent of age and body mass index. ROC curves identified lower cut-off values of the PCOS-defining characteristics to predict patients' risks of hyperinsulinemia, dyslipidemia, and glucose intolerance. Adverse metabolic effects of PCOS are already present in women at the time they present complaining of infertility and/or irregular menses. Hyperandrogenism and ultrasound can assist in predicting the patients' concomitant metabolic abnormalities and can aid physicians in tailoring counseling for effective preventive strategies.

The Use of Immersive Virtual Reality (VR) to Predict the Occurrence 6 Months Later of Paranoid Thinking and Posttraumatic Stress Symptoms Assessed by Self-Report and Interviewer Methods: A Study of Individuals Who Have Been Physically Assaulted

PubMed Central

2014-01-01

Presentation of social situations via immersive virtual reality (VR) has the potential to be an ecologically valid way of assessing psychiatric symptoms. In this study we assess the occurrence of paranoid thinking and of symptoms of posttraumatic stress disorder (PTSD) in response to a single neutral VR social environment as predictors of later psychiatric symptoms assessed by standard methods. One hundred six people entered an immersive VR social environment (a train ride), presented via a head-mounted display, 4 weeks after having attended hospital because of a physical assault. Paranoid thinking about the neutral computer-generated characters and the occurrence of PTSD symptoms in VR were assessed. Reactions in VR were then used to predict the occurrence 6 months later of symptoms of paranoia and PTSD, as assessed by standard interviewer and self-report methods. Responses to VR predicted the severity of paranoia and PTSD symptoms as assessed by standard measures 6 months later. The VR assessments also added predictive value to the baseline interviewer methods, especially for paranoia. Brief exposure to environments presented via virtual reality provides a symptom assessment with predictive ability over many months. VR assessment may be of particular benefit for difficult to assess problems, such as paranoia, that have no gold standard assessment method. In the future, VR environments may be used in the clinic to complement standard self-report and clinical interview methods. PMID:24708073

The use of immersive virtual reality (VR) to predict the occurrence 6 months later of paranoid thinking and posttraumatic stress symptoms assessed by self-report and interviewer methods: a study of individuals who have been physically assaulted.

PubMed

Freeman, Daniel; Antley, Angus; Ehlers, Anke; Dunn, Graham; Thompson, Claire; Vorontsova, Natasha; Garety, Philippa; Kuipers, Elizabeth; Glucksman, Edward; Slater, Mel

2014-09-01

Presentation of social situations via immersive virtual reality (VR) has the potential to be an ecologically valid way of assessing psychiatric symptoms. In this study we assess the occurrence of paranoid thinking and of symptoms of posttraumatic stress disorder (PTSD) in response to a single neutral VR social environment as predictors of later psychiatric symptoms assessed by standard methods. One hundred six people entered an immersive VR social environment (a train ride), presented via a head-mounted display, 4 weeks after having attended hospital because of a physical assault. Paranoid thinking about the neutral computer-generated characters and the occurrence of PTSD symptoms in VR were assessed. Reactions in VR were then used to predict the occurrence 6 months later of symptoms of paranoia and PTSD, as assessed by standard interviewer and self-report methods. Responses to VR predicted the severity of paranoia and PTSD symptoms as assessed by standard measures 6 months later. The VR assessments also added predictive value to the baseline interviewer methods, especially for paranoia. Brief exposure to environments presented via virtual reality provides a symptom assessment with predictive ability over many months. VR assessment may be of particular benefit for difficult to assess problems, such as paranoia, that have no gold standard assessment method. In the future, VR environments may be used in the clinic to complement standard self-report and clinical interview methods. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

The Role of Family for Youth Friendships: Examining a Social Anxiety Mechanism.

PubMed

Mak, Hio Wa; Fosco, Gregory M; Feinberg, Mark E

2018-02-01

The quality of family relationships and youth friendships are intricately linked. Previous studies have examined different mechanisms of family-peer linkage, but few have examined social anxiety. The present study examined whether parental rejection and family climate predicted changes in youth social anxiety, which in turn predicted changes in friendship quality and loneliness. Possible bidirectional associations also were examined. Data for mothers, fathers, and youth (M age at Time 1 = 11.27; 52.3% were female) from 687 two-parent households over three time points are presented. Results from autoregressive, cross-lagged analyses revealed that father rejection (not mother rejection or family climate) at Time 1 (Fall of 6th Grade) predicted increased youth social anxiety at Time 2 (Spring of 7th Grade), which in turn, predicted increased loneliness at Time 3 (Spring of 8th Grade). The indirect effect of father rejection on loneliness was statistically significant. Mother rejection, father rejection, and a poor family climate were associated with decreased friendship quality and increased loneliness over time. Finally, there was some evidence of transactional associations between father rejection and youth social anxiety as well as between social anxiety and loneliness. This study's findings underscore the important role of fathers in youth social anxiety and subsequent social adjustment.

Household food insecurity during childhood and adolescent misconduct.

PubMed

Jackson, Dylan B; Vaughn, Michael G

2017-03-01

A large body of research has found that household food insecurity can interfere with the healthy development of children. The link between household food insecurity during childhood and misbehaviors during adolescence, however, is not commonly explored. The objective of the current study is to assess whether household food insecurity across childhood predicts four different forms of misconduct during early adolescence. Data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 (ECLS-K), a nationally representative sample of U.S. children, were employed in the present study. Associations between household food insecurity during childhood and adolescent misconduct were examined using Logistic and Negative Binomial Regression. Analyses were performed separately for males and females. The results revealed that household food insecurity and food insecurity persistence were predictive of most forms of misconduct for males, and were consistently predictive of engagement in multiple forms of misconduct and a greater variety of forms of misconduct for males. For females, however, household food insecurity generally failed to predict adolescent misconduct. The behavioral development of males during adolescence appears to be sensitive to the presence and persistence of household food insecurity during childhood. Future research should seek to replicate and extend the present findings to late adolescence and adulthood. Copyright © 2017 Elsevier Inc. All rights reserved.

Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang

PubMed Central

Liu, Bing-Chun; Binaykia, Arihant; Chang, Pei-Chann; Tiwari, Manoj Kumar; Tsao, Cheng-Chin

2017-01-01

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. PMID:28708836

Epigenome-wide cross-tissue predictive modeling and comparison of cord blood and placental methylation in a birth cohort

PubMed Central

De Carli, Margherita M; Baccarelli, Andrea A; Trevisi, Letizia; Pantic, Ivan; Brennan, Kasey JM; Hacker, Michele R; Loudon, Holly; Brunst, Kelly J; Wright, Robert O; Wright, Rosalind J; Just, Allan C

2017-01-01

Aim: We compared predictive modeling approaches to estimate placental methylation using cord blood methylation. Materials & methods: We performed locus-specific methylation prediction using both linear regression and support vector machine models with 174 matched pairs of 450k arrays. Results: At most CpG sites, both approaches gave poor predictions in spite of a misleading improvement in array-wide correlation. CpG islands and gene promoters, but not enhancers, were the genomic contexts where the correlation between measured and predicted placental methylation levels achieved higher values. We provide a list of 714 sites where both models achieved an R2 ≥0.75. Conclusion: The present study indicates the need for caution in interpreting cross-tissue predictions. Few methylation sites can be predicted between cord blood and placenta. PMID:28234020

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.

PubMed

Müller, Martin; Seidenberg, Ruth; Schuh, Sabine K; Exadaktylos, Aristomenis K; Schechter, Clyde B; Leichtle, Alexander B; Hautz, Wolf E

2018-01-01

Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter

PubMed Central

Seidenberg, Ruth; Schuh, Sabine K.; Exadaktylos, Aristomenis K.; Schechter, Clyde B.; Leichtle, Alexander B.; Hautz, Wolf E.

2018-01-01

Objective Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. Methods This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Results Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Conclusions Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected. PMID:29474463

The relationships between perfectionism, pathological worry and generalised anxiety disorder.

PubMed

Handley, Alicia K; Egan, Sarah J; Kane, Robert T; Rees, Clare S

2014-04-02

The relationships between perfectionism, pathological worry and generalised anxiety disorder (GAD) were investigated in a clinical sample presenting for treatment of perfectionism. This study explored the utility of perfectionism in predicting pathological worry in a sample of individuals with elevated perfectionism and GAD (n = 36). Following this, the study examined whether perfectionism could predict a principal GAD diagnosis in the full sample (n = 42). Scores on the perfectionism dimensions Concern over Mistakes, Personal Standards, and Clinical Perfectionism significantly predicted pathological worry among participants with GAD after controlling for gender and depression. The perfectionism dimension Doubts about Actions significantly predicted whether individuals from the full sample received a principal diagnosis of GAD. These findings support certain dimensions of perfectionism having significant associations with pathological worry and GAD.

Wave models for turbulent free shear flows

NASA Technical Reports Server (NTRS)

Liou, W. W.; Morris, P. J.

1991-01-01

New predictive closure models for turbulent free shear flows are presented. They are based on an instability wave description of the dominant large scale structures in these flows using a quasi-linear theory. Three model were developed to study the structural dynamics of turbulent motions of different scales in free shear flows. The local characteristics of the large scale motions are described using linear theory. Their amplitude is determined from an energy integral analysis. The models were applied to the study of an incompressible free mixing layer. In all cases, predictions are made for the development of the mean flow field. In the last model, predictions of the time dependent motion of the large scale structure of the mixing region are made. The predictions show good agreement with experimental observations.

Is Cyberbullying Related to Lack of Empathy and Social-Emotional Problems?

ERIC Educational Resources Information Center

Schultze-Krumbholz, Anja; Scheithauer, Herbert

2013-01-01

Examination of the longitudinal relationship between empathy, social-emotional problems and cyberbullying is still rare and the present study is one of very few. The present study assessed whether low scores of affective and cognitive empathy at wave 1 (t1) can predict involvement in cyberbullying five months later (t2). Furthermore, it was…

BOLD responses in reward regions to hypothetical and imaginary monetary rewards

PubMed Central

Miyapuram, Krishna P.; Tobler, Philippe N.; Gregorios-Pippas, Lucy; Schultz, Wolfram

2015-01-01

Monetary rewards are uniquely human. Because money is easy to quantify and present visually, it is the reward of choice for most fMRI studies, even though it cannot be handed over to participants inside the scanner. A typical fMRI study requires hundreds of trials and thus small amounts of monetary rewards per trial (e.g. 5p) if all trials are to be treated equally. However, small payoffs can have detrimental effects on performance due to their limited buying power. Hypothetical monetary rewards can overcome the limitations of smaller monetary rewards but it is less well known whether predictors of hypothetical rewards activate reward regions. In two experiments, visual stimuli were associated with hypothetical monetary rewards. In Experiment 1, we used stimuli predicting either visually presented or imagined hypothetical monetary rewards, together with non-rewarding control pictures. Activations to reward predictive stimuli occurred in reward regions, namely the medial orbitofrontal cortex and midbrain. In Experiment 2, we parametrically varied the amount of visually presented hypothetical monetary reward keeping constant the amount of actually received reward. Graded activation in midbrain was observed to stimuli predicting increasing hypothetical rewards. The results demonstrate the efficacy of using hypothetical monetary rewards in fMRI studies. PMID:21985912

BOLD responses in reward regions to hypothetical and imaginary monetary rewards.

PubMed

Miyapuram, Krishna P; Tobler, Philippe N; Gregorios-Pippas, Lucy; Schultz, Wolfram

2012-01-16

Monetary rewards are uniquely human. Because money is easy to quantify and present visually, it is the reward of choice for most fMRI studies, even though it cannot be handed over to participants inside the scanner. A typical fMRI study requires hundreds of trials and thus small amounts of monetary rewards per trial (e.g. 5p) if all trials are to be treated equally. However, small payoffs can have detrimental effects on performance due to their limited buying power. Hypothetical monetary rewards can overcome the limitations of smaller monetary rewards but it is less well known whether predictors of hypothetical rewards activate reward regions. In two experiments, visual stimuli were associated with hypothetical monetary rewards. In Experiment 1, we used stimuli predicting either visually presented or imagined hypothetical monetary rewards, together with non-rewarding control pictures. Activations to reward predictive stimuli occurred in reward regions, namely the medial orbitofrontal cortex and midbrain. In Experiment 2, we parametrically varied the amount of visually presented hypothetical monetary reward keeping constant the amount of actually received reward. Graded activation in midbrain was observed to stimuli predicting increasing hypothetical rewards. The results demonstrate the efficacy of using hypothetical monetary rewards in fMRI studies. Copyright © 2011 Elsevier Inc. All rights reserved.

Combinatorial markers of mild cognitive impairment conversion to Alzheimer's disease--cytokines and MRI measures together predict disease progression.

PubMed

Furney, Simon J; Kronenberg, Deborah; Simmons, Andrew; Güntert, Andreas; Dobson, Richard J; Proitsi, Petroula; Wahlund, Lars Olof; Kloszewska, Iwona; Mecocci, Patrizia; Soininen, Hilkka; Tsolaki, Magda; Vellas, Bruno; Spenger, Christian; Lovestone, Simon

2011-01-01

Progression of people presenting with Mild Cognitive Impairment (MCI) to dementia is not certain and it is not possible for clinicians to predict which people are most likely to convert. The inability of clinicians to predict progression limits the use of MCI as a syndrome for treatment in prevention trials and, as more people present with this syndrome in memory clinics, and as earlier diagnosis is a major goal of health services, this presents an important clinical problem. Some data suggest that CSF biomarkers and functional imaging using PET might act as markers to facilitate prediction of conversion. However, both techniques are costly and not universally available. The objective of our study was to investigate the potential added benefit of combining biomarkers that are more easily obtained in routine clinical practice to predict conversion from MCI to Alzheimer's disease. To explore this we combined automated regional analysis of structural MRI with analysis of plasma cytokines and chemokines and compared these to measures of APOE genotype and clinical assessment to assess which best predict progression. In a total of 205 people with MCI, 77 of whom subsequently converted to Alzheimer's disease, we find biochemical markers of inflammation to be better predictors of conversion than APOE genotype or clinical measures (Area under the curve (AUC) 0.65, 0.62, 0.59 respectively). In a subset of subjects who also had MRI scans the combination of serum markers of inflammation and MRI automated imaging analysis provided the best predictor of conversion (AUC 0.78). These results show that the combination of imaging and cytokine biomarkers provides an improvement in prediction of MCI to AD conversion compared to either datatype alone, APOE genotype or clinical data and an accuracy of prediction that would have clinical utility.

A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

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

Poulin, Patrick, E-mail: patrick-poulin@videotron.ca; Ekins, Sean; Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, MD 21201

A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V{sub ss}) in humans under in vivo conditions. Thismore » correlation method demonstrated inaccurate predictions of V{sub ss} for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V{sub ss} of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.« less

In Silico Prediction Analysis of Idiotope-Driven T–B Cell Collaboration in Multiple Sclerosis

PubMed Central

Høglund, Rune A.; Lossius, Andreas; Johansen, Jorunn N.; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D.; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4+ T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T–B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4+ T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses. PMID:29038659

In Silico Prediction Analysis of Idiotope-Driven T-B Cell Collaboration in Multiple Sclerosis.

PubMed

Høglund, Rune A; Lossius, Andreas; Johansen, Jorunn N; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4 + T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T-B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4 + T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses.

Predicting writing development in dual language instructional contexts: exploring cross-linguistic relationships.

PubMed

Savage, Robert; Kozakewich, Meagan; Genesee, Fred; Erdos, Caroline; Haigh, Corinne

2017-01-01

This study examined whether decoding and linguistic comprehension abilities, broadly defined by the Simple View of Reading, in grade 1 each uniquely predicted the grade 6 writing performance of English-speaking children (n = 76) who were educated bilingually in both English their first language and French, a second language. Prediction was made from (1) English to English; (2) French to French; and (3) English to French. Results showed that both decoding and linguistic comprehension scores predicted writing accuracy but rarely predicted persuasive writing. Within the linguistic comprehension cluster of tests, Formulating Sentences was a strong consistent within- and between-language predictor of writing accuracy. In practical terms, the present results indicate that early screening for later writing ability using measures of sentence formulation early in students' schooling, in their L1 or L2, can provide greatest predictive power and allow teachers to differentiate instruction in the primary grades. Theoretically, the present results argue that there are correlations between reading-related abilities and writing abilities not only within the same language but also across languages, adding to the growing body of evidence for facilitative cross-linguistic relationships between bilinguals' developing languages. © 2016 John Wiley & Sons Ltd.

Modeling and Prediction of Fan Noise

NASA Technical Reports Server (NTRS)

Envia, Ed

2008-01-01

Fan noise is a significant contributor to the total noise signature of a modern high bypass ratio aircraft engine and with the advent of ultra high bypass ratio engines like the geared turbofan, it is likely to remain so in the future. As such, accurate modeling and prediction of the basic characteristics of fan noise are necessary ingredients in designing quieter aircraft engines in order to ensure compliance with ever more stringent aviation noise regulations. In this paper, results from a comprehensive study aimed at establishing the utility of current tools for modeling and predicting fan noise will be summarized. It should be emphasized that these tools exemplify present state of the practice and embody what is currently used at NASA and Industry for predicting fan noise. The ability of these tools to model and predict fan noise is assessed against a set of benchmark fan noise databases obtained for a range of representative fan cycles and operating conditions. Detailed comparisons between the predicted and measured narrowband spectral and directivity characteristics of fan nose will be presented in the full paper. General conclusions regarding the utility of current tools and recommendations for future improvements will also be given.

PASS assisted prediction and pharmacological evaluation of novel nicotinic analogs for nootropic activity in mice.

PubMed

Khurana, Navneet; Ishar, Mohan Pal Singh; Gajbhiye, Asmita; Goel, Rajesh Kumar

2011-07-15

The aim of present study is to predict the probable nootropic activity of novel nicotine analogues with the help of computer program, PASS (prediction of activity spectra for substances) and evaluate the same. Two compounds from differently substituted pyridines were selected for synthesis and evaluation of nootropic activity based on their high probable activity (Pa) value predicted by PASS computer program. Evaluation of nootropic activity of compounds after acute and chronic treatment was done with transfer latency (TL) and step down latency (SDL) methods which showed significant nootropic activity. The effect on scopolamine induced amnesia was also observed along with their acetylcholine esterase inhibitory activity which also showed positive results which strengthened their efficacy as nootropic agents through involvement of cholinergic system. This nootropic effect was similar to the effect of nicotine and donepezil used as standard drugs. Muscle coordination and locomotor activity along with their addiction liability, safety and tolerability studies were also evaluated. These studies showed that these compounds are well tolerable and safe over a wide range of doses tested along with the absence of withdrawal effect which is present in nicotine due to its addiction liability. The study showed that these compounds are true nicotine analogs with desirable efficacy and safety profile for their use as effective nootropic agents. Copyright © 2011 Elsevier B.V. All rights reserved.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

PubMed

Qin, Li-Tang; Chen, Yu-Han; Zhang, Xin; Mo, Ling-Yun; Zeng, Hong-Hu; Liang, Yan-Peng

2018-05-01

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC 50 ) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Interplay Between Conceptual Expectations and Movement Predictions Underlies Action Understanding.

PubMed

Ondobaka, Sasha; de Lange, Floris P; Wittmann, Marco; Frith, Chris D; Bekkering, Harold

2015-09-01

Recent accounts of understanding goal-directed action underline the importance of a hierarchical predictive architecture. However, the neural implementation of such an architecture remains elusive. In the present study, we used functional neuroimaging to quantify brain activity associated with predicting physical movements, as they were modulated by conceptual-expectations regarding the purpose of the object involved in the action. Participants observed object-related actions preceded by a cue that generated both conceptual goal expectations and movement goal predictions. In 2 tasks, observers judged whether conceptual or movement goals matched or mismatched the cue. At the conceptual level, expected goals specifically recruited the posterior cingulate cortex, irrespectively of the task and the perceived movement goal. At the movement level, neural activation of the parieto-frontal circuit, including inferior frontal gyrus and the inferior parietal lobe, reflected unpredicted movement goals. Crucially, this movement prediction error was only present when the purpose of the involved object was expected. These findings provide neural evidence that prior conceptual expectations influence processing of physical movement goals and thereby support the hierarchical predictive account of action processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Ketamine Effects on Memory Reconsolidation Favor a Learning Model of Delusions

PubMed Central

Gardner, Jennifer M.; Piggot, Jennifer S.; Turner, Danielle C.; Everitt, Jessica C.; Arana, Fernando Sergio; Morgan, Hannah L.; Milton, Amy L.; Lee, Jonathan L.; Aitken, Michael R. F.; Dickinson, Anthony; Everitt, Barry J.; Absalom, Anthony R.; Adapa, Ram; Subramanian, Naresh; Taylor, Jane R.; Krystal, John H.; Fletcher, Paul C.

2013-01-01

Delusions are the persistent and often bizarre beliefs that characterise psychosis. Previous studies have suggested that their emergence may be explained by disturbances in prediction error-dependent learning. Here we set up complementary studies in order to examine whether such a disturbance also modulates memory reconsolidation and hence explains their remarkable persistence. First, we quantified individual brain responses to prediction error in a causal learning task in 18 human subjects (8 female). Next, a placebo-controlled within-subjects study of the impact of ketamine was set up on the same individuals. We determined the influence of this NMDA receptor antagonist (previously shown to induce aberrant prediction error signal and lead to transient alterations in perception and belief) on the evolution of a fear memory over a 72 hour period: they initially underwent Pavlovian fear conditioning; 24 hours later, during ketamine or placebo administration, the conditioned stimulus (CS) was presented once, without reinforcement; memory strength was then tested again 24 hours later. Re-presentation of the CS under ketamine led to a stronger subsequent memory than under placebo. Moreover, the degree of strengthening correlated with individual vulnerability to ketamine's psychotogenic effects and with prediction error brain signal. This finding was partially replicated in an independent sample with an appetitive learning procedure (in 8 human subjects, 4 female). These results suggest a link between altered prediction error, memory strength and psychosis. They point to a core disruption that may explain not only the emergence of delusional beliefs but also their persistence. PMID:23776445

Prediction of future subsurface temperatures in Korea

NASA Astrophysics Data System (ADS)

Lee, Y.; Kim, S. K.; Jeong, J.; SHIN, E.

2017-12-01

The importance of climate change has been increasingly recognized because it has had the huge amount of impact on social, economic, and environmental aspect. For the reason, paleoclimate change has been studied intensively using different geological tools including borehole temperatures and future surface air temperatures (SATs) have been predicted for the local areas and the globe. Future subsurface temperatures can have also enormous impact on various areas and be predicted by an analytical method or a numerical simulation using measured and predicted SATs, and thermal diffusivity data of rocks. SATs have been measured at 73 meteorological observatories since 1907 in Korea and predicted at same locations up to the year of 2100. Measured SATs at the Seoul meteorological observatory increased by about 3.0 K from the year of 1907 to the present. Predicted SATs have 4 different scenarios depending on mainly CO2 concentration and national action plan on climate change in the future. The hottest scenario shows that SATs in Korea will increase by about 5.0 K from the present to the year of 2100. In addition, thermal diffusivity values have been measured on 2,903 rock samples collected from entire Korea. Data pretreatment based on autocorrelation analysis was conducted to control high frequency noise in thermal diffusivity data. Finally, future subsurface temperatures in Korea were predicted up to the year of 2100 by a FEM simulation code (COMSOL Multiphysics) using measured and predicted SATs, and thermal diffusivity data in Korea. At Seoul, the results of predictions show that subsurface temperatures will increase by about 5.4 K, 3.0 K, 1.5 K, and 0.2 K from the present to 2050 and then by about 7.9 K, 4.8 K, 2.5 K, and 0.5 K to 2100 at the depths of 10 m, 50 m, 100 m, and 200 m, respectively. We are now proceeding numerical simulations for subsurface temperature predictions for 73 locations in Korea.

Correlation of the association of serum lactate, random blood sugar, and revised trauma score as predictors of outcome in hemodynamically unstable abdominal emergencies.

PubMed

Allwell-Brown, E; Afuwape, O O; Ayandipo, O; Alonge, T

2016-01-01

Elevated levels of serum lactate and glucose during resuscitation have been demonstrated to be predictors of morbidity and mortality in hemodynamically unstable patients with surgical abdominal conditions. However, the rate of return to normal levels of both lactate and blood glucose may be better predictors of mortality and morbidity. The aims of this study are: (I) To determine the pattern of serum lactate and glucose changes in patients with surgical abdominal conditions requiring resuscitation within 48 hours of presentation. (II) To correlate the predictive capability of these two independent parameters. (III) To correlate the predictive values of these parameters with the revised trauma score (RTS). This is a prospective observational study conducted over three months. The patients admitted by the general surgery division requiring resuscitation from shock was included in this study. Resuscitation was carried out with crystalloids. The estimation of serum lactate and glucose levels was done at presentation (0 hours), 12, 24 and 48 hours after admission. The revised trauma score (RTS) was calculated for each patient at presentation and at 12, 24 and 48 hours subsequently. The patients were followed up four weeks or when death occurred within four weeks of presentation. Forty four patients were recruited in the study. There were seven mortalities. The mean serum levels of Plasma glucose and lactate of all the patients were elevated at presentation in the emergency department. Survival was better with a return to normal serum lactate within 12 hours. On the other hand the random plasma glucose (RPG) levels may not be useful in prognosticating patients. However a combination of serum lactate, RTS (at 24 and 48 hours) and RPG at 48 hours may improve predictive parameters in trauma related cases.

Peak-summer East Asian rainfall predictability and prediction part II: extratropical East Asia

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Xing, Wen

2016-07-01

The part II of the present study focuses on northern East Asia (NEA: 26°N-50°N, 100°-140°E), exploring the source and limit of the predictability of the peak summer (July-August) rainfall. Prediction of NEA peak summer rainfall is extremely challenging because of the exposure of the NEA to midlatitude influence. By examining four coupled climate models' multi-model ensemble (MME) hindcast during 1979-2010, we found that the domain-averaged MME temporal correlation coefficient (TCC) skill is only 0.13. It is unclear whether the dynamical models' poor skills are due to limited predictability of the peak-summer NEA rainfall. In the present study we attempted to address this issue by applying predictable mode analysis method using 35-year observations (1979-2013). Four empirical orthogonal modes of variability and associated major potential sources of variability are identified: (a) an equatorial western Pacific (EWP)-NEA teleconnection driven by EWP sea surface temperature (SST) anomalies, (b) a western Pacific subtropical high and Indo-Pacific dipole SST feedback mode, (c) a central Pacific-El Nino-Southern Oscillation mode, and (d) a Eurasian wave train pattern. Physically meaningful predictors for each principal component (PC) were selected based on analysis of the lead-lag correlations with the persistent and tendency fields of SST and sea-level pressure from March to June. A suite of physical-empirical (P-E) models is established to predict the four leading PCs. The peak summer rainfall anomaly pattern is then objectively predicted by using the predicted PCs and the corresponding observed spatial patterns. A 35-year cross-validated hindcast over the NEA yields a domain-averaged TCC skill of 0.36, which is significantly higher than the MME dynamical hindcast (0.13). The estimated maximum potential attainable TCC skill averaged over the entire domain is around 0.61, suggesting that the current dynamical prediction models may have large rooms to improve. Limitations and future work are also discussed.

Using the load-velocity relationship for 1RM prediction.

PubMed

Jidovtseff, Boris; Harris, Nigel K; Crielaard, Jean-Michel; Cronin, John B

2011-01-01

The purpose of this study was to investigate the ability of the load-velocity relationship to accurately predict a bench press 1 repetition maximum (1RM). Data from 3 different bench press studies (n = 112) that incorporated both 1RM assessment and submaximal load-velocity profiling were analyzed. Individual regression analysis was performed to determine the theoretical load at zero velocity (LD0). Data from each of the 3 studies were analyzed separately and also presented as overall group mean. Thereafter, correlation analysis provided quantification of the relationships between 1RM and LD0. Practically perfect correlations (r = ∼0.95) were observed in our samples, confirming the ability of the load-velocity profile to accurately predict bench press 1RM.

The Role of Depression and Attachment Styles in Predicting Students' Addiction to Cell Phones.

PubMed

Ghasempour, Abdollah; Mahmoodi-Aghdam, Mansour

2015-01-01

The present study aimed at investigating the role of depression and attachment styles in predicting cell phone addiction. In this descriptive correlational study, a sample including 100 students of Payame Noor University (PNU), Reyneh Center, Iran, in the academic year of 2013-2014 was selected using volunteer sampling. Participants were asked to complete the adult attachment inventory (AAI), Beck depression inventory-13 (BDI-13) and the cell phone overuse scale (COS). Results of the stepwise multiple regression analysis showed that depression and avoidant attachment style were the best predictors of students' cell phone addiction (R(2) = 0.23). The results of this study highlighted the predictive value of depression and avoidant attachment style concerning students' cell phone addiction.

Elastic properties of graphene: A pseudo-beam model with modified internal bending moment and its application

NASA Astrophysics Data System (ADS)

Xia, Z. M.; Wang, C. G.; Tan, H. F.

2018-04-01

A pseudo-beam model with modified internal bending moment is presented to predict elastic properties of graphene, including the Young's modulus and Poisson's ratio. In order to overcome a drawback in existing molecular structural mechanics models, which only account for pure bending (constant bending moment), the presented model accounts for linear bending moments deduced from the balance equations. Based on this pseudo-beam model, an analytical prediction is accomplished to predict the Young's modulus and Poisson's ratio of graphene based on the equation of the strain energies by using Castigliano second theorem. Then, the elastic properties of graphene are calculated compared with results available in literature, which verifies the feasibility of the pseudo-beam model. Finally, the pseudo-beam model is utilized to study the twisting wrinkling characteristics of annular graphene. Due to modifications of the internal bending moment, the wrinkling behaviors of graphene sheet are predicted accurately. The obtained results show that the pseudo-beam model has a good ability to predict the elastic properties of graphene accurately, especially the out-of-plane deformation behavior.

Indoor NO2 air pollution and lung function of professional cooks.

PubMed

Arbex, M A; Martins, L C; Pereira, L A A; Negrini, F; Cardoso, A A; Melchert, W R; Arbex, R F; Saldiva, P H N; Zanobetti, A; Braga, A L F

2007-04-01

Studies of cooking-generated NO2 effects are rare in occupational epidemiology. In the present study, we evaluated the lung function of professional cooks exposed to NO2 in hospital kitchens. We performed spirometry in 37 cooks working in four hospital kitchens and estimated the predicted FVC, FEV1 and FEF(25-75), based on age, sex, race, weight, and height, according to Knudson standards. NO2 measurements were obtained for 4 consecutive days during 4 different periods at 20-day intervals in each kitchen. Measurements were performed inside and outside the kitchens, simultaneously using Palm diffusion tubes. A time/exposure indicator was defined as representative of the cumulative exposure of each cook. No statistically significant effect of NO2 exposure on FVC was found. Each year of work as a cook corresponded to a decrease in predicted FEV1 of 2.5% (P = 0.046) for the group as a whole. When smoking status and asthma were included in the analysis the effect of time/exposure decreased about 10% and lost statistical significance. On predicted FEF(25-75), a decrease of 3.5% (P = 0.035) was observed for the same group and the inclusion of controllers for smoking status and asthma did not affect the effects of time/exposure on pulmonary function parameter. After a 10-year period of work as cooks the participants of the study may present decreases in both predicted FEV1 and FEF(25-75) that can reach 20 and 30%, respectively. The present study showed small but statistically significant adverse effects of gas stove exposure on the lung function of professional cooks.

Algorithm for early discharge after total thyroidectomy using PTH to predict hypocalcemia: prospective study.

PubMed

Schlottmann, F; Arbulú, A L Campos; Sadava, E E; Mendez, P; Pereyra, L; Fernández Vila, J M; Mezzadri, N A

2015-10-01

Hypocalcemia is the most common complication after total thyroidectomy. The aim of this study was to determine whether postoperative parathyroid hormone (PTH) levels predict hypocalcemia in order to design an algorithm for early discharge. We present a prospective study including patients who underwent total thyroidectomy. Hypocalcemia was defined as serum ionized calcium < 1.09 mmol/L or clinical evidence of hypocalcemia. PTH measurement was performed preoperatively and at 1, 3, and 6 h postoperatively. The percent decline of preoperative values was calculated for each time point. One hundred and six patients were included. Thirty-six (33.9%) patients presented hypocalcemia. A 50% decline in PTH levels at 3 h postoperatively showed the highest sensitivity and specificity to predict hypocalcemia (91 and 73%, respectively). No patients with a decrease <35% developed hypocalcemia (100% sensitivity), and all patients with a decrease >80% had hypocalcemia (100% specificity). PTH determination at 3 h postoperatively is a reliable predictor of hypocalcemia. According to the proposed algorithm, patients with less than 80% drop in PTH levels can be safely discharged the day of the surgery.

In silico platform for predicting and initiating β-turns in a protein at desired locations.

PubMed

Singh, Harinder; Singh, Sandeep; Raghava, Gajendra P S

2015-05-01

Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein. © 2015 Wiley Periodicals, Inc.

Predictive Biomarkers of Gastroesophageal Reflux Disease and Barrett's Esophagus in World Trade Center Exposed Firefighters: a 15 Year Longitudinal Study.

PubMed

Haider, Syed H; Kwon, Sophia; Lam, Rachel; Lee, Audrey K; Caraher, Erin J; Crowley, George; Zhang, Liqun; Schwartz, Theresa M; Zeig-Owens, Rachel; Liu, Mengling; Prezant, David J; Nolan, Anna

2018-02-15

Gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE), which are prevalent in the World Trade Center (WTC) exposed and general populations, negatively impact quality of life and cost of healthcare. GERD, a risk factor of BE, is linked to obstructive airways disease (OAD). We aim to identify serum biomarkers of GERD/BE, and assess the respiratory and clinical phenotype of a longitudinal cohort of never-smoking, male, WTC-exposed rescue workers presenting with pulmonary symptoms. Biomarkers collected soon after WTC-exposure were evaluated in optimized predictive models of GERD/BE. In the WTC-exposed cohort, the prevalence of BE is at least 6 times higher than in the general population. GERD/BE cases had similar lung function, D LCO , bronchodilator response and long-acting β-agonist use compared to controls. In confounder-adjusted regression models, TNF-α ≥ 6 pg/mL predicted both GERD and BE. GERD was also predicted by C-peptide ≥ 360 pg/mL, while BE was predicted by fractalkine ≥ 250 pg/mL and IP-10 ≥ 290 pg/mL. Finally, participants with GERD had significantly increased use of short-acting β-agonist compared to controls. Overall, biomarkers sampled prior to GERD/BE presentation showed strong predictive abilities of disease development. This study frames future investigations to further our understanding of aerodigestive pathology due to particulate matter exposure.

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS*

PubMed Central

Keller, Joshua P.; Drton, Mathias; Larson, Timothy; Kaufman, Joel D.; Sandler, Dale P.; Szpiro, Adam A.

2017-01-01

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP. PMID:28572869

Venous phase of computed tomography angiography increases spot sign detection, but intracerebral hemorrhage expansion is greater in spot signs detected in arterial phase.

PubMed

Rodriguez-Luna, David; Dowlatshahi, Dar; Aviv, Richard I; Molina, Carlos A; Silva, Yolanda; Dzialowski, Imanuel; Lum, Cheemun; Czlonkowska, Anna; Boulanger, Jean-Martin; Kase, Carlos S; Gubitz, Gord; Bhatia, Rohit; Padma, Vasantha; Roy, Jayanta; Stewart, Teri; Huynh, Thien J; Hill, Michael D; Demchuk, Andrew M

2014-03-01

Variability in computed tomography angiography (CTA) acquisitions may be one explanation for the modest accuracy of the spot sign for predicting intracerebral hemorrhage expansion detected in the multicenter Predicting Hematoma Growth and Outcome in Intracerebral Hemorrhage Using Contrast Bolus CT (PREDICT) study. This study aimed to determine the frequency of the spot sign in intracerebral hemorrhage and its relationship with hematoma expansion depending on the phase of image acquisition. PREDICT study was a prospective observational cohort study of patients with intracerebral hemorrhage presenting within 6 hours from onset. A post hoc analysis of the Hounsfield units of an artery and venous structure were measured on CTA source images of the entire PREDICT cohort in a core laboratory. Each CTA study was classified into arterial or venous phase and into 1 of 5 specific image acquisition phases. Significant hematoma expansion and total hematoma enlargement were recorded at 24 hours. Overall (n=371), 77.9% of CTA were acquired in arterial phase. The spot sign, present in 29.9% of patients, was more frequently seen in venous phase as compared with arterial phase (39% versus 27.3%; P=0.041) and the later the phase of image acquisition (P=0.095). Significant hematoma expansion (P=0.253) and higher total hematoma enlargement (P=0.019) were observed more frequently among spot sign-positive patients with earlier phases of image acquisition. Later image acquisition of CTA improves the frequency of spot sign detection. However, spot signs identified in earlier phases may be associated with greater absolute enlargement. A multiphase CTA including arterial and venous acquisitions could be optimal in patients with intracerebral hemorrhage.

Bell's palsy in children: Current treatment patterns in Australia and New Zealand. A PREDICT study.

PubMed

Babl, Franz E; Gardiner, Kaya K; Kochar, Amit; Wilson, Catherine L; George, Shane A; Zhang, Michael; Furyk, Jeremy; Thosar, Deepali; Cheek, John A; Krieser, David; Rao, Arjun S; Borland, Meredith L; Cheng, Nicholas; Phillips, Natalie T; Sinn, Kam K; Neutze, Jocelyn M; Dalziel, Stuart R

2017-04-01

The aetiology and clinical course of Bell's palsy may be different in paediatric and adult patients. There is no randomised placebo controlled trial (RCT) to show effectiveness of prednisolone for Bell's palsy in children. The aim of the study was to assess current practice in paediatric Bell's palsy in Australia and New Zealand Emergency Departments (ED) and determine the feasibility of conducting a multicentre RCT within the Paediatric Research in Emergency Departments International Collaborative (PREDICT). A retrospective analysis of ED medical records of children less than 18 years diagnosed with Bell's palsy between 1 January, 2012 and 31 December, 2013 was performed. Potential participants were identified from ED information systems using Bell's palsy related search terms. Repeat presentations during the same illness were excluded but relapses were not. Data on presentation, diagnosis and management were entered into an online data base (REDCap). Three hundred and twenty-three presentations were included from 14 PREDICT sites. Mean age at presentation was 9.0 (SD 5.0) years with 184 (57.0%) females. Most (238, 73.7%) presented to ED within 72 h of symptoms, 168 (52.0%) had seen a doctor prior. In ED, 218 (67.5%) were treated with steroids. Prednisolone was usually prescribed for 9 days at around 1 mg/kg/day, with tapering in 35.7%. Treatment of Bell's palsy in children presenting to Australasian EDs is varied. Prednisolone is commonly used in Australasian EDs, despite lack of high-level paediatric evidence. The study findings confirm the feasibility of an RCT of prednisolone for Bell's palsy in children. © 2017 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Predicting reasoning from memory.

PubMed

Heit, Evan; Hayes, Brett K

2011-02-01

In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the presence of stimuli from other categories, there was a high correlation between reasoning and memory responses (average r = .87), and these manipulations showed similar effects on the 2 tasks. The results point to common mechanisms underlying inductive reasoning and recognition memory abilities. A mathematical model, GEN-EX (generalization from examples), derived from exemplar models of categorization, is presented, which predicts both reasoning and memory responses from pairwise similarities among the stimuli, allowing for additional influences of subtyping and deterministic responding. (c) 2010 APA, all rights reserved.

[Diabetes and predictive medicine--parallax of the present time].

PubMed

Rybka, J

2010-04-01

Predictive genetics uses genetic testing to estimate the risk in asymptomatic persons. Since in the case of multifactorial diseases predictive genetic analysis deals with findings which allow wider interpretation, it has a higher predictive value in expressly qualified diseases (monogenous) with high penetration compared to multifactorial (polygenous) diseases with high participation of environmental factors. In most "civilisation" (multifactorial) diseases including diabetes, heredity and environmental factors do not play two separate, independent roles. Instead, their interactions play a principal role. The new classification of diabetes is based on the implementation of not only ethiopathogenetic, but also genetic research. Diabetes mellitus type 1 (DM1T) is a polygenous multifactorial disease with the genetic component carrying about one half of the risk, the non-genetic one the other half. The study of the autoimmune nature of DM1T in connection with genetic analysis is going to bring about new insights in DM1T prediction. The author presents new pieces of knowledge on molecular genetics concerning certain specific types of diabetes. Issues relating to heredity in diabetes mellitus type 2 (DM2T) are even more complex. The disease has a polygenous nature, and the phenotype of a patient with DM2T, in addition to environmental factors, involves at least three, perhaps even tens of different genetic variations. At present, results at the genom-wide level appear to be most promising. The current concept of prediabetes is a realistic foundation for our prediction and prevention of DM2T. A multifactorial, multimarker approach based on our understanding of new pathophysiological factors of DM2T, tries to outline a "map" of prediabetes physiology, and if these tests are combined with sophisticated methods of genetic forecasting of DM2T, this may represent a significant step in our methodology of diabetes prediction. So far however, predictive genetics is limited by the interpretation of genetic predisposition and individualisation of the level of risk. There is no doubt that interpretation calls for co-operation with clinicians, while results of genetic analyses should presently be not uncritically overestimated. Predictive medicine, however, unquestionably fulfills the preventive focus of modern medicine, and genetic analysis is a perspective diagnostic method.

The Effect of Self-Explanation and Prediction on the Development of Principled Understanding of Chess in Novices

ERIC Educational Resources Information Center

de Bruin, Anique B. H.; Rikers, Remy M. J. P.; Schmidt, Henk G.

2007-01-01

The present study was designed to test the effect of self-explanation and prediction on the development of principled understanding of novices learning to play chess. First-year psychology students, who had no chess experience, first learned the basic rules of chess and were afterwards divided in three conditions. They either observed (control…

Older Women, Deeper Learning, and Greater Satisfaction at University: Age and Gender Predict University Students' Learning Approach and Degree Satisfaction

ERIC Educational Resources Information Center

Rubin, Mark; Scevak, Jill; Southgate, Erica; Macqueen, Suzanne; Williams, Paul; Douglas, Heather

2018-01-01

The present study explored the interactive effect of age and gender in predicting surface and deep learning approaches. It also investigated how these variables related to degree satisfaction. Participants were 983 undergraduate students at a large public Australian university. They completed a research survey either online or on paper. Consistent…

Does Growth in Working Memory Span or Executive Processes Predict Growth in Reading and Math in Children with Reading Disabilities?

ERIC Educational Resources Information Center

Jerman, Olga; Reynolds, Chandra; Swanson, H. Lee

2012-01-01

The present study investigated whether (a) growth patterns related to cognitive processing (working memory, updating, inhibition) differed in subgroups of children with reading disabilities (RD) and (b) growth in working memory (executive processing) predicted growth in other cognitive areas, such as reading and math. Seventy-three children (ages…

The Predictive Ability of IQ and Working Memory Scores in Literacy in an Adult Population

ERIC Educational Resources Information Center

Alloway, Tracy Packiam; Gregory, David

2013-01-01

Literacy problems are highly prevalent and can persist into adulthood. Yet, the majority of research on the predictive nature of cognitive skills to literacy has primarily focused on development and adolescent populations. The aim of the present study was to extend existing research to investigate the roles of IQ scores and Working Memory…

Assessment of modification factors for a row of bolts or timber connectors

Treesearch

Thomas Lee Wilkinson

1980-01-01

When bolts or timber connectors are used in a row, with load applied parallel to the row, load will be unequally distributed among the fasteners. This study assessed methods of predicting this unequal load distribution, looked at how joint variables can affect the distribution, and compared the predictions with data existing in the literature. Presently used design...

The Comparative Effects of Prediction/Discussion-Based Learning Cycle, Conceptual Change Text, and Traditional Instructions on Student Understanding of Genetics

ERIC Educational Resources Information Center

Yilmaz, Diba; Tekkaya, Ceren; Sungur, Semra

2011-01-01

The present study examined the comparative effects of a prediction/discussion-based learning cycle, conceptual change text (CCT), and traditional instructions on students' understanding of genetics concepts. A quasi-experimental research design of the pre-test-post-test non-equivalent control group was adopted. The three intact classes, taught by…

Parent- and Self-Reported Dimensions of Oppositionality in Youth: Construct Validity, Concurrent Validity, and the Prediction of Criminal Outcomes in Adulthood

ERIC Educational Resources Information Center

Aebi, Marcel; Plattner, Belinda; Metzke, Christa Winkler; Bessler, Cornelia; Steinhausen, Hans-Christoph

2013-01-01

Background: Different dimensions of oppositional defiant disorder (ODD) have been found as valid predictors of further mental health problems and antisocial behaviors in youth. The present study aimed at testing the construct, concurrent, and predictive validity of ODD dimensions derived from parent- and self-report measures. Method: Confirmatory…

Aptitude and Trait Predictors of Manned and Unmanned Aircraft Pilot Job Performance

DTIC Science & Technology

2016-04-22

actually fly RPAs. To address this gap, the present study evaluated pre-accession trait (Big Five personality domains) and aptitude (spatial...knowledge, and personality traits that predict successful job performance for manned aircraft pilots also predict successful job performance for RPA...aptitude and personality traits , job performance, remotely-piloted aircraft, unmanned aircraft systems 16. SECURITY CLASSIFICATION OF: 17

Stationary measure in the multiverse

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

Linde, Andrei; Vanchurin, Vitaly; Winitzki, Sergei, E-mail: alinde@stanford.edu, E-mail: vitaly@cosmos2.phy.tufts.edu, E-mail: winitzki@physik.uni-muenchen.de

2009-01-15

We study the recently proposed ''stationary measure'' in the context of the string landscape scenario. We show that it suffers neither from the ''Boltzmann brain'' problem nor from the ''youngness'' paradox that makes some other measures predict a high CMB temperature at present. We also demonstrate a good performance of this measure in predicting the results of local experiments, such as proton decay.

Use of plasma orosomucoid in newborn piglets to predict preweaning growth performance and its mechanism of action

USDA-ARS?s Scientific Manuscript database

Orosomucoid (ORM) is the most prevalent serum protein in the newborn pig. The present study was designed to determine if plasma ORM at birth can be used to predict the relative performance of piglets within a litter between birth and weaning using a highly sensitive ELISA specific for pig ORM. Sec...

Predicting Presence of Offender's Criminal Record From Antisocial Lifestyle Indicators of Homicide Victims

ERIC Educational Resources Information Center

Santtila, Pekka; Runtti, Markus; Mokros, Andreas

2004-01-01

The aim of the present study is to explore the possibility of predicting the presence of a criminal record in the background of a homicide offender on the basis of victim characteristics. Eight victim characteristics, as well as the presence or absence of offender criminal record and offender violent criminal record, were coded for 502 Finnish…

Prediction Of Critical Crack Sizes In Solar Cells

NASA Technical Reports Server (NTRS)

Chen, Chern P.

1989-01-01

Report presents theoretical analysis of cracking in Si and GaAs solar photovoltaic cells subjected to bending or twisting. Analysis also extended to predict critical sizes for cracks in Ge substrate coated with thin film of GaAs. Analysis leads to general conclusions. Approach and results of study useful in development of guidelines for acceptance or rejection of slightly flawed cells during manufacture.

Noun and Verb Production in Maternal and Child Language: Continuity, Stability, and Prediction across the Second Year of Life

ERIC Educational Resources Information Center

Longobardi, Emiddia; Spataro, Pietro; Putnick, Diane L.; Bornstein, Marc H.

2016-01-01

The present study examined continuity/discontinuity and stability/instability of noun and verb production measures in 30 child-mother dyads observed at 16 and 20 months, and predictive relations with the acquisition of nouns and verbs at 24 months. Children exhibited significant discontinuity and robust stability in the frequency of nouns and…

Height-diameter equations for thirteen midwestern bottomland hardwood species

Treesearch

Kenneth C. Colbert; David R. Larsen; James R. Lootens

2002-01-01

Height-diameter equations are often used to predict the mean total tree height for trees when only diameter at breast height (dbh) is measured. Measuring dbh is much easier and is subject to less measurement error than total tree height. However, predicted heights only reflect the average height for trees of a particular diameter. In this study, we present a set of...

Can future land use change be usefully predicted?

NASA Astrophysics Data System (ADS)

Ramankutty, N.; Coomes, O.

2011-12-01

There has been increasing recognition over the last decade that land use and land cover change is an important driver of global environmental change. Consequently, there have been growing efforts to understanding processes of land change from local-to-global scales, and to develop models to predict future changes in the land. However, we believe that such efforts are hampered by limited attention being paid to the critical points of land change. Here, we present a framework for understanding land use change by distinguishing within-regime land-use dynamics from land-use regime shifts. Illustrative historical examples reveal the significance of land-use regime shifts. We further argue that the land-use literature predominantly demonstrates a good understanding (with predictive power) of within-regime dynamics, while understanding of land-use regime shifts is limited to ex post facto explanations with limited predictive capability. The focus of land use change science needs to be redirected toward studying land-use regime shifts if we are to have any hope of making useful future projections. We present a preliminary framework for understanding land-use regime-shifts, using two case studies in Latin America as examples. We finally discuss the implications of our proposal for land change science.

Data base for the prediction of inlet external drag

NASA Technical Reports Server (NTRS)

Mcmillan, O. J.; Perkins, E. W.; Perkins, S. C., Jr.

1980-01-01

Results are presented from a study to define and evaluate the data base for predicting an airframe/propulsion system interference effect shown to be of considerable importance, inlet external drag. The study is focused on supersonic tactical aircraft with highly integrated jet propulsion systems, although some information is included for supersonic strategic aircraft and for transport aircraft designed for high subsonic or low supersonic cruise. The data base for inlet external drag is considered to consist of the theoretical and empirical prediction methods as well as the experimental data identified in an extensive literature search. The state of the art in the subsonic and transonic speed regimes is evaluated. The experimental data base is organized and presented in a series of tables in which the test article, the quantities measured and the ranges of test conditions covered are described for each set of data; in this way, the breadth of coverage and gaps in the existing experimental data are evident. Prediction methods are categorized by method of solution, type of inlet and speed range to which they apply, major features are given, and their accuracy is assessed by means of comparison to experimental data.

The Importance of Adolescents' Sexually Outgoing Self-Concept: Differential Roles of Self- and Other-Generated Sexy Self-Presentations in Social Media.

PubMed

van Oosten, Johanna M F; de Vries, Dian A; Peter, Jochen

2018-01-01

The present study investigated the relationships between (exposure to) sexy self-presentations on social network sites (SNSs) and adolescents' sexual self-concept over time. Results from a three-wave panel study among 1,288 Dutch adolescents (aged 13-17 years) showed that more frequent engagement in sexy self-presentation, rather than exposure to sexy self-presentations of others, on SNSs positively predicted the importance of being sexually outgoing (e.g., sexy, seductive, and wild) in adolescents' self-concept 6 months later.

A Numerical Round Robin for the Reliability Prediction of Structural Ceramics

NASA Technical Reports Server (NTRS)

Powers, Lynn M.; Janosik, Lesley A.

1993-01-01

A round robin has been conducted on integrated fast fracture design programs for brittle materials. An informal working group (WELFEP-WEakest Link failure probability prediction by Finite Element Postprocessors) was formed to discuss and evaluate the implementation of the programs examined in the study. Results from the study have provided insight on the differences between the various programs examined. Conclusions from the study have shown that when brittle materials are used in design, analysis must understand how to apply the concepts presented herein to failure probability analysis.

HKF-R 10 - screening for predicting chronicity in acute low back pain (LBP): a prospective clinical trial.

PubMed

Neubauer, Eva; Junge, Astrid; Pirron, Peter; Seemann, Hanne; Schiltenwolf, Marcus

2006-08-01

Prospective cohort study. To develop a short instrument to reliably predict chronicity in low back pain (LBP). Health care expenditures on the treatment of low back pain continue to increase. It is therefore important to prevent the development of chronicity. In Germany, there is at present no early risk assessment tool to predict the risk of developing chronic LBP for patients presenting with acute LBP. Undertaken in an orthopedic practice setting, this study examined known risk factors for chronicity. It resulted in the development of a short questionnaire that successfully predicted the course of chronicity with an accuracy of 78%. A cohort of 192 orthopaedic outpatients was assessed for clinical, behavioral, emotional, and cognitive parameters bsed on a self-report test battery of 167 established items predictive for chronicity in LBP. Chronicity was defined as back pain persisting for longer than six months. Logistic regression analysis was performed to evaluate the predictive value of all items significantly associated with the dependent variable. The study found the following items to have the strongest predictive value in the development of chronicity: "How strong was your back pain during the last week when it was most tolerable?" and the question "How much residual pain would you be willing to tolerate while still considering the therapy successful?" These were followed by the variables for "Duration of existing LBP" (more than eight days), the patient's educational level (low levels are related to higher risks of chronicity) and pain being experienced elsewhere in the body. Other significant factors were five items assessing depression (Zung) and the palliative effect of therapeutic massage (where a positive correlation was found). Female patients have a higher risk for chronicity, as do patients with a high total score on the scales assessing "catastrophizing thoughts" and thoughts of "helplessness". Using the items listed above, the study was able to predict a patient's risk of developing chronic LBP with a probability of 78%. These items were assembled in a brief questionnaire and were paired with a corresponding evaluative tool. This enables practitioners to assess an individual patient's risk for chronicity by means of a simple calculator in just a few minutes. A validation study for the questionnaire is currently being prepared. MINI ABSTRACT: The objective of this study was the development of a brief questionnaire to assess the risk for chronicity for LBP.

Time-series analysis of hepatitis A, B, C and E infections in a large Chinese city: application to prediction analysis.

PubMed

Sumi, A; Luo, T; Zhou, D; Yu, B; Kong, D; Kobayashi, N

2013-05-01

Viral hepatitis is recognized as one of the most frequently reported diseases, and especially in China, acute and chronic liver disease due to viral hepatitis has been a major public health problem. The present study aimed to analyse and predict surveillance data of infections of hepatitis A, B, C and E in Wuhan, China, by the method of time-series analysis (MemCalc, Suwa-Trast, Japan). On the basis of spectral analysis, fundamental modes explaining the underlying variation of the data for the years 2004-2008 were assigned. The model was calculated using the fundamental modes and the underlying variation of the data reproduced well. An extension of the model to the year 2009 could predict the data quantitatively. Our study suggests that the present method will allow us to model the temporal pattern of epidemics of viral hepatitis much more effectively than using the artificial neural network, which has been used previously.

Language-driven anticipatory eye movements in virtual reality.

PubMed

Eichert, Nicole; Peeters, David; Hagoort, Peter

2018-06-01

Predictive language processing is often studied by measuring eye movements as participants look at objects on a computer screen while they listen to spoken sentences. This variant of the visual-world paradigm has revealed that information encountered by a listener at a spoken verb can give rise to anticipatory eye movements to a target object, which is taken to indicate that people predict upcoming words. The ecological validity of such findings remains questionable, however, because these computer experiments used two-dimensional stimuli that were mere abstractions of real-world objects. Here we present a visual-world paradigm study in a three-dimensional (3-D) immersive virtual reality environment. Despite significant changes in the stimulus materials and the different mode of stimulus presentation, language-mediated anticipatory eye movements were still observed. These findings thus indicate that people do predict upcoming words during language comprehension in a more naturalistic setting where natural depth cues are preserved. Moreover, the results confirm the feasibility of using eyetracking in rich and multimodal 3-D virtual environments.

Systematic Review: Predisposing, Precipitating, Perpetuating, and Present Factors Predicting Anticipatory Distress to Painful Medical Procedures in Children

PubMed Central

Pillai Riddell, Rebecca R.; Khan, Maria; Calic, Masa; Taddio, Anna; Tablon, Paula

2016-01-01

Objective To conduct a systematic review of the factors predicting anticipatory distress to painful medical procedures in children. Methods A systematic search was conducted to identify studies with factors related to anticipatory distress to painful medical procedures in children aged 0–18 years. The search retrieved 7,088 articles to review against inclusion criteria. A total of 77 studies were included in the review. Results 31 factors were found to predict anticipatory distress to painful medical procedures in children. A narrative synthesis of the evidence was conducted, and a summary figure is presented. Conclusions Many factors were elucidated that contribute to the occurrence of anticipatory distress to painful medical procedures. The factors that appear to increase anticipatory distress are child psychopathology, difficult child temperament, parent distress promoting behaviors, parent situational distress, previous pain events, parent anticipation of distress, and parent anxious predisposition. Longitudinal and experimental research is needed to further elucidate these factors. PMID:26338981

DRA/NASA/ONERA Collaboration on Icing Research. Part 2; Prediction of Airfoil Ice Accretion

NASA Technical Reports Server (NTRS)

Wright, William B.; Gent, R. W.; Guffond, Didier

1997-01-01

This report presents results from a joint study by DRA, NASA, and ONERA for the purpose of comparing, improving, and validating the aircraft icing computer codes developed by each agency. These codes are of three kinds: (1) water droplet trajectory prediction, (2) ice accretion modeling, and (3) transient electrothermal deicer analysis. In this joint study, the agencies compared their code predictions with each other and with experimental results. These comparison exercises were published in three technical reports, each with joint authorship. DRA published and had first authorship of Part 1 - Droplet Trajectory Calculations, NASA of Part 2 - Ice Accretion Prediction, and ONERA of Part 3 - Electrothermal Deicer Analysis. The results cover work done during the period from August 1986 to late 1991. As a result, all of the information in this report is dated. Where necessary, current information is provided to show the direction of current research. In this present report on ice accretion, each agency predicted ice shapes on two dimensional airfoils under icing conditions for which experimental ice shapes were available. In general, all three codes did a reasonable job of predicting the measured ice shapes. For any given experimental condition, one of the three codes predicted the general ice features (i.e., shape, impingement limits, mass of ice) somewhat better than did the other two. However, no single code consistently did better than the other two over the full range of conditions examined, which included rime, mixed, and glaze ice conditions. In several of the cases, DRA showed that the user's knowledge of icing can significantly improve the accuracy of the code prediction. Rime ice predictions were reasonably accurate and consistent among the codes, because droplets freeze on impact and the freezing model is simple. Glaze ice predictions were less accurate and less consistent among the codes, because the freezing model is more complex and is critically dependent upon unsubstantiated heat transfer and surface roughness models. Thus, heat transfer prediction methods used in the codes became the subject for a separate study in this report to compare predicted heat transfer coefficients with a limited experimental database of heat transfer coefficients for cylinders with simulated glaze and rime ice shapes. The codes did a good job of predicting heat transfer coefficients near the stagnation region of the ice shapes. But in the region of the ice horns, all three codes predicted heat transfer coefficients considerably higher than the measured values. An important conclusion of this study is that further research is needed to understand the finer detail of of the glaze ice accretion process and to develop improved glaze ice accretion models.

Decisional strategy determines whether frame influences treatment preferences for medical decisions.

PubMed

Woodhead, Erin L; Lynch, Elizabeth B; Edelstein, Barry A

2011-06-01

Decision makers are influenced by the frame of information such that preferences vary depending on whether survival or mortality data are presented. Research is inconsistent as to whether and how age impacts framing effects. This paper presents two studies that used qualitative analyses of think-aloud protocols to understand how the type of information used in the decision making process varies by frame and age. In Study 1, 40 older adults, age 65 to 89, and 40 younger adults, age 18 to 24, responded to a hypothetical lung cancer scenario in a within-subject design. Participants received both a survival and mortality frame. Qualitative analyses revealed that two main decisional strategies were used by all participants: one strategy reflected a data-driven decisional process, whereas the other reflected an experience-driven process. Age predicted decisional strategy, with older adults less likely to use a data-driven strategy. Frame interacted with strategy to predict treatment choice; only those using a data-driven strategy demonstrated framing effects. In Study 2, 61 older adults, age 65 to 98, and 63 younger adults, age 18 to 30, responded to the same scenarios as in Study 1 in a between-subject design. The results of Study 1 were replicated, with age significantly predicting decisional strategy and frame interacting with strategy to predict treatment choice. Findings suggest that framing effects may be more related to decisional strategy than to age. (c) 2011 APA, all rights reserved.

Validation and Use of a Predictive Modeling Tool: Employing Scientific Findings to Improve Responsible Conduct of Research Education.

PubMed

Mulhearn, Tyler J; Watts, Logan L; Todd, E Michelle; Medeiros, Kelsey E; Connelly, Shane; Mumford, Michael D

2017-01-01

Although recent evidence suggests ethics education can be effective, the nature of specific training programs, and their effectiveness, varies considerably. Building on a recent path modeling effort, the present study developed and validated a predictive modeling tool for responsible conduct of research education. The predictive modeling tool allows users to enter ratings in relation to a given ethics training program and receive instantaneous evaluative information for course refinement. Validation work suggests the tool's predicted outcomes correlate strongly (r = 0.46) with objective course outcomes. Implications for training program development and refinement are discussed.

The Williams' legacy: A critical reappraisal of his nine predictions about the evolution of senescence.

PubMed

Gaillard, Jean-Michel; Lemaître, Jean-François

2017-12-01

Williams' evolutionary theory of senescence based on antagonistic pleiotropy has become a landmark in evolutionary biology, and more recently in biogerontology and evolutionary medicine. In his original article, Williams launched a set of nine "testable deductions" from his theory. Although some of these predictions have been repeatedly discussed, most have been overlooked and no systematic evaluation of the whole set of Williams' original predictions has been performed. For the sixtieth anniversary of the publication of the Williams' article, we provide an updated evaluation of all these predictions. We present the pros and cons of each prediction based on recent accumulation of both theoretical and empirical studies performed in the laboratory and in the wild. From our viewpoint, six predictions are mostly supported by our current knowledge at least under some conditions (although Williams' theory cannot thoroughly explain why for some of them). Three predictions, all involving the timing of senescence, are not supported. Our critical review of Williams' predictions highlights the importance of William's contribution and clearly demonstrates that, 60 years after its publication, his article does not show any sign of senescence. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

NASA Technical Reports Server (NTRS)

Farassat, F.; Doty, Michael J.; Hunter, Craig A.

2004-01-01

The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

Tone Noise Predictions for a Spacecraft Cabin Ventilation Fan Ingesting Distorted Inflow and the Challenges of Validation

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Shook, Tony D.; Astler, Douglas T.; Bittinger, Samantha A.

2011-01-01

A fan tone noise prediction code has been developed at NASA Glenn Research Center that is capable of estimating duct mode sound power levels for a fan ingesting distorted inflow. This code was used to predict the circumferential and radial mode sound power levels in the inlet and exhaust duct of an axial spacecraft cabin ventilation fan. Noise predictions at fan design rotational speed were generated. Three fan inflow conditions were studied: an undistorted inflow, a circumferentially symmetric inflow distortion pattern (cylindrical rods inserted radially into the flowpath at 15deg, 135deg, and 255deg), and a circumferentially asymmetric inflow distortion pattern (rods located at 15deg, 52deg and 173deg). Noise predictions indicate that tones are produced for the distorted inflow cases that are not present when the fan operates with an undistorted inflow. Experimental data are needed to validate these acoustic predictions, as well as the aerodynamic performance predictions. Given the aerodynamic design of the spacecraft cabin ventilation fan, a mechanical and electrical conceptual design study was conducted. Design features of a fan suitable for obtaining detailed acoustic and aerodynamic measurements needed to validate predictions are discussed.

Tone Noise Predictions for a Spacecraft Cabin Ventilation Fan Ingesting Distorted Inflow and the Challenges of Validation

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Shook, Tony D.; Astler, Douglas T.; Bittinger, Samantha A.

2012-01-01

A fan tone noise prediction code has been developed at NASA Glenn Research Center that is capable of estimating duct mode sound power levels for a fan ingesting distorted inflow. This code was used to predict the circumferential and radial mode sound power levels in the inlet and exhaust duct of an axial spacecraft cabin ventilation fan. Noise predictions at fan design rotational speed were generated. Three fan inflow conditions were studied: an undistorted inflow, a circumferentially symmetric inflow distortion pattern (cylindrical rods inserted radially into the flowpath at 15deg, 135deg, and 255deg), and a circumferentially asymmetric inflow distortion pattern (rods located at 15deg, 52deg and 173deg). Noise predictions indicate that tones are produced for the distorted inflow cases that are not present when the fan operates with an undistorted inflow. Experimental data are needed to validate these acoustic predictions, as well as the aerodynamic performance predictions. Given the aerodynamic design of the spacecraft cabin ventilation fan, a mechanical and electrical conceptual design study was conducted. Design features of a fan suitable for obtaining detailed acoustic and aerodynamic measurements needed to validate predictions are discussed.

Behaviour and burnout in medical students.

PubMed

Cecil, Jo; McHale, Calum; Hart, Jo; Laidlaw, Anita

2014-01-01

Background Burnout is prevalent in doctors and can impact on job dissatisfaction and patient care. In medical students, burnout is associated with poorer self-rated health; however, it is unclear what factors influence its development. This study investigated whether health behaviours predict burnout in medical students. Methods Medical students (n=356) at the Universities of St Andrews and Manchester completed an online questionnaire assessing: emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA), alcohol use, physical activity, diet, and smoking. Results Approximately 55% (54.8%) of students reported high levels of EE, 34% reported high levels of DP, and 46.6% reported low levels of PA. Linear regression analysis revealed that year of study, physical activity, and smoking status significantly predicted EE whilst gender, year of study, and institution significantly predicted DP. PA was significantly predicted by alcohol binge score, year of study, gender, and physical activity. Conclusions Burnout is present in undergraduate medical students in the United Kingdom, and health behaviours, particularly physical activity, predict components of burnout. Gender, year of study, and institution also appear to influence the prevalence of burnout. Encouraging medical students to make healthier lifestyle choices early in their medical training may reduce the likelihood of the development of burnout.

Behaviour and burnout in medical students

PubMed Central

Cecil, Jo; McHale, Calum; Hart, Jo; Laidlaw, Anita

2014-01-01

Background Burnout is prevalent in doctors and can impact on job dissatisfaction and patient care. In medical students, burnout is associated with poorer self-rated health; however, it is unclear what factors influence its development. This study investigated whether health behaviours predict burnout in medical students. Methods Medical students (n=356) at the Universities of St Andrews and Manchester completed an online questionnaire assessing: emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA), alcohol use, physical activity, diet, and smoking. Results Approximately 55% (54.8%) of students reported high levels of EE, 34% reported high levels of DP, and 46.6% reported low levels of PA. Linear regression analysis revealed that year of study, physical activity, and smoking status significantly predicted EE whilst gender, year of study, and institution significantly predicted DP. PA was significantly predicted by alcohol binge score, year of study, gender, and physical activity. Conclusions Burnout is present in undergraduate medical students in the United Kingdom, and health behaviours, particularly physical activity, predict components of burnout. Gender, year of study, and institution also appear to influence the prevalence of burnout. Encouraging medical students to make healthier lifestyle choices early in their medical training may reduce the likelihood of the development of burnout. PMID:25160716

Behaviour and burnout in medical students.

PubMed

Cecil, Jo; McHale, Calum; Hart, Jo; Laidlaw, Anita

2014-01-01

Burnout is prevalent in doctors and can impact on job dissatisfaction and patient care. In medical students, burnout is associated with poorer self-rated health; however, it is unclear what factors influence its development. This study investigated whether health behaviours predict burnout in medical students. Medical students (n=356) at the Universities of St Andrews and Manchester completed an online questionnaire assessing: emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA), alcohol use, physical activity, diet, and smoking. Approximately 55% (54.8%) of students reported high levels of EE, 34% reported high levels of DP, and 46.6% reported low levels of PA. Linear regression analysis revealed that year of study, physical activity, and smoking status significantly predicted EE whilst gender, year of study, and institution significantly predicted DP. PA was significantly predicted by alcohol binge score, year of study, gender, and physical activity. Burnout is present in undergraduate medical students in the United Kingdom, and health behaviours, particularly physical activity, predict components of burnout. Gender, year of study, and institution also appear to influence the prevalence of burnout. Encouraging medical students to make healthier lifestyle choices early in their medical training may reduce the likelihood of the development of burnout.

Validation of the close-to-delivery prediction model for vaginal birth after cesarean delivery in a Middle Eastern cohort.

PubMed

Abdel Aziz, Ahmed; Abd Rabbo, Amal; Sayed Ahmed, Waleed A; Khamees, Rasha E; Atwa, Khaled A

2016-07-01

To validate a prediction model for vaginal birth after cesarean (VBAC) that incorporates variables available at admission for delivery among Middle Eastern women. The present prospective cohort study enrolled women at 37weeks of pregnancy or more with cephalic presentation who were willing to attempt a trial of labor (TOL) after a single prior low transverse cesarean delivery at Al-Jahra Hospital, Kuwait, between June 2013 and June 2014. The predicted success rate of VBAC determined via the close-to-delivery prediction model of Grobman et al. was compared between participants whose TOL was and was not successful. Among 203 enrolled women, 140 (69.0%) had successful VBAC. The predicted VBAC success rate was higher among women with successful TOL (82.4%±13.1%) than among those with failed TOL (67.7%±18.3%; P<0.001). There was a high positive correlation between actual and predicted success rates. For deciles of predicted success rate increasing from >30%-40% to >90%-100%, the actual success rate was 20%, 30.7%, 38.5%, 59.1%, 71.4%, 76%, and 84.5%, respectively (r=0.98, P=0.013). The close-to-delivery prediction model was found to be applicable to Middle Eastern women and might predict VBAC success rates, thereby decreasing morbidities associated with failed TOL. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Numerical and experimental investigation of the bending response of thin-walled composite cylinders

NASA Technical Reports Server (NTRS)

Fuchs, J. P.; Hyer, M. W.; Starnes, J. H., Jr.

1993-01-01

A numerical and experimental investigation of the bending behavior of six eight-ply graphite-epoxy circular cylinders is presented. Bending is induced by applying a known end-rotation to each end of the cylinders, analogous to a beam in bending. The cylinders have a nominal radius of 6 inches, a length-to-radius ratio of 2 and 5, and a radius-to-thickness ratio of approximately 160. A (+/- 45/0/90)S quasi-isotropic layup and two orthotropic layups, (+/- 45/0 sub 2)S and (+/- 45/90 sub 2)S, are studied. A geometrically nonlinear special-purpose analysis, based on Donnell's nonlinear shell equations, is developed to study the prebuckling responses and gain insight into the effects of non-ideal boundary conditions and initial geometric imperfections. A geometrically nonlinear finite element analysis is utilized to compare with the prebuckling solutions of the special-purpose analysis and to study the buckling and post buckling responses of both geometrically perfect and imperfect cylinders. The imperfect cylinder geometries are represented by an analytical approximation of the measured shape imperfections. Extensive experimental data are obtained from quasi-static tests of the cylinders using a test fixture specifically designed for the present investigation. A description of the test fixture is included. The experimental data are compared to predictions for both perfect and imperfect cylinder geometries. Prebuckling results are presented in the form of displacement and strain profiles. Buckling end-rotations, moments, and strains are reported, and predicted mode shapes are presented. Observed and predicted moment vs. end-rotation relations, deflection patterns, and strain profiles are illustrated for the post buckling responses. It is found that a geometrically nonlinear boundary layer behavior characterizes the prebuckling responses. The boundary layer behavior is sensitive to laminate orthotropy, cylinder geometry, initial geometric imperfections, applied end-rotation, and non-ideal boundary conditions. Buckling end-rotations, strains, and moments are influenced by laminate orthotropy and initial geometric imperfections. Measured buckling results correlate well with predictions for the geometrically imperfect specimens. The postbuckling analyses predict equilibrium paths with a number of scallop-shaped branches that correspond to unique deflection patterns. The observed postbuckling deflection patterns and measured strain profiles show striking similarities to the predictions in some cases. Ultimate failure of the cylinders is attributed to an interlaminar shear failure mode along the nodal lines of the postbuckling deflection patterns.

Interpretation biases in victims and non-victims of interpersonal trauma and their relation to symptom development.

PubMed

Elwood, Lisa S; Williams, Nathan L; Olatunji, Bunmi O; Lohr, Jeffrey M

2007-01-01

Previous studies examining information processing in posttraumatic stress disorder (PTSD) have focused on attention and memory biases, with few studies examining interpretive biases. The majority of these studies have employed lexically based methodologies, rather than examining the processing of visual information. In the present study, victims (N=40) and non-victims (N=41) of interpersonal trauma viewed a series of short positive, neutral, and threatening filmstrips of social situations with ambiguous endings. Participants were then asked about their perceptions and interpretations of the situations. Victims perceived threatening situations as more predictable and more quickly increasing in risk than non-victims. Trauma status interacted with the perceived predictability of positive situations and the perceived speed with which neutral situations reached their conclusion to predict anxious symptoms. In addition, trauma status interacted with the perceived increase in risk of positive situations to predict PTSD symptoms. The implications of these findings for theories of PTSD are discussed.

Early lactate clearance for predicting active bleeding in critically ill patients with acute upper gastrointestinal bleeding: a retrospective study.

PubMed

Wada, Tomoki; Hagiwara, Akiyoshi; Uemura, Tatsuki; Yahagi, Naoki; Kimura, Akio

2016-08-01

Not all patients with upper gastrointestinal bleeding (UGIB) require emergency endoscopy. Lactate clearance has been suggested as a parameter for predicting patient outcomes in various critical care settings. This study investigates whether lactate clearance can predict active bleeding in critically ill patients with UGIB. This single-center, retrospective, observational study included critically ill patients with UGIB who met all of the following criteria: admission to the emergency department (ED) from April 2011 to August 2014; had blood samples for lactate evaluation at least twice during the ED stay; and had emergency endoscopy within 6 h of ED presentation. The main outcome was active bleeding detected with emergency endoscopy. Classification and regression tree (CART) analyses were performed using variables associated with active bleeding to derive a prediction rule for active bleeding in critically ill UGIB patients. A total of 154 patients with UGIB were analyzed, and 31.2 % (48/154) had active bleeding. In the univariate analysis, lactate clearance was significantly lower in patients with active bleeding than in those without active bleeding (13 vs. 29 %, P < 0.001). Using the CART analysis, a prediction rule for active bleeding is derived, and includes three variables: lactate clearance; platelet count; and systolic blood pressure at ED presentation. The rule has 97.9 % (95 % CI 90.2-99.6 %) sensitivity with 32.1 % (28.6-32.9 %) specificity. Lactate clearance may be associated with active bleeding in critically ill patients with UGIB, and may be clinically useful as a component of a prediction rule for active bleeding.

Prediction of thermal cycling induced cracking in polymer matrix composites

NASA Technical Reports Server (NTRS)

Mcmanus, Hugh L.

1993-01-01

This report summarizes the work done in the period February 1993 through July 1993 on the 'Prediction of Thermal Cycling Induced Cracking In Polymer Matrix Composites' program. An oral presentation of this work was given to Langley personnel in September of 1993. This document was prepared for archival purposes. Progress studies have been performed on the effects of spatial variations in material strength. Qualitative agreement was found with observed patterns of crack distribution. These results were presented to NASA Langley personnel in November 1992. The analytical methodology developed by Prof. McManus in the summer of 1992 (under an ASEE fellowship) has been generalized. A method for predicting matrix cracking due to decreasing temperatures and/or thermal cycling in all plies of an arbitrary laminate has been implemented as a computer code. The code also predicts changes in properties due to the cracking. Experimental progressive cracking studies on a variety of laminates were carried out at Langley Research Center. Results were correlated to predictions using the new methods. Results were initially mixed. This motivated an exploration of the configuration of cracks within laminates. A crack configuration study was carried out by cutting and/or sanding specimens in order to examine the distribution of cracks within the specimens. These investigations were supplemented by dye-penetrant enhanced X-ray photographs. The behavior of thin plies was found to be different from the behavior of thicker plies (or ply groups) on which existing theories are based. Significant edge effects were also noted, which caused the traditional metric of microcracking (count of cracks on a polished edge) to be very inaccurate in some cases. With edge and configuration taken into account, rough agreement with predictions was achieved. All results to date were reviewed with NASA Langley personnel in September 1993.

The influence of a wall function on turbine blade heat transfer prediction

NASA Technical Reports Server (NTRS)

Whitaker, Kevin W.

1989-01-01

The second phase of a continuing investigation to improve the prediction of turbine blade heat transfer coefficients was completed. The present study specifically investigated how a numeric wall function in the turbulence model of a two-dimensional boundary layer code, STAN5, affected heat transfer prediction capabilities. Several sources of inaccuracy in the wall function were identified and then corrected or improved. Heat transfer coefficient predictions were then obtained using each one of the modifications to determine its effect. Results indicated that the modifications made to the wall function can significantly affect the prediction of heat transfer coefficients on turbine blades. The improvement in accuracy due the modifications is still inconclusive and is still being investigated.

Predict the fatigue life of crack based on extended finite element method and SVR

NASA Astrophysics Data System (ADS)

Song, Weizhen; Jiang, Zhansi; Jiang, Hui

2018-05-01

Using extended finite element method (XFEM) and support vector regression (SVR) to predict the fatigue life of plate crack. Firstly, the XFEM is employed to calculate the stress intensity factors (SIFs) with given crack sizes. Then predicetion model can be built based on the function relationship of the SIFs with the fatigue life or crack length. Finally, according to the prediction model predict the SIFs at different crack sizes or different cycles. Because of the accuracy of the forward Euler method only ensured by the small step size, a new prediction method is presented to resolve the issue. The numerical examples were studied to demonstrate the proposed method allow a larger step size and have a high accuracy.

What to do on spring break? The role of predicted, on-line, and remembered experience in future choice.

PubMed

Wirtz, Derrick; Kruger, Justin; Napa Scollon, Christie; Diener, Ed

2003-09-01

When individuals choose future activities on the basis of their past experiences, what guides those choices? The present study compared students' predicted, on-line, and remembered spring-break experiences, as well as the influence of these factors on students' desire to take a similar vacation in the future. Predicted and remembered experiences were both more positive-and, paradoxically, more negative-than on-line experiences. Of key importance, path analyses revealed that remembered experience, but neither on-line nor anticipated experience, directly predicted the desire to repeat the experience. These results suggest that although on-line measures may be superior to retrospective measures for approximating objective experience, retrospective measures may be superior for predicting choice.

Hyperbilirubinemia as a Diagnostic Tool for the Prediction of Appendicular Perforation: A Prospective Study.

PubMed

Saxena, Divish; Tandon, Mrinal; Shah, Yunus; Gedam, B S

2015-01-01

The certainty of diagnosing acute appendicitis in patients presenting with right iliac fossa pain still remains a mystery though acute appendicitis being the commonest surgical procedure done in emergency. In acute appendicitis, serum bilirubin levels are raised due to hepatocellular damage as a result of direct insult caused by Gram-negative bacterial endotoxemia. The need for the study is to conclude whether the serum bilirubin can be considered as a new laboratory marker to aid in the diagnosis of acute appendicitis and if so, does it have the predictive capacity to warn us about appendicular perforation. This is a prospective study carried out at rural tertiary healthcare center and includes 213 patients clinically diagnosed as acute appendicitis. Out of 213 patients, raised serum bilirubin ≥1.2 mg/dl was present in 195 (91.5%) patients, out of which 194 (99.4%) patients had histopathologically inflamed appendix and this difference was statistically highly significant with p-value < 0.0001. In this study, 32 patients had perforated appendix. Out of those, 30 patients had bilirubin ≥ 4 mg/dl and 2 patients had bilirubin level between 1.2 and < 4 mg/dl. Raised serum bilirubin (≥4 mg/dl) was present in 35 (17.9%) patients, out of which 30 (87.7%) patients had perforated appendix. Saxena D, Tandon M, Shah Y, Gedam BS. Hyperbilirubinemia as a Diagnostic Tool for the Prediction of Appendicular Perforation: A Prospective Study. Euroasian J Hepato-Gastroenterol 2015;5(2):87-89.

Application of indoor noise prediction in the real world

NASA Astrophysics Data System (ADS)

Lewis, David N.

2002-11-01

Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

Presenting Different Selves to Different People: Self-Presentation as a Function of Relationship Type and Contingent Self-Esteem.

PubMed

Øverup, Camilla S; Brunson, Julie A; Acitelli, Linda K

2015-01-01

Past work has established a connection between self-esteem and self-presentation; however, research has not explored how self-esteem that is contingent on one's relationship may influence self-presentational tactics in that relationship. Across two studies, undergraduate students reported on the extent to which their self-esteem depended on their friendship and romantic relationship, as well as the extent to which they engaged in self-presentation behaviors in those relationships. The results suggest that relationship-specific contingent self-esteem predicts relationship-specific self-presentation; however, friendship-contingent self-esteem predicted self-presentation in both friendships and romantic relationships. These results suggest that individuals are keenly and differentially attuned to qualitatively different relationships, and when perceiving potential problems, they attempt to remedy those through their self-presentations. Furthermore, results indicate the possibility that self-esteem tied to a particular relationship may not be as important as self-esteem based more generally on one's relationships.

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.

Older Adults' Online Dating Profiles and Successful Aging.

PubMed

Wada, Mineko; Mortenson, William Bennett; Hurd Clarke, Laura

2016-12-01

This study examined how relevant Rowe and Kahn's three criteria of successful aging were to older adults' self-portrayals in online dating profiles: low probability of disease and disability, high functioning, and active life engagement. In this cross-sectional study, 320 online dating profiles of older adults were randomly selected and coded based on the criteria. Logistic regression analyses determined whether age, gender, and race/ethnicity predicted self-presentation. Few profiles were indicative of successful aging due to the low prevalence of the first two criteria; the third criterion, however, was identified in many profiles. Native Americans were significantly less likely than other ethnic groups to highlight the first two criteria. Younger age predicted presenting the first criterion. Women's presentation of the third criterion remained significantly high with age. The findings suggest that the criteria may be unimportant to older adults when seeking partners, or they may reflect the exclusivity of this construct.

Individual differences in working memory capacity predict learned control over attentional capture.

PubMed

Robison, Matthew K; Unsworth, Nash

2017-11-01

Although individual differences in working memory capacity (WMC) typically predict susceptibility to attentional capture in various paradigms (e.g., Stroop, antisaccade, flankers), it sometimes fails to correlate with the magnitude of attentional capture effects in visual search (e.g., Stokes, 2016), which is 1 of the most frequently studied tasks to study capture (Theeuwes, 2010). But some studies have shown that search modes can mitigate the effects of attentional capture (Leber & Egeth, 2006). Therefore, the present study examined whether or not the relationship between WMC and attentional capture changes as a function of the search modes available. In Experiment 1, WMC was unrelated to attentional capture, but only 1 search mode (singleton-detection) could be employed. In Experiment 2, greater WMC predicted smaller attentional capture effects, but only when multiple search modes (feature-search and singleton-detection) could be employed. Importantly this relationship was entirely independent of variation in attention control, which suggests that this effect is driven by WMC-related long-term memory differences (Cosman & Vecera, 2013a, 2013b). The present set of findings help to further our understanding of the nuanced ways in which memory and attention interact. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Closure models for transitional blunt-body flows

NASA Astrophysics Data System (ADS)

Nance, Robert Paul

1998-12-01

A mean-flow modeling approach is proposed for the prediction of high-speed blunt-body wake flows undergoing transition to turbulence. This method couples the k- /zeta (Enstrophy) compressible turbulence model with a procedure for characterizing non-turbulent fluctuations upstream of transition. Two different instability mechanisms are examined in this study. In the first model, transition is brought about by streamwise disturbance modes, whereas the second mechanism considers instabilities in the free shear layer associated with the wake flow. An important feature of this combined approach is the ability to specify or predict the location of transition onset. Solutions obtained using the new approach are presented for a variety of perfect-gas hypersonic flows over blunt- cone configurations. These results are shown to provide better agreement with experimental heating data than earlier laminar predictions by other researchers. In addition, it is demonstrated that the free-shear-layer instability mechanism is superior to the streamwise mechanism in terms of comparisons with heating measurements. The favorable comparisons are a strong indication that transition to turbulence is indeed present in the flowfields considered. They also show that the present method is a useful predictive tool for transitional blunt-body wake flows.