Base Rates, Contingencies, and Prediction Behavior

ERIC Educational Resources Information Center

Kareev, Yaakov; Fiedler, Klaus; Avrahami, Judith

2009-01-01

A skew in the base rate of upcoming events can often provide a better cue for accurate predictions than a contingency between signals and events. The authors study prediction behavior and test people's sensitivity to both base rate and contingency; they also examine people's ability to compare the benefits of both for prediction. They formalize…

Simple Mindreading Abilities Predict Complex Theory of Mind: Developmental Delay in Autism Spectrum Disorders.

PubMed

Pino, Maria Chiara; Mazza, Monica; Mariano, Melania; Peretti, Sara; Dimitriou, Dagmara; Masedu, Francesco; Valenti, Marco; Franco, Fabia

2017-09-01

Theory of mind (ToM) is impaired in individuals with autism spectrum disorders (ASD). The aims of this study were to: (i) examine the developmental trajectories of ToM abilities in two different mentalizing tasks in children with ASD compared to TD children; and (ii) to assess if a ToM simple test known as eyes-test could predict performance on the more advanced ToM task, i.e. comic strip test. Based on a sample of 37 children with ASD and 55 TD children, our results revealed slower development at varying rates in all ToM measures in children with ASD, with delayed onset compared to TD children. These results could stimulate new treatments for social abilities, which would lessen the social deficit in ASD.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Predictability effect on N400 reflects the severity of reading comprehension deficits in aphasia.

PubMed

Chang, Chih-Ting; Lee, Chia-Ying; Chou, Chia-Ju; Fuh, Jong-Ling; Wu, Hsin-Chi

2016-01-29

Predictability effect on N400, in which low predictability words elicited a larger N400 than high predictability words did over central to posterior electrodes, has been used to index difficulty of lexical retrieval and semantic integration of words in sentence comprehension. This study examined predictability effect on N400 in aphasic patients to determine if the properties of N400 are suited to indexing the severity of reading comprehension deficits. Patients with aphasia were divided into high and low ability groups based on scores on the reading comprehension subtest in the Chinese Concise Aphasia Test (CCAT). The two aphasia groups, a group of healthy elders who were age-matched to the aphasic participants, and a group of young adults, were requested to read sentences that either ended with highly predictable words or unexpected but plausible words, while undergoing electroencephalography (EEG). The young adult and healthy elderly groups exhibited the typical centro-parietal distributed effect of predictability on N400; however, healthy elders exhibited a reduced N400 effect in a delayed time window compared to the young adults. Compared with the elderly control, the high ability aphasia group exhibited a comparable N400 effect in a more restricted time window; by contrast, the low ability aphasia group exhibited a frontal distributed N400 in a much later time window (400-700 ms). These data suggest that the severity of reading comprehension deficits affects predictability effect on a set of N400 characteristics (i.e., amplitude, time window, and topographic distribution), which may be effective as ERP signatures in the evaluation of language recovery in aphasia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Narrative discourse in adults with high-functioning autism or Asperger syndrome.

PubMed

Colle, Livia; Baron-Cohen, Simon; Wheelwright, Sally; van der Lely, Heather K J

2008-01-01

We report a study comparing the narrative abilities of 12 adults with high-functioning autism (HFA) or Asperger Syndrome (AS) versus 12 matched controls. The study focuses on the use of referential expressions (temporal expressions and anaphoric pronouns) during a story-telling task. The aim was to assess pragmatics skills in people with HFA/AS in whom linguistic impairments are more subtle than in classic autism. We predicted no significant differences in general narrative abilities between the two groups, but specific pragmatic deficits in people with AS. We predicted they use fewer personal pronouns, temporal expressions and referential expressions, which require theory of mind abilities. Results confirmed both predictions. These findings provide initial evidence of how social impairments can produce mild linguistic impairments.

A Longitudinal Field Study Comparing a Multiplicative and an Additive Model of Motivation and Ability. Technical Report No. 11.

ERIC Educational Resources Information Center

Barrett, Gerald V.; And Others

The relative contribution of motivation to ability measures in predicting performance criteria of sales personnel from successive fiscal periods was investigated. In this context, the merits of a multiplicative and additive combination of motivation and ability measures were examined. The relationship between satisfaction and motivation and…

Assessing the Performance of 3 Human Immunodeficiency Virus Incidence Risk Scores in a Cohort of Black and White Men Who Have Sex With Men in the South.

PubMed

Jones, Jeb; Hoenigl, Martin; Siegler, Aaron J; Sullivan, Patrick S; Little, Susan; Rosenberg, Eli

2017-05-01

Risk scores have been developed to identify men at high risk of human immunodeficiency virus (HIV) seroconversion. These scores can be used to more efficiently allocate public health prevention resources, such as pre-exposure prophylaxis. However, the published scores were developed with data sets that comprise predominantly white men who have sex with men (MSM) collected several years prior and recruited from a limited geographic area. Thus, it is unclear how well these scores perform in men of different races or ethnicities or men in different geographic regions. We assessed the predictive ability of 3 published scores to predict HIV seroconversion in a cohort of black and white MSM in Atlanta, GA. Questionnaire data from the baseline study visit were used to derive individual scores for each participant. We assessed the discriminatory ability of each risk score to predict HIV seroconversion over 2 years of follow-up. The predictive ability of each score was low among all MSM and lower among black men compared to white men. Each score had lower sensitivity to predict seroconversion among black MSM compared to white MSM and low area under the curve values for the receiver operating characteristic curve indicating poor discriminatory ability. Reliance on the currently available risk scores will result in misclassification of high proportions of MSM, especially black MSM, in terms of HIV risk, leading to missed opportunities for HIV prevention services.

Administering Spatial and Cognitive Instruments In-class and On-line: Are These Equivalent?

NASA Astrophysics Data System (ADS)

Williamson, Kenneth C.; Williamson, Vickie M.; Hinze, Scott R.

2017-02-01

Standardized, well-established paper-and-pencil tests, which measure spatial abilities or which measure reasoning abilities, have long been found to be predictive of success in the STEM (science, technology, engineering, and mathematics) fields. Instructors can use these tests for prediction of success and to inform instruction. A comparative administration of spatial visualization and cognitive reasoning tests, between in-class (proctored paper and pencil) and on-line (unproctored Internet) ( N = 457), was used to investigate and to determine whether the differing instrument formats yielded equal measures of spatial ability and reasoning ability in large first-semester general chemistry sections. Although some gender differences were found, findings suggest that some differences across administration formats, but that on-line administration had similar properties of predicting chemistry performance as the in-class version. Therefore, on-line administration is a viable option for instructors to consider especially when dealing with large classes.

Intrinsic motivation towards sports in Singaporean students: the role of sport ability beliefs.

PubMed

Wang, C K John; Biddle, Stuart J H

2003-09-01

This study investigated determinants of active lifestyles in Singaporean university students. Using confirmatory factor analysis, a measure of lay beliefs concerning athletic ability was confirmed. Other results confirmed hypotheses that beliefs reflecting that athletic ability can be developed over time (incremental beliefs) predict an achievement task (self-referenced) orientation, while beliefs reflecting that athletic ability is relatively stable (entity beliefs) predict an ego (other-person, comparative) orientation. Goal orientations directly affect perceived competence which, in turn, influence intrinsic motivation to be physically active. A task orientation had a direct link to intrinsic motivation. Results suggest that intrinsic motivation towards sport and physical activity might be enhanced through interventions that focus on self-referenced and self-improvement notions of ability as well as perceived competence.

Mortality Prediction Using Acute Physiology and Chronic Health Evaluation II and Acute Physiology and Chronic Health Evaluation IV Scoring Systems: Is There a Difference?

PubMed Central

Venkataraman, Ramesh; Gopichandran, Vijayaprasad; Ranganathan, Lakshmi; Rajagopal, Senthilkumar; Abraham, Babu K; Ramakrishnan, Nagarajan

2018-01-01

Background: Mortality prediction in the Intensive Care Unit (ICU) setting is complex, and there are several scoring systems utilized for this process. The Acute Physiology and Chronic Health Evaluation (APACHE) II has been the most widely used scoring system; although, the more recent APACHE IV is considered an updated and advanced prediction model. However, these two systems may not give similar mortality predictions. Objectives: The aim of this study is to compare the mortality prediction ability of APACHE II and APACHE IV scoring systems among patients admitted to a tertiary care ICU. Methods: In this prospective longitudinal observational study, APACHE II and APACHE IV scores of ICU patients were computed using an online calculator. The outcome of the ICU admissions for all the patients was collected as discharged or deceased. The data were analyzed to compare the discrimination and calibration of the mortality prediction ability of the two scores. Results: Out of the 1670 patients' data analyzed, the area under the receiver operating characteristic of APACHE II score was 0.906 (95% confidence interval [CI] – 0.890–0.992), and APACHE IV score was 0.881 (95% CI – 0.862–0.890). The mean predicted mortality rate of the study population as given by the APACHE II scoring system was 44.8 ± 26.7 and as given by APACHE IV scoring system was 29.1 ± 28.5. The observed mortality rate was 22.4%. Conclusions: The APACHE II and IV scoring systems have comparable discrimination ability, but the calibration of APACHE IV seems to be better than that of APACHE II. There is a need to recalibrate the scales with weights derived from the Indian population. PMID:29910542

Mortality Prediction Using Acute Physiology and Chronic Health Evaluation II and Acute Physiology and Chronic Health Evaluation IV Scoring Systems: Is There a Difference?

PubMed

Venkataraman, Ramesh; Gopichandran, Vijayaprasad; Ranganathan, Lakshmi; Rajagopal, Senthilkumar; Abraham, Babu K; Ramakrishnan, Nagarajan

2018-05-01

Mortality prediction in the Intensive Care Unit (ICU) setting is complex, and there are several scoring systems utilized for this process. The Acute Physiology and Chronic Health Evaluation (APACHE) II has been the most widely used scoring system; although, the more recent APACHE IV is considered an updated and advanced prediction model. However, these two systems may not give similar mortality predictions. The aim of this study is to compare the mortality prediction ability of APACHE II and APACHE IV scoring systems among patients admitted to a tertiary care ICU. In this prospective longitudinal observational study, APACHE II and APACHE IV scores of ICU patients were computed using an online calculator. The outcome of the ICU admissions for all the patients was collected as discharged or deceased. The data were analyzed to compare the discrimination and calibration of the mortality prediction ability of the two scores. Out of the 1670 patients' data analyzed, the area under the receiver operating characteristic of APACHE II score was 0.906 (95% confidence interval [CI] - 0.890-0.992), and APACHE IV score was 0.881 (95% CI - 0.862-0.890). The mean predicted mortality rate of the study population as given by the APACHE II scoring system was 44.8 ± 26.7 and as given by APACHE IV scoring system was 29.1 ± 28.5. The observed mortality rate was 22.4%. The APACHE II and IV scoring systems have comparable discrimination ability, but the calibration of APACHE IV seems to be better than that of APACHE II. There is a need to recalibrate the scales with weights derived from the Indian population.

Executive function predicts artificial language learning

PubMed Central

Kapa, Leah L.; Colombo, John

2017-01-01

Previous research suggests executive function (EF) advantages among bilinguals compared to monolingual peers, and these advantages are generally attributed to experience controlling two linguistic systems. However, the possibility that the relationship between bilingualism and EF might be bidirectional has not been widely considered; while experience with two languages might improve EF, better EF skills might also facilitate language learning. In the current studies, we tested whether adults’ and preschool children’s EF abilities predicted success in learning a novel artificial language. After controlling for working memory and English receptive vocabulary, adults’ artificial language performance was predicted by their inhibitory control ability (Study 1) and children’s performance was predicted by their attentional monitoring and shifting ability (Study 2). These findings provide preliminary evidence suggesting that EF processes may be employed during initial stages of language learning, particularly vocabulary acquisition, and support the possibility of a bidirectional relationship between EF and language acquisition. PMID:29129958

Genomic prediction in a nuclear population of layers using single-step models.

PubMed

Yan, Yiyuan; Wu, Guiqin; Liu, Aiqiao; Sun, Congjiao; Han, Wenpeng; Li, Guangqi; Yang, Ning

2018-02-01

Single-step genomic prediction method has been proposed to improve the accuracy of genomic prediction by incorporating information of both genotyped and ungenotyped animals. The objective of this study is to compare the prediction performance of single-step model with a 2-step models and the pedigree-based models in a nuclear population of layers. A total of 1,344 chickens across 4 generations were genotyped by a 600 K SNP chip. Four traits were analyzed, i.e., body weight at 28 wk (BW28), egg weight at 28 wk (EW28), laying rate at 38 wk (LR38), and Haugh unit at 36 wk (HU36). In predicting offsprings, individuals from generation 1 to 3 were used as training data and females from generation 4 were used as validation set. The accuracies of predicted breeding values by pedigree BLUP (PBLUP), genomic BLUP (GBLUP), SSGBLUP and single-step blending (SSBlending) were compared for both genotyped and ungenotyped individuals. For genotyped females, GBLUP performed no better than PBLUP because of the small size of training data, while the 2 single-step models predicted more accurately than the PBLUP model. The average predictive ability of SSGBLUP and SSBlending were 16.0% and 10.8% higher than the PBLUP model across traits, respectively. Furthermore, the predictive abilities for ungenotyped individuals were also enhanced. The average improvements of prediction abilities were 5.9% and 1.5% for SSGBLUP and SSBlending model, respectively. It was concluded that single-step models, especially the SSGBLUP model, can yield more accurate prediction of genetic merits and are preferable for practical implementation of genomic selection in layers. © 2017 Poultry Science Association Inc.

A Formula to Calculate Standard Liver Volume Using Thoracoabdominal Circumference.

PubMed

Shaw, Brian I; Burdine, Lyle J; Braun, Hillary J; Ascher, Nancy L; Roberts, John P

2017-12-01

With the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates. LDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression. The optimal formula using TAC was determined to be SLV = (TAC × 3.5816) - (Age × 3.9844) - (Sex × 109.7386) - 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025). We report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts.

Predicting risk of trace element pollution from municipal roads using site-specific soil samples and remotely sensed data.

PubMed

Reeves, Mari Kathryn; Perdue, Margaret; Munk, Lee Ann; Hagedorn, Birgit

2018-07-15

Studies of environmental processes exhibit spatial variation within data sets. The ability to derive predictions of risk from field data is a critical path forward in understanding the data and applying the information to land and resource management. Thanks to recent advances in predictive modeling, open source software, and computing, the power to do this is within grasp. This article provides an example of how we predicted relative trace element pollution risk from roads across a region by combining site specific trace element data in soils with regional land cover and planning information in a predictive model framework. In the Kenai Peninsula of Alaska, we sampled 36 sites (191 soil samples) adjacent to roads for trace elements. We then combined this site specific data with freely-available land cover and urban planning data to derive a predictive model of landscape scale environmental risk. We used six different model algorithms to analyze the dataset, comparing these in terms of their predictive abilities and the variables identified as important. Based on comparable predictive abilities (mean R 2 from 30 to 35% and mean root mean square error from 65 to 68%), we averaged all six model outputs to predict relative levels of trace element deposition in soils-given the road surface, traffic volume, sample distance from the road, land cover category, and impervious surface percentage. Mapped predictions of environmental risk from toxic trace element pollution can show land managers and transportation planners where to prioritize road renewal or maintenance by each road segment's relative environmental and human health risk. Published by Elsevier B.V.

The "ick" Factor Matters: Disgust Prospectively Predicts Avoidance in Chemotherapy Patients.

PubMed

Reynolds, Lisa M; Bissett, Ian P; Porter, David; Consedine, Nathan S

2016-12-01

Chemotherapy can be physically and psychologically demanding. Avoidance and withdrawal are common among patients coping with these demands. This report compares established emotional predictors of avoidance during chemotherapy (embarrassment; distress) with an emotion (disgust) that has been unstudied in this context. This report outlines secondary analyses of an RCT where 68 cancer patients undergoing chemotherapy were randomized to mindfulness or relaxation interventions. Self-reported baseline disgust (DS-R), embarrassment (SES-SF), and distress (Distress Thermometer) were used to prospectively predict multiple classes of avoidance post-intervention and at 3 months follow-up. Measures assessed social avoidance, cognitive and emotional avoidance (IES Avoidance), as well as information seeking and treatment adherence (General Adherence Scale). Repeated-measures ANOVAs evaluated possible longitudinal changes in disgust and forward entry regression models contrasted the ability of the affective variables to predict avoidance. Although disgust did not change over time or vary between groups, greater disgust predicted greater social, cognitive, and emotional avoidance, as well as greater information seeking. Social avoidance was predicted by trait embarrassment and distress predicted non-adherence. This report represents the first investigation of disgust's ability to prospectively predict avoidance in people undergoing chemotherapy. Compared to embarrassment and distress, disgust was a more consistent predictor across avoidance domains and its predictive ability was evident across a longer period of time. Findings highlight disgust's role as an indicator of likely avoidance in this health context. Early identification of cancer patients at risk of deleterious avoidance may enable timely interventions and has important clinical implications (ACTRN12613000238774).

Discriminative ability of commonly used indices to predict adverse outcomes after poster lumbar fusion: a comparison of demographics, ASA, the modified Charlson Comorbidity Index, and the modified Frailty Index.

PubMed

Ondeck, Nathaniel T; Bohl, Daniel D; Bovonratwet, Patawut; McLynn, Ryan P; Cui, Jonathan J; Shultz, Blake N; Lukasiewicz, Adam M; Grauer, Jonathan N

2018-01-01

As research tools, the American Society of Anesthesiologists (ASA) physical status classification system, the modified Charlson Comorbidity Index (mCCI), and the modified Frailty Index (mFI) have been associated with complications following spine procedures. However, with respect to clinical use for various adverse outcomes, no known study has compared the predictive performance of these indices specifically following posterior lumbar fusion (PLF). This study aimed to compare the discriminative ability of ASA, mCCI, and mFI, as well as demographic factors including age, body mass index, and gender for perioperative adverse outcomes following PLF. A retrospective review of prospectively collected data was performed. Patients undergoing elective PLF with or without interbody fusion were extracted from the 2011-2014 American College of Surgeons National Surgical Quality Improvement Program (NSQIP). Perioperative adverse outcome variables assessed included the occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, and discharge to higher-level care. Patient comorbidity indices and characteristics were delineated and assessed for discriminative ability in predicting perioperative adverse outcomes using an area under the curve analysis from the receiver operating characteristics curves. In total, 16,495 patients were identified who met the inclusion criteria. The most predictive comorbidity index was ASA and demographic factor was age. Of these two factors, age had the larger discriminative ability for three out of the six adverse outcomes and ASA was the most predictive for one out of six adverse outcomes. A combination of the most predictive demographic factor and comorbidity index resulted in improvements in discriminative ability over the individual components for five of the six outcome variables. For PLF, easily obtained patient ASA and age have overall similar or better discriminative abilities for perioperative adverse outcomes than numerically tabulated indices that have multiple inputs and are harder to implement in clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

DOE PAGES

Preciat Gonzalez, German A.; El Assal, Lemmer R. P.; Noronha, Alberto; ...

2017-06-14

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, manymore » algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.« less

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

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

Preciat Gonzalez, German A.; El Assal, Lemmer R. P.; Noronha, Alberto

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, manymore » algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.« less

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D.

PubMed

Preciat Gonzalez, German A; El Assal, Lemmer R P; Noronha, Alberto; Thiele, Ines; Haraldsdóttir, Hulda S; Fleming, Ronan M T

2017-06-14

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.

External validation of Vascular Study Group of New England risk predictive model of mortality after elective abdominal aorta aneurysm repair in the Vascular Quality Initiative and comparison against established models.

PubMed

Eslami, Mohammad H; Rybin, Denis V; Doros, Gheorghe; Siracuse, Jeffrey J; Farber, Alik

2018-01-01

The purpose of this study is to externally validate a recently reported Vascular Study Group of New England (VSGNE) risk predictive model of postoperative mortality after elective abdominal aortic aneurysm (AAA) repair and to compare its predictive ability across different patients' risk categories and against the established risk predictive models using the Vascular Quality Initiative (VQI) AAA sample. The VQI AAA database (2010-2015) was queried for patients who underwent elective AAA repair. The VSGNE cases were excluded from the VQI sample. The external validation of a recently published VSGNE AAA risk predictive model, which includes only preoperative variables (age, gender, history of coronary artery disease, chronic obstructive pulmonary disease, cerebrovascular disease, creatinine levels, and aneurysm size) and planned type of repair, was performed using the VQI elective AAA repair sample. The predictive value of the model was assessed via the C-statistic. Hosmer-Lemeshow method was used to assess calibration and goodness of fit. This model was then compared with the Medicare, Vascular Governance Northwest model, and Glasgow Aneurysm Score for predicting mortality in VQI sample. The Vuong test was performed to compare the model fit between the models. Model discrimination was assessed in different risk group VQI quintiles. Data from 4431 cases from the VSGNE sample with the overall mortality rate of 1.4% was used to develop the model. The internally validated VSGNE model showed a very high discriminating ability in predicting mortality (C = 0.822) and good model fit (Hosmer-Lemeshow P = .309) among the VSGNE elective AAA repair sample. External validation on 16,989 VQI cases with an overall 0.9% mortality rate showed very robust predictive ability of mortality (C = 0.802). Vuong tests yielded a significant fit difference favoring the VSGNE over then Medicare model (C = 0.780), Vascular Governance Northwest (0.774), and Glasgow Aneurysm Score (0.639). Across the 5 risk quintiles, the VSGNE model predicted observed mortality significantly with great accuracy. This simple VSGNE AAA risk predictive model showed very high discriminative ability in predicting mortality after elective AAA repair among a large external independent sample of AAA cases performed by a diverse array of physicians nationwide. The risk score based on this simple VSGNE model can reliably stratify patients according to their risk of mortality after elective AAA repair better than other established models. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Genomic Selection in Multi-environment Crop Trials.

PubMed

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Auditory brainstem response to complex sounds predicts self-reported speech-in-noise performance.

PubMed

Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

2013-02-01

To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) and pure-tone hearing thresholds. Participants included 111 middle- to older-age adults (range = 45-78) with audiometric configurations ranging from normal hearing levels to moderate sensorineural hearing loss. In addition to using audiometric testing, the authors also used such evaluation measures as the QuickSIN, the SSQ, and the cABR. Multiple linear regression analysis indicated that the inclusion of brainstem variables in a model with QuickSIN, hearing thresholds, and age accounted for 30% of the variance in the Speech subtest of the SSQ, compared with significantly less variance (19%) when brainstem variables were not included. The authors' results demonstrate the cABR's efficacy for predicting self-reported speech-in-noise perception difficulties. The fact that the cABR predicts more variance in self-reported speech-in-noise (SIN) perception than either the QuickSIN or hearing thresholds indicates that the cABR provides additional insight into an individual's ability to hear in background noise. In addition, the findings underscore the link between the cABR and hearing in noise.

Assessment of gross motor skills of at-risk infants: predictive validity of the Alberta Infant Motor Scale.

PubMed

Darrah, J; Piper, M; Watt, M J

1998-07-01

The Alberta Infant Motor Scale (AIMS) is a norm-referenced measure of infant gross motor development. The objectives of this study were: (1) to establish the best cut-off scores on the AIMS for predictive purposes, and (2) to compare the predictive abilities of the AIMS with those of the Movement Assessment of Infants (MAI) and the Peabody Developmental Gross Motor Scale (PDGMS). One hundred and sixty-four infants were assessed at 4 and 8 months adjusted ages on the three measures. A pediatrician assessed each infant's gross motor development at 18 months as normal, suspicious, or abnormal. For the AIMS, two different cut-off points were identified: the 10th centile at 4 months and the 5th centile at 8 months. The MAI provided the best specificity rates at 4 months while the AIMS was superior in specificity at 8 months. Sensitivity rates were comparable between the two tests. The PDGMS in general demonstrated poor predictive abilities.

Limited predictive ability of surrogate indices of insulin sensitivity/resistance in Asian-Indian men.

PubMed

Muniyappa, Ranganath; Irving, Brian A; Unni, Uma S; Briggs, William M; Nair, K Sreekumaran; Quon, Michael J; Kurpad, Anura V

2010-12-01

Insulin resistance is highly prevalent in Asian Indians and contributes to worldwide public health problems, including diabetes and related disorders. Surrogate measurements of insulin sensitivity/resistance are used frequently to study Asian Indians, but these are not formally validated in this population. In this study, we compared the ability of simple surrogate indices to accurately predict insulin sensitivity as determined by the reference glucose clamp method. In this cross-sectional study of Asian-Indian men (n = 70), we used a calibration model to assess the ability of simple surrogate indices for insulin sensitivity [quantitative insulin sensitivity check index (QUICKI), homeostasis model assessment (HOMA2-IR), fasting insulin-to-glucose ratio (FIGR), and fasting insulin (FI)] to predict an insulin sensitivity index derived from the reference glucose clamp method (SI(Clamp)). Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction as well as leave-one-out cross-validation-type RMSE of prediction (CVPE). QUICKI, FIGR, and FI, but not HOMA2-IR, had modest linear correlations with SI(Clamp) (QUICKI: r = 0.36; FIGR: r = -0.36; FI: r = -0.27; P < 0.05). No significant differences were noted among CVPE or RMSE from any of the surrogate indices when compared with QUICKI. Surrogate measurements of insulin sensitivity/resistance such as QUICKI, FIGR, and FI are easily obtainable in large clinical studies, but these may only be useful as secondary outcome measurements in assessing insulin sensitivity/resistance in clinical studies of Asian Indians.

Narrative Ability of Children With Speech Sound Disorders and the Prediction of Later Literacy Skills

PubMed Central

Wellman, Rachel L.; Lewis, Barbara A.; Freebairn, Lisa A.; Avrich, Allison A.; Hansen, Amy J.; Stein, Catherine M.

2012-01-01

Purpose The main purpose of this study was to examine how children with isolated speech sound disorders (SSDs; n = 20), children with combined SSDs and language impairment (LI; n = 20), and typically developing children (n = 20), ages 3;3 (years;months) to 6;6, differ in narrative ability. The second purpose was to determine if early narrative ability predicts school-age (8–12 years) literacy skills. Method This study employed a longitudinal cohort design. The children completed a narrative retelling task before their formal literacy instruction began. The narratives were analyzed and compared for group differences. Performance on these early narratives was then used to predict the children’s reading decoding, reading comprehension, and written language ability at school age. Results Significant group differences were found in children’s (a) ability to answer questions about the story, (b) use of story grammars, and (c) number of correct and irrelevant utterances. Regression analysis demonstrated that measures of story structure and accuracy were the best predictors of the decoding of real words, reading comprehension, and written language. Measures of syntax and lexical diversity were the best predictors of the decoding of nonsense words. Conclusion Combined SSDs and LI, and not isolated SSDs, impact a child’s narrative abilities. Narrative retelling is a useful task for predicting which children may be at risk for later literacy problems. PMID:21969531

Measuring ability to enhance and suppress emotional expression: The Flexible Regulation of Emotional Expression (FREE) Scale.

PubMed

Burton, Charles L; Bonanno, George A

2016-08-01

Flexibility in self-regulatory behaviors has proved to be an important quality for adjusting to stressful life events and requires individuals to have a diverse repertoire of emotion regulation abilities. However, the most commonly used emotion regulation questionnaires assess frequency of behavior rather than ability, with little evidence linking these measures to observable capacity to enact a behavior. The aim of the current investigation was to develop and validate a Flexible Regulation of Emotional Expression (FREE) Scale that measures a person's ability to enhance and suppress displayed emotion across an array of hypothetical contexts. In Studies 1 and 2, a series of confirmatory factor analyses revealed that the FREE Scale consists of 4 first-order factors divided by regulation and emotional valence type that can contribute to 2 higher order factors: expressive enhancement ability and suppression ability. In Study 1, we also compared the FREE Scale to other commonly used emotion regulation measures, which revealed that suppression ability is conceptually distinct from suppression frequency. In Study 3, we compared the FREE Scale with a composite of traditional frequency-based indices of expressive regulation to predict performance in a previously validated emotional modulation paradigm. Participants' enhancement and suppression ability scores on the FREE Scale predicted their corresponding performance on the laboratory task, even when controlling for baseline expressiveness. These studies suggest that the FREE Scale is a valid and flexible measure of expressive regulation ability. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The proposed 'concordance-statistic for benefit' provided a useful metric when modeling heterogeneous treatment effects.

PubMed

van Klaveren, David; Steyerberg, Ewout W; Serruys, Patrick W; Kent, David M

2018-02-01

Clinical prediction models that support treatment decisions are usually evaluated for their ability to predict the risk of an outcome rather than treatment benefit-the difference between outcome risk with vs. without therapy. We aimed to define performance metrics for a model's ability to predict treatment benefit. We analyzed data of the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) trial and of three recombinant tissue plasminogen activator trials. We assessed alternative prediction models with a conventional risk concordance-statistic (c-statistic) and a novel c-statistic for benefit. We defined observed treatment benefit by the outcomes in pairs of patients matched on predicted benefit but discordant for treatment assignment. The 'c-for-benefit' represents the probability that from two randomly chosen matched patient pairs with unequal observed benefit, the pair with greater observed benefit also has a higher predicted benefit. Compared to a model without treatment interactions, the SYNTAX score II had improved ability to discriminate treatment benefit (c-for-benefit 0.590 vs. 0.552), despite having similar risk discrimination (c-statistic 0.725 vs. 0.719). However, for the simplified stroke-thrombolytic predictive instrument (TPI) vs. the original stroke-TPI, the c-for-benefit (0.584 vs. 0.578) was similar. The proposed methodology has the potential to measure a model's ability to predict treatment benefit not captured with conventional performance metrics. Copyright © 2017 Elsevier Inc. All rights reserved.

Self-assessment of social cognitive ability in schizophrenia: Association with social cognitive test performance, informant assessments of social cognitive ability, and everyday outcomes.

PubMed

Silberstein, Juliet M; Pinkham, Amy E; Penn, David L; Harvey, Philip D

2018-04-17

Impairments in self-assessment are common in people with schizophrenia and impairments in self-assessment of cognitive ability have been found to predict impaired functional outcome. In this study, we examined self-assessment of social cognitive ability and related them to assessments of social cognition provided by informants, to performance on tests of social cognition, and to everyday outcomes. The difference between self-reported social cognition and informant ratings was used to predict everyday functioning. People with schizophrenia (n=135) performed 8 different tests of social cognition. They were asked to rate their social cognitive abilities on the Observable Social Cognition Rating Scale (OSCARs). High contact informants also rated social cognitive ability and everyday outcomes, while unaware of the patients' social cognitive performance and self-assessments. Social competence was measured with a performance-based assessment and clinical ratings of negative symptoms were also performed. Patient reports of their social cognitive abilities were uncorrelated with performance on social cognitive tests and with three of the four domains of functional outcomes. Differences between self-reported and informant rated social cognitive ability predicted impaired everyday functioning across all four functional domains. This difference score predicted disability even when the influences of social cognitive performance, social competence, and negative symptoms were considered. Mis-estimation of social cognitive ability was an important predictor of social and nonsocial outcomes in schizophrenia compared to performance on social cognitive tests. These results suggest that consideration of self-assessment is critical when attempting to evaluate the causes of disability and when trying to implement interventions targeting disability reduction. Copyright © 2018 Elsevier B.V. All rights reserved.

A Demand-Driven Approach for a Multi-Agent System in Supply Chain Management

NASA Astrophysics Data System (ADS)

Kovalchuk, Yevgeniya; Fasli, Maria

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit.

Detailed characteristics of drop-laden mixing layers: LES predictions compared to DNS

NASA Technical Reports Server (NTRS)

Okong'o, N.; Leboissetier, A.; Bellan, J.

2004-01-01

Results have been compared from Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) of a temporal mixing layer laden with evaporating drops, to assess the ability of LES to reproduce detailed characteristics of DNS.

Predictive rhythmic tapping to isochronous and tempo changing metronomes in the nonhuman primate.

PubMed

Gámez, Jorge; Yc, Karyna; Ayala, Yaneri A; Dotov, Dobromir; Prado, Luis; Merchant, Hugo

2018-04-30

Beat entrainment is the ability to entrain one's movements to a perceived periodic stimulus, such as a metronome or a pulse in music. Humans have a capacity to predictively respond to a periodic pulse and to dynamically adjust their movement timing to match the varying music tempos. Previous studies have shown that monkeys share some of the human capabilities for rhythmic entrainment, such as tapping regularly at the period of isochronous stimuli. However, it is still unknown whether monkeys can predictively entrain to dynamic tempo changes like humans. To address this question, we trained monkeys in three tapping tasks and compared their rhythmic entrainment abilities with those of humans. We found that, when immediate feedback about the timing of each movement is provided, monkeys can predictively entrain to an isochronous beat, generating tapping movements in anticipation of the metronome pulse. This ability also generalized to a novel untrained tempo. Notably, macaques can modify their tapping tempo by predicting the beat changes of accelerating and decelerating visual metronomes in a manner similar to humans. Our findings support the notion that nonhuman primates share with humans the ability of temporal anticipation during tapping to isochronous and smoothly changing sequences of stimuli. © 2018 New York Academy of Sciences.

Prospective comparison of three predictive rules for assessing severity of community‐acquired pneumonia in Hong Kong

PubMed Central

Man, Shin Yan; Lee, Nelson; Ip, Margaret; Antonio, Gregory E; Chau, Shirley SL; Mak, Paulina; Graham, Colin A; Zhang, Mingdong; Lui, Grace; Chan, Paul K S; Ahuja, Anil T; Hui, David S; Sung, Joseph J Y; Rainer, Timothy H

2007-01-01

Background Community‐acquired pneumonia (CAP) is a leading infectious cause of death throughout the world, including Hong Kong. Aim To compare the ability of three validated prediction rules for CAP to predict mortality in Hong Kong: the 20 variable Pneumonia Severity Index (PSI), the 6‐point CURB65 scale adopted by the British Thoracic Society and the simpler CRB65. Methods A prospective observational study of 1016 consecutive inpatients with CAP (583 men, mean (SD) age 72 (17) years) was performed in a university hospital in the New Territories of Hong Kong in 2004. The patients were classified into three risk groups (low, intermediate and high) according to each rule. The ability of the three rules to predict 30 day mortality was compared. Results The overall mortality and intensive care unit (ICU) admission rates were 8.6% and 4.0%, respectively. PSI, CURB65 and CRB65 performed similarly, and the areas under the receiver operating characteristic (ROC) curve were 0.736 (95% CI 0.687 to 0.736), 0.733 (95% CI 0.679 to 0.787) and 0.694 (95% CI 0.634 to 0.753), respectively. All three rules had high negative predictive values but relatively low positive predictive values at all cut‐off points. Larger proportions of patients were identified as low risk by PSI (47.2%) and CURB65 (43.3%) than by CRB65 (12.6%). Conclusion All three predictive rules have a similar performance in predicting the severity of CAP, but CURB65 is more suitable than the other two for use in the emergency department because of its simplicity of application and ability to identify low‐risk patients. PMID:17121867

Changes in Predictive Task Switching with Age and with Cognitive Load.

PubMed

Levy-Tzedek, Shelly

2017-01-01

Predictive control of movement is more efficient than feedback-based control, and is an important skill in everyday life. We tested whether the ability to predictively control movements of the upper arm is affected by age and by cognitive load. A total of 63 participants were tested in two experiments. In both experiments participants were seated, and controlled a cursor on a computer screen by flexing and extending their dominant arm. In Experiment 1, 20 young adults and 20 older adults were asked to continuously change the frequency of their horizontal arm movements, with the goal of inducing an abrupt switch between discrete movements (at low frequencies) and rhythmic movements (at high frequencies). We tested whether that change was performed based on a feed-forward (predictive) or on a feedback (reactive) control. In Experiment 2, 23 young adults performed the same task, while being exposed to a cognitive load half of the time via a serial subtraction task. We found that both aging and cognitive load diminished, on average, the ability of participants to predictively control their movements. Five older adults and one young adult under a cognitive load were not able to perform the switch between rhythmic and discrete movement (or vice versa). In Experiment 1, 40% of the older participants were able to predictively control their movements, compared with 70% in the young group. In Experiment 2, 48% of the participants were able to predictively control their movements with a cognitively loading task, compared with 70% in the no-load condition. The ability to predictively change a motor plan in anticipation of upcoming changes may be an important component in performing everyday functions, such as safe driving and avoiding falls.

A comparative analysis of primary and secondary Gleason pattern predictive ability for positive surgical margins after radical prostatectomy.

PubMed

Sfoungaristos, S; Kavouras, A; Kanatas, P; Polimeros, N; Perimenis, P

2011-01-01

To compare the predictive ability of primary and secondary Gleason pattern for positive surgical margins in patients with clinically localized prostate cancer and a preoperative Gleason score ≤ 6. A retrospective analysis of the medical records of patients undergone a radical prostatectomy between January 2005 and October 2010 was conducted. Patients' age, prostate volume, preoperative PSA, biopsy Gleason score, the 1st and 2nd Gleason pattern were entered a univariate and multivariate analysis. The 1st and 2nd pattern were tested for their ability to predict positive surgical margins using receiver operating characteristic curves. Positive surgical margins were noticed in 56 cases (38.1%) out of 147 studied patients. The 2nd pattern was significantly greater in those with positive surgical margins while the 1st pattern was not significantly different between the 2 groups of patients. ROC analysis revealed that area under the curve was 0.53 (p=0.538) for the 1st pattern and 0.60 (p=0.048) for the 2nd pattern. Concerning the cases with PSA <10 ng/ml, it was also found that only the 2nd pattern had a predictive ability (p=0.050). When multiple logistic regression analysis was conducted it was found that the 2nd pattern was the only independent predictor. The second Gleason pattern was found to be of higher value than the 1st one for the prediction of positive surgical margins in patients with preoperative Gleason score ≤ 6 and this should be considered especially when a neurovascular bundle sparing radical prostatectomy is planned, in order not to harm the oncological outcome.

Learning temporal statistics for sensory predictions in mild cognitive impairment.

PubMed

Di Bernardi Luft, Caroline; Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-08-01

Training is known to improve performance in a variety of perceptual and cognitive skills. However, there is accumulating evidence that mere exposure (i.e. without supervised training) to regularities (i.e. patterns that co-occur in the environment) facilitates our ability to learn contingencies that allow us to interpret the current scene and make predictions about future events. Recent neuroimaging studies have implicated fronto-striatal and medial temporal lobe brain regions in the learning of spatial and temporal statistics. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are characterized by hippocampal dysfunction are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards orientated gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. However, our fMRI results demonstrate that MCI-AD patients recruit an alternate circuit to hippocampus to succeed in learning of predictive structures. In particular, we observed stronger learning-dependent activations for structured sequences in frontal, subcortical and cerebellar regions for patients compared to age-matched controls. Thus, our findings suggest a cortico-striatal-cerebellar network that may mediate the ability for predictive learning despite hippocampal dysfunction in MCI-AD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deviation from expected cognitive ability across psychotic disorders.

PubMed

Hochberger, W C; Combs, T; Reilly, J L; Bishop, J R; Keefe, R S E; Clementz, B A; Keshavan, M S; Pearlson, G D; Tamminga, C A; Hill, S K; Sweeney, J A

2018-02-01

Patients with schizophrenia show a deficit in cognitive ability compared to estimated premorbid and familial intellectual abilities. However, the degree to which this pattern holds across psychotic disorders and is familial is unclear. The present study examined deviation from expected cognitive level in schizophrenia, schizoaffective disorder, and psychotic bipolar disorder probands and their first-degree relatives. Using a norm-based regression approach, parental education and WRAT-IV Reading scores (both significant predictors of cognitive level in the healthy control group) were used to predict global neuropsychological function as measured by the composite score from the Brief Assessment of Cognition in Schizophrenia (BACS) test in probands and relatives. When compared to healthy control group, psychotic probands showed a significant gap between observed and predicted BACS composite scores and a greater likelihood of robust cognitive decline. This effect was not seen in unaffected relatives. While BACS and WRAT-IV Reading scores were themselves highly familial, the decline in cognitive function from expectation had lower estimates of familiality. Thus, illness-related factors such as epigenetic, treatment, or pathophysiological factors may be important causes of illness related decline in cognitive abilities across psychotic disorders. This is consistent with the markedly greater level of cognitive impairment seen in affected individuals compared to their unaffected family members. Copyright © 2017 Elsevier B.V. All rights reserved.

Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.

PubMed

Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah

2018-05-09

Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.

Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study

USGS Publications Warehouse

Douglas, Steven; Dixon, Barnali; Griffin, Dale W.

2018-01-01

With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class.

Neurocognitive Predictors of Academic Outcomes among Childhood Leukemia Survivors

PubMed Central

(Ki) Moore, Ida M.; Lupo, Philip J.; Insel, Kathleen; Harris, Lynnette L.; Pasvogel, Alice; Koerner, Kari M.; Adkins, Kristin B.; Taylor, Olga A.; Hockenberry, Marilyn J.

2015-01-01

Background Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and survival approaches 90%. ALL survivors are more likely than healthy peers or siblings to experience academic underachievement yet little is known about neurocognitive predictors of academic outcomes. Objective Objectives were to compare neurocognitive abilities to age-adjusted standardized norms; to examine change over time in neurocognitive abilities; and to establish neurocognitive predictors of academic outcomes. Methods Seventy-one children were followed over the course of therapy. Cognitive abilities were assessed during Induction when the child was in remission (Baseline) and annually for 3 years (Year 1, Year 2, Year 3). Reading and mathematics abilities were assessed at Year 3. Results Fine motor dexterity was significantly below age-adjusted norms at all data points, but showed improvement over time. Baseline visual-motor integration was within the normal range but significantly declined by Year 3, and mean scores at Years 2 and 3 were significantly below age-adjusted norms. Verbal short-term memory was significantly below age-adjusted norms at all assessments. Visual-motor integration predicted reading and mathematic abilities. Verbal short-term memory predicted reading abilities, and visual short-term memory predicted mathematic abilities. Conclusions CNS-directed therapy is associated with specific neurocognitive problems. Visual spatial skills, verbal and visual short term memory predict academic outcomes. Implications for practice Early assessment of visual spatial perception and short-term memory can identify children at risk for academic problems. Children who are at risk for academic problems could benefit from a school based Individual Educational Program and/or educational intervention. PMID:26166361

Cognitive skills and bacterial load: comparative evidence of costs of cognitive proficiency in birds

NASA Astrophysics Data System (ADS)

Soler, Juan José; Peralta-Sánchez, Juan Manuel; Martín-Vivaldi, Manuel; Martín-Platero, Antonio Manuel; Flensted-Jensen, Einar; Møller, Anders Pape

2012-02-01

Parasite-mediated selection may affect the evolution of cognitive abilities because parasites may influence development of the brain, but also learning capacity. Here, we tested some predictions of this hypothesis by analyzing the relationship between complex behaviours (feeding innovations (as a measure of behavioural flexibility) and ability to detect foreign eggs in their nests (i.e. a measure of discriminatory ability)) and abundance of microorganisms in different species of birds. A positive relationship would be predicted if these cognitive abilities implied a larger number of visited environments, while if these skills favoured detection and avoidance of risky environments, a negative relationship would be the prediction. Bacterial loads of eggshells, estimated for mesophilic and potentially pathogenic bacteria (i.e. Enterococcus, Staphylococcus and Enterobacteriaceae), were used as a surrogate of probability of contact with pathogenic bacteria. We found that bird species with higher feeding innovation rates and rejection rates of experimental brood parasitic eggs had higher density of bacteria on their eggshells than the average species. Since the analysed groups of microorganisms include pathogenic bacteria, these results suggest that both feeding innovation and ability to recognize foreign eggs are costly and highlight the importance of parasite-mediated selection in explaining the evolution of cognitive abilities in animals.

Development of a Clinical Forecasting Model to Predict Comorbid Depression Among Diabetes Patients and an Application in Depression Screening Policy Making.

PubMed

Jin, Haomiao; Wu, Shinyi; Di Capua, Paul

2015-09-03

Depression is a common but often undiagnosed comorbid condition of people with diabetes. Mass screening can detect undiagnosed depression but may require significant resources and time. The objectives of this study were 1) to develop a clinical forecasting model that predicts comorbid depression among patients with diabetes and 2) to evaluate a model-based screening policy that saves resources and time by screening only patients considered as depressed by the clinical forecasting model. We trained and validated 4 machine learning models by using data from 2 safety-net clinical trials; we chose the one with the best overall predictive ability as the ultimate model. We compared model-based policy with alternative policies, including mass screening and partial screening, on the basis of depression history or diabetes severity. Logistic regression had the best overall predictive ability of the 4 models evaluated and was chosen as the ultimate forecasting model. Compared with mass screening, the model-based policy can save approximately 50% to 60% of provider resources and time but will miss identifying about 30% of patients with depression. Partial-screening policy based on depression history alone found only a low rate of depression. Two other heuristic-based partial screening policies identified depression at rates similar to those of the model-based policy but cost more in resources and time. The depression prediction model developed in this study has compelling predictive ability. By adopting the model-based depression screening policy, health care providers can use their resources and time better and increase their efficiency in managing their patients with depression.

Improvement of Predictive Ability by Uniform Coverage of the Target Genetic Space

PubMed Central

Bustos-Korts, Daniela; Malosetti, Marcos; Chapman, Scott; Biddulph, Ben; van Eeuwijk, Fred

2016-01-01

Genome-enabled prediction provides breeders with the means to increase the number of genotypes that can be evaluated for selection. One of the major challenges in genome-enabled prediction is how to construct a training set of genotypes from a calibration set that represents the target population of genotypes, where the calibration set is composed of a training and validation set. A random sampling protocol of genotypes from the calibration set will lead to low quality coverage of the total genetic space by the training set when the calibration set contains population structure. As a consequence, predictive ability will be affected negatively, because some parts of the genotypic diversity in the target population will be under-represented in the training set, whereas other parts will be over-represented. Therefore, we propose a training set construction method that uniformly samples the genetic space spanned by the target population of genotypes, thereby increasing predictive ability. To evaluate our method, we constructed training sets alongside with the identification of corresponding genomic prediction models for four genotype panels that differed in the amount of population structure they contained (maize Flint, maize Dent, wheat, and rice). Training sets were constructed using uniform sampling, stratified-uniform sampling, stratified sampling and random sampling. We compared these methods with a method that maximizes the generalized coefficient of determination (CD). Several training set sizes were considered. We investigated four genomic prediction models: multi-locus QTL models, GBLUP models, combinations of QTL and GBLUPs, and Reproducing Kernel Hilbert Space (RKHS) models. For the maize and wheat panels, construction of the training set under uniform sampling led to a larger predictive ability than under stratified and random sampling. The results of our methods were similar to those of the CD method. For the rice panel, all training set construction methods led to similar predictive ability, a reflection of the very strong population structure in this panel. PMID:27672112

In silico prediction of pharmaceutical degradation pathways: a benchmarking study.

PubMed

Kleinman, Mark H; Baertschi, Steven W; Alsante, Karen M; Reid, Darren L; Mowery, Mark D; Shimanovich, Roman; Foti, Chris; Smith, William K; Reynolds, Dan W; Nefliu, Marcela; Ott, Martin A

2014-11-03

Zeneth is a new software application capable of predicting degradation products derived from small molecule active pharmaceutical ingredients. This study was aimed at understanding the current status of Zeneth's predictive capabilities and assessing gaps in predictivity. Using data from 27 small molecule drug substances from five pharmaceutical companies, the evolution of Zeneth predictions through knowledge base development since 2009 was evaluated. The experimentally observed degradation products from forced degradation, accelerated, and long-term stability studies were compared to Zeneth predictions. Steady progress in predictive performance was observed as the knowledge bases grew and were refined. Over the course of the development covered within this evaluation, the ability of Zeneth to predict experimentally observed degradants increased from 31% to 54%. In particular, gaps in predictivity were noted in the areas of epimerizations, N-dealkylation of N-alkylheteroaromatic compounds, photochemical decarboxylations, and electrocyclic reactions. The results of this study show that knowledge base development efforts have increased the ability of Zeneth to predict relevant degradation products and aid pharmaceutical research. This study has also provided valuable information to help guide further improvements to Zeneth and its knowledge base.

Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.

PubMed

Cuthbertson, Carmen C; Kucharska-Newton, Anna; Faurot, Keturah R; Stürmer, Til; Jonsson Funk, Michele; Palta, Priya; Windham, B Gwen; Thai, Sydney; Lund, Jennifer L

2018-07-01

Frailty is a geriatric syndrome characterized by weakness and weight loss and is associated with adverse health outcomes. It is often an unmeasured confounder in pharmacoepidemiologic and comparative effectiveness studies using administrative claims data. Among the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 participants (2011-2013; n = 3,146), we conducted a validation study to compare a Medicare claims-based algorithm of dependency in activities of daily living (or dependency) developed as a proxy for frailty with a reference standard measure of phenotypic frailty. We applied the algorithm to the ARIC participants' claims data to generate a predicted probability of dependency. Using the claims-based algorithm, we estimated the C-statistic for predicting phenotypic frailty. We further categorized participants by their predicted probability of dependency (<5%, 5% to <20%, and ≥20%) and estimated associations with difficulties in physical abilities, falls, and mortality. The claims-based algorithm showed good discrimination of phenotypic frailty (C-statistic = 0.71; 95% confidence interval [CI] = 0.67, 0.74). Participants classified with a high predicted probability of dependency (≥20%) had higher prevalence of falls and difficulty in physical ability, and a greater risk of 1-year all-cause mortality (hazard ratio = 5.7 [95% CI = 2.5, 13]) than participants classified with a low predicted probability (<5%). Sensitivity and specificity varied across predicted probability of dependency thresholds. The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

Frailty Screening Tools for Elderly Patients Incident to Dialysis.

PubMed

van Loon, Ismay N; Goto, Namiko A; Boereboom, Franciscus T J; Bots, Michiel L; Verhaar, Marianne C; Hamaker, Marije E

2017-09-07

A geriatric assessment is an appropriate method for identifying frail elderly patients. In CKD, it may contribute to optimize personalized care. However, a geriatric assessment is time consuming. The purpose of our study was to compare easy to apply frailty screening tools with the geriatric assessment in patients eligible for dialysis. A total of 123 patients on incident dialysis ≥65 years old were included <3 weeks before to ≤2 weeks after dialysis initiation, and all underwent a geriatric assessment. Patients with impairment in two or more geriatric domains on the geriatric assessment were considered frail. The diagnostic abilities of six frailty screening tools were compared with the geriatric assessment: the Fried Frailty Index, the Groningen Frailty Indicator, Geriatric8, the Identification of Seniors at Risk, the Hospital Safety Program, and the clinical judgment of the nephrologist. Outcome measures were sensitivity, specificity, positive predictive value, and negative predictive value. In total, 75% of patients were frail according to the geriatric assessment. Sensitivity of frailty screening tools ranged from 48% (Fried Frailty Index) to 88% (Geriatric8). The discriminating features of the clinical judgment were comparable with the other screening tools. The Identification of Seniors at Risk screening tool had the best discriminating abilities, with a sensitivity of 74%, a specificity of 80%, a positive predictive value of 91%, and a negative predictive value of 52%. The negative predictive value was poor for all tools, which means that almost one half of the patients screened as fit (nonfrail) had two or more geriatric impairments on the geriatric assessment. All frailty screening tools are able to detect geriatric impairment in elderly patients eligible for dialysis. However, all applied screening tools, including the judgment of the nephrologist, lack the discriminating abilities to adequately rule out frailty compared with a geriatric assessment. Copyright © 2017 by the American Society of Nephrology.

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Mathematical skills in 3- and 5-year-olds with spina bifida and their typically developing peers: a longitudinal approach.

PubMed

Barnes, Marcia A; Stubbs, Allison; Raghubar, Kimberly P; Agostino, Alba; Taylor, Heather; Landry, Susan; Fletcher, Jack M; Smith-Chant, Brenda

2011-05-01

Preschoolers with spina bifida (SB) were compared to typically developing (TD) children on tasks tapping mathematical knowledge at 36 months (n = 102) and 60 months of age (n = 98). The group with SB had difficulty compared to TD peers on all mathematical tasks except for transformation on quantities in the subitizable range. At 36 months, vocabulary knowledge, visual-spatial, and fine motor abilities predicted achievement on a measure of informal math knowledge in both groups. At 60 months of age, phonological awareness, visual-spatial ability, and fine motor skill were uniquely and differentially related to counting knowledge, oral counting, object-based arithmetic skills, and quantitative concepts. Importantly, the patterns of association between these predictors and mathematical performance were similar across the groups. A novel finding is that fine motor skill uniquely predicted object-based arithmetic abilities in both groups, suggesting developmental continuity in the neurocognitive correlates of early object-based and later symbolic arithmetic problem solving. Models combining 36-month mathematical ability and these language-based, visual-spatial, and fine motor abilities at 60 months accounted for considerable variance on 60-month informal mathematical outcomes. Results are discussed with reference to models of mathematical development and early identification of risk in preschoolers with neurodevelopmental disorder.

Mathematical Skills in 3- and 5-Year-Olds with Spina Bifida and Their Typically Developing Peers: A Longitudinal Approach

PubMed Central

Barnes, Marcia A.; Stubbs, Allison; Raghubar, Kimberly P.; Agostino, Alba; Taylor, Heather; Landry, Susan; Fletcher, Jack M.; Smith-Chant, Brenda

2011-01-01

Preschoolers with spina bifida (SB) were compared to typically developing (TD) children on tasks tapping mathematical knowledge at 36 months (n = 102) and 60 months of age (n = 98). The group with SB had difficulty compared to TD peers on all mathematical tasks except for transformation on quantities in the subitizable range. At 36 months, vocabulary knowledge, visual–spatial, and fine motor abilities predicted achievement on a measure of informal math knowledge in both groups. At 60 months of age, phonological awareness, visual–spatial ability, and fine motor skill were uniquely and differentially related to counting knowledge, oral counting, object-based arithmetic skills, and quantitative concepts. Importantly, the patterns of association between these predictors and mathematical performance were similar across the groups. A novel finding is that fine motor skill uniquely predicted object-based arithmetic abilities in both groups, suggesting developmental continuity in the neurocognitive correlates of early object-based and later symbolic arithmetic problem solving. Models combining 36-month mathematical ability and these language-based, visual–spatial, and fine motor abilities at 60 months accounted for considerable variance on 60-month informal mathematical outcomes. Results are discussed with reference to models of mathematical development and early identification of risk in preschoolers with neurodevelopmental disorder. PMID:21418718

Evolution of competitive ability within Lonicera japonica's invaded range

Treesearch

Gregory A. Evans; Francis F. Kilkenny; Laura F. Galloway

2013-01-01

Factors influencing invasive taxa may change during the course of an invasion. For example, intraspecific competition is predicted to be more important in areas with older stands of dense monospecific invaders than at the margins of an invaded range. We evaluated evolution in response to predicted changes in competition by comparing the intraspecific competitive...

SOME DIFFERENCES IN ENCODING AND DECODING MESSAGES.

ERIC Educational Resources Information Center

BICKLEY, A. C.; WEAVER, WENDELL W.

LANGUAGE ENCODING AND DECODING PROCESSES WERE EXAMINED BY DETERMINING THE ABILITY OF SUBJECTS TO PREDICT OMISSIONS FROM A NATURAL LANGUAGE TEXT WHICH THEY HAD PREVIOUSLY PRODUCED THEMSELVES, AND BY COMPARING THIS PERFORMANCE WITH THAT OF OTHER SUBJECTS TO PREDICT OMISSIONS FROM THESE SAME TEXTS WHICH THE SECOND GROUP READ AT THE TIME OF…

Predicting People's Environmental Behaviour: Theory of Planned Behaviour and Model of Responsible Environmental Behaviour

ERIC Educational Resources Information Center

Chao, Yu-Long

2012-01-01

Using different measures of self-reported and other-reported environmental behaviour (EB), two important theoretical models explaining EB--Hines, Hungerford and Tomera's model of responsible environmental behaviour (REB) and Ajzen's theory of planned behaviour (TPB)--were compared regarding the fit between model and data, predictive ability,…

Some Empirical Evidence for Latent Trait Model Selection.

ERIC Educational Resources Information Center

Hutten, Leah R.

The results of this study suggest that for purposes of estimating ability by latent trait methods, the Rasch model compares favorably with the three-parameter logistic model. Using estimated parameters to make predictions about 25 actual number-correct score distributions with samples of 1,000 cases each, those predicted by the Rasch model fit the…

The Development of MST Test Information for the Prediction of Test Performances

ERIC Educational Resources Information Center

Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G.

2017-01-01

The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials

NASA Astrophysics Data System (ADS)

Vlasiuk, Maryna; Sadus, Richard J.

2017-06-01

The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.

Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials.

PubMed

Vlasiuk, Maryna; Sadus, Richard J

2017-06-28

The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability

PubMed Central

Boudewyn, Megan A.; Long, Debra L.; Traxler, Matthew J.; Lesh, Tyler A.; Dave, Shruti; Mangun, George R.; Carter, Cameron S.; Swaab, Tamara Y.

2016-01-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners’ sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension. PMID:26401815

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability.

PubMed

Boudewyn, Megan A; Long, Debra L; Traxler, Matthew J; Lesh, Tyler A; Dave, Shruti; Mangun, George R; Carter, Cameron S; Swaab, Tamara Y

2015-12-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners' sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension.

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

CSF neurofilament light chain and phosphorylated tau 181 predict disease progression in PSP.

PubMed

Rojas, Julio C; Bang, Jee; Lobach, Iryna V; Tsai, Richard M; Rabinovici, Gil D; Miller, Bruce L; Boxer, Adam L

2018-01-23

To determine the ability of CSF biomarkers to predict disease progression in progressive supranuclear palsy (PSP). We compared the ability of baseline CSF β-amyloid 1-42 , tau, phosphorylated tau 181 (p-tau), and neurofilament light chain (NfL) concentrations, measured by INNO-BIA AlzBio3 or ELISA, to predict 52-week changes in clinical (PSP Rating Scale [PSPRS] and Schwab and England Activities of Daily Living [SEADL]), neuropsychological, and regional brain volumes on MRI using linear mixed effects models controlled for age, sex, and baseline disease severity, and Fisher F density curves to compare effect sizes in 50 patients with PSP. Similar analyses were done using plasma NfL measured by single molecule arrays in 141 patients. Higher CSF NfL concentration predicted more rapid decline (biomarker × time interaction) over 52 weeks in PSPRS ( p = 0.004, false discovery rate-corrected) and SEADL ( p = 0.008), whereas lower baseline CSF p-tau predicted faster decline on PSPRS ( p = 0.004). Higher CSF tau concentrations predicted faster decline by SEADL ( p = 0.004). The CSF NfL/p-tau ratio was superior for predicting change in PSPRS, compared to p-tau ( p = 0.003) or NfL ( p = 0.001) alone. Higher NfL concentrations in CSF or blood were associated with greater superior cerebellar peduncle atrophy (fixed effect, p ≤ 0.029 and 0.008, respectively). Both CSF p-tau and NfL correlate with disease severity and rate of disease progression in PSP. The inverse correlation of p-tau with disease severity suggests a potentially different mechanism of tau pathology in PSP as compared to Alzheimer disease. Copyright © 2017 American Academy of Neurology.

Testing Math or Testing Language? The Construct Validity of the KeyMath-Revised for Children With Intellectual Disability and Language Difficulties.

PubMed

Rhodes, Katherine T; Branum-Martin, Lee; Morris, Robin D; Romski, MaryAnn; Sevcik, Rose A

2015-11-01

Although it is often assumed that mathematics ability alone predicts mathematics test performance, linguistic demands may also predict achievement. This study examined the role of language in mathematics assessment performance for children with intellectual disability (ID) at less severe levels, on the KeyMath-Revised Inventory (KM-R) with a sample of 264 children, in grades 2-5. Using confirmatory factor analysis, the hypothesis that the KM-R would demonstrate discriminant validity with measures of language abilities in a two-factor model was compared to two plausible alternative models. Results indicated that KM-R did not have discriminant validity with measures of children's language abilities and was a multidimensional test of both mathematics and language abilities for this population of test users. Implications are considered for test development, interpretation, and intervention.

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

[Spanish versions of the Simplified Motor Score and the Glasgow Coma Scale in out-of-hospital treatment of head injury in adults: a preliminary study of each scale's ability to predict adverse events].

PubMed

Roca, Guillem; Mayol, Sergi; García, Esteban; Casajuana, Edgar; Quintana, Salvador

2015-06-01

To determine the ability of the modified (Spanish) version of the Simplified Motor Score (mSMS) to predict adverse events during hospitalization and to compare its predictive ability to that of the Glasgow Coma Scale (GCS) in adults with head injuries treated outside the hospital. Observational study of retrospective cohorts including all patients over the age of 14 years attended for head injuries occurring within 24 hours of treatment by an advanced life-support unit staffed by nurses between May 1, 2013, and May 1, 2014. The mSMS was a translation of the English original, created through a process of discussions of direct and back translations to arrive at consensus. Out-of-hospital patient records were searched to find GCS and mSMS scores. To predict the ability of each scale to predict brain injuries, neurosurgery, intubation, and/or inhospital death, we calculated the area under the receiving operator characteristic curves (AUCs). Of the total of 115 head-injury patients attended, 64 met the inclusion criteria. The mean (SD) age was 47 (24) years. Twelve (18.8%) patients developed some form of adverse event during hospitalization; 91.6% had brain damage, 58.3% required intubation, 8.3% required surgery, and 41.6% died. The AUC for the GCS was 0.907 (95% CI, 0.81-1.00; P<.001); the AUC for the mSMS was 0.796 (95% CI, 0.64-0.95; P=.001). Although the ability of the mSMS to predict in-hospital adverse outcomes is good, it is inferior to the GCS in adults with head injuries attended outside the hospital.

The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

PubMed Central

Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

2015-01-01

The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

The Modified Telephone Interview for Cognitive Status is More Predictive of Memory Abilities Than the Mini-Mental State Examination.

PubMed

Duff, Kevin; Tometich, Danielle; Dennett, Kathryn

2015-09-01

Although not as popular as the Mini-Mental State Examination (MMSE), the modified Telephone Interview for Cognitive Status (mTICS) has some distinct advantages when screening cognitive functioning in older adults. The current study compared these 2 cognitive screening measures in their ability to predict performance on a memory composite (ie, delayed recall of verbal and visual information) in a cohort of 121 community-dwelling older adults, both at baseline and after 1 year. Both the MMSE and the mTICS significantly correlated with the memory composite at baseline (r's of .41 and .62, respectively) and at 1 year (r's of .36 and .50, respectively). At baseline, stepwise linear regression indicated that the mTICS and gender best predicted the memory composite score (R (2) = .45, P < .001), and the MMSE and other demographic variables did not significantly improve the prediction. At 1 year, the results were very similar. Despite its lesser popularity, the mTICS may be a more attractive option when screening for cognitive abilities in this age range. © The Author(s) 2015.

Contributions of Morphological Awareness Skills to Word-Level Reading and Spelling in First-Grade Children with and without Speech Sound Disorder

ERIC Educational Resources Information Center

Apel, Kenn; Lawrence, Jessika

2011-01-01

Purpose: In this study, the authors compared the morphological awareness abilities of children with speech sound disorder (SSD) and children with typical speech skills and examined how morphological awareness ability predicted word-level reading and spelling performance above other known contributors to literacy development. Method: Eighty-eight…

Pathological gambling in Estonia: relationships with personality, self-esteem, emotional States and cognitive ability.

PubMed

Kaare, Pille-Riin; Mõttus, René; Konstabel, Kenn

2009-09-01

Due to changes in gambling accessibility during the last decade gambling has become more widespread in Estonia and the prevalence of pathological gambling has sharply increased. The present study attempts to identify psychological characteristics of Estonian pathological gamblers. It has been shown that a wide range of social, economic, and individual factors (e.g. personality traits and emotional states) predict the likelihood of becoming a pathological gambler. In the present study, pathological gamblers' (N = 33) personality traits, self-esteem, self-reported emotional states and cognitive ability were compared to the respective characteristics in a non-gambling control group (N = 42) matched for age, gender and educational level. It was found that compared to controls, pathological gamblers had higher scores on Neuroticism (especially on its immoderation facet) and lower scores on Conscientiousness (especially on its dutifulness and cautiousness facets) and on self-esteem scale. They reported more negative emotional states during the previous month (especially depression and anxiety). Finally, pathological gamblers had lower general cognitive ability. In a logistic regression model, the likelihood of being a pathological gambler was best predicted by high immoderation score and low cognitive ability.

Macrocell path loss prediction using artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

2014-04-01

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

PubMed

Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

2013-01-01

Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

Phenotype–genotype correlation in Hirschsprung disease is illuminated by comparative analysis of the RET protein sequence

PubMed Central

Kashuk, Carl S.; Stone, Eric A.; Grice, Elizabeth A.; Portnoy, Matthew E.; Green, Eric D.; Sidow, Arend; Chakravarti, Aravinda; McCallion, Andrew S.

2005-01-01

The ability to discriminate between deleterious and neutral amino acid substitutions in the genes of patients remains a significant challenge in human genetics. The increasing availability of genomic sequence data from multiple vertebrate species allows inclusion of sequence conservation and physicochemical properties of residues to be used for functional prediction. In this study, the RET receptor tyrosine kinase serves as a model disease gene in which a broad spectrum (≥116) of disease-associated mutations has been identified among patients with Hirschsprung disease and multiple endocrine neoplasia type 2. We report the alignment of the human RET protein sequence with the orthologous sequences of 12 non-human vertebrates (eight mammalian, one avian, and three teleost species), their comparative analysis, the evolutionary topology of the RET protein, and predicted tolerance for all published missense mutations. We show that, although evolutionary conservation alone provides significant information to predict the effect of a RET mutation, a model that combines comparative sequence data with analysis of physiochemical properties in a quantitative framework provides far greater accuracy. Although the ability to discern the impact of a mutation is imperfect, our analyses permit substantial discrimination between predicted functional classes of RET mutations and disease severity even for a multigenic disease such as Hirschsprung disease. PMID:15956201

Echocardiographic measurements of epicardial adipose tissue and comparative ability to predict adverse cardiovascular outcomes in patients with coronary artery disease.

PubMed

Morales-Portano, Julieta D; Peraza-Zaldivar, Juan Ángel; Suárez-Cuenca, Juan A; Aceves-Millán, Rocío; Amezcua-Gómez, Lilia; Ixcamparij-Rosales, Carlos H; Trujillo-Cortés, Rafael; Robledo-Nolasco, Rogelio; Mondragón-Terán, Paul; Pérez-Cabeza de Vaca, Rebeca; Hernández-Muñoz, Rolando; Melchor-López, Alberto; Vannan, Mani A; Rubio-Guerra, Alberto Francisco

2018-05-02

The present study aimed to compare echocardiography measurements of epicardial adipose tissue (EAT) thickness and other risk factors regarding their ability to predict adverse cardiovascular outcomes in patients with coronary artery disease (CAD). Outcomes of 107 patients (86 males, 21 females, mean age 63.6 years old) submitted to diagnostic echocardiography and coronary angiography were prospectively analyzed. EAT (measures over the right ventricle, interventricular groove and complete bulk of EAT) and left ventricle ejection fraction (LVEF) were performed by echocardiography. Coronary complexity was evaluated by Syntax score. Primary endpoints were major adverse cardiovascular events (MACE's), composite of cardiovascular death, myocardial infarction, unstable angina, intra-stent re-stenosis and episodes of decompensate heart failure requiring hospital attention during a mean follow up of 15.94 ± 3.6 months. Mean EAT thickness was 4.6 ± 1.9 mm; and correlated with Syntax score and body mass index; negatively correlated with LVEF. Twenty-three cases of MACE's were recorded during follow up, who showed higher EAT. Diagnostic ability of EAT to discriminate MACE's was comparable to LVEF (AUROC > 0.5); but higher than Syntax score. Quartile comparison of EAT revealed that measurement of the complete bulk of EAT provided a better discrimination range for MACE's, and higher, more significant adjusted risk (cutoff 4.6 mm, RR = 3.91; 95% CI 1.01-15.08; p = 0.04) than the other risk factors. We concluded that echocardiographic measurement of EAT showed higher predicting ability for MACE's than the other markers tested, in patients with CAD. Whether location for echocardiographic measurement of EAT impacts the diagnostic performance of this method deserves further study.

The influence of spelling ability on handwriting production: children with and without dyslexia.

PubMed

Sumner, Emma; Connelly, Vincent; Barnett, Anna L

2014-09-01

Current models of writing do not sufficiently address the complex relationship between the 2 transcription skills: spelling and handwriting. For children with dyslexia and beginning writers, it is conceivable that spelling ability will influence rate of handwriting production. Our aim in this study was to examine execution speed and temporal characteristics of handwriting when completing sentence-copying tasks that are free from composing demands and to determine the predictive value of spelling, pausing, and motor skill on handwriting production. Thirty-one children with dyslexia (Mage = 9 years 4 months) were compared with age-matched and spelling-ability matched children (Mage = 6 years 6 months). A digital writing tablet and Eye and Pen software were used to analyze handwriting. Children with dyslexia were able to execute handwriting at the same speed as the age-matched peers. However, they wrote less overall and paused more frequently while writing, especially within words. Combined spelling ability and within-word pausing accounted for over 76% of the variance in handwriting production of children with dyslexia, demonstrating that productivity relies on spelling capabilities. Motor skill did not significantly predict any additional variance in handwriting production. Reading ability predicted performance of the age-matched group, and pausing predicted performance for the spelling-ability group. The findings from the digital writing tablet highlight the interactive relationship between the transcription skills and how, if spelling is not fully automatized, it can constrain the rate of handwriting production. Practical implications are also addressed, emphasizing the need for more consideration to be given to what common handwriting tasks are assessing as a whole.

Sensorimotor abilities predict on-field performance in professional baseball.

PubMed

Burris, Kyle; Vittetoe, Kelly; Ramger, Benjamin; Suresh, Sunith; Tokdar, Surya T; Reiter, Jerome P; Appelbaum, L Gregory

2018-01-08

Baseball players must be able to see and react in an instant, yet it is hotly debated whether superior performance is associated with superior sensorimotor abilities. In this study, we compare sensorimotor abilities, measured through 8 psychomotor tasks comprising the Nike Sensory Station assessment battery, and game statistics in a sample of 252 professional baseball players to evaluate the links between sensorimotor skills and on-field performance. For this purpose, we develop a series of Bayesian hierarchical latent variable models enabling us to compare statistics across professional baseball leagues. Within this framework, we find that sensorimotor abilities are significant predictors of on-base percentage, walk rate and strikeout rate, accounting for age, position, and league. We find no such relationship for either slugging percentage or fielder-independent pitching. The pattern of results suggests performance contributions from both visual-sensory and visual-motor abilities and indicates that sensorimotor screenings may be useful for player scouting.

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

PubMed

León Blanco, José M; González-R, Pedro L; Arroyo García, Carmen Martina; Cózar-Bernal, María José; Calle Suárez, Marcos; Canca Ortiz, David; Rabasco Álvarez, Antonio María; González Rodríguez, María Luisa

2018-01-01

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10 000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.

Home Environment, Social Status, and Mental Test Performance

ERIC Educational Resources Information Center

Bradley, Robert H.; And Others

1977-01-01

The ability of an environmental process measure and socioeconomic status (SES) measures to predict Stanford-Binet IQ at 3 years of age was compared in a separate analysis by sex and race. The environmental process measure predicted IQ as well as a combination of process and status measures, and was superior to SES measures alone. (Author/CP)

4-Year Trajectory of Visceral Adiposity Index in the Development of Type 2 Diabetes: A Prospective Cohort Study.

PubMed

Zhang, Meilin; Zheng, Li; Li, Ping; Zhu, Yufeng; Chang, Hong; Wang, Xuan; Liu, Weiqiao; Zhang, Yuwen; Huang, Guowei

2016-01-01

Our aim was to evaluate whether visceral adiposity index (VAI) could predict the risk of type 2 diabetes (T2D) in different genders and to compare the predictive ability between VAI and other fatness indices. Four thousand seventy-eight participants including 1,817 men and 2,261 women, aged 18 and older and free of T2D at baseline were enrolled in 2010 and followed up for 4 years. New cases of T2D were identified via the annual medical examination. Cox regression analysis was used to assess the association between VAI and incidence of T2D. Receiver operating characteristic curve and area under the curves (AUC) were applied to compare the prediction ability of T2D between VAI and other fatness indices. During the 4-year follow-up, 153 (8.42%) of 1,817 men and 88 (3.89%) of 2,261 women developed T2D. The multivariable-adjusted hazards ratios for developing T2D in the highest tertile of VAI scores were 2.854 (95% CI 1.815-4.487) in men and 3.551 (95% CI 1.586-7.955) in women. The AUC of VAI was not higher than that of other fatness indices. VAI could predict the risk of T2D among Chinese adults, especially in women. However, the prediction ability of T2D risk for VAI was not higher than that of the other fatness indices. © 2016 S. Karger AG, Basel.

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

The Power of Personality

PubMed Central

Roberts, Brent W.; Kuncel, Nathan R.; Shiner, Rebecca; Caspi, Avshalom; Goldberg, Lewis R.

2015-01-01

The ability of personality traits to predict important life outcomes has traditionally been questioned because of the putative small effects of personality. In this article, we compare the predictive validity of personality traits with that of socioeconomic status (SES) and cognitive ability to test the relative contribution of personality traits to predictions of three critical outcomes: mortality, divorce, and occupational attainment. Only evidence from prospective longitudinal studies was considered. In addition, an attempt was made to limit the review to studies that controlled for important background factors. Results showed that the magnitude of the effects of personality traits on mortality, divorce, and occupational attainment was indistinguishable from the effects of SES and cognitive ability on these outcomes. These results demonstrate the influence of personality traits on important life outcomes, highlight the need to more routinely incorporate measures of personality into quality of life surveys, and encourage further research about the developmental origins of personality traits and the processes by which these traits influence diverse life outcomes. PMID:26151971

Brain size predicts problem-solving ability in mammalian carnivores

PubMed Central

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M.; Holekamp, Kay E.

2016-01-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem. PMID:26811470

Brain size predicts problem-solving ability in mammalian carnivores.

PubMed

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M; Holekamp, Kay E

2016-03-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem.

Evolutionary Influences on Attribution and Affect

PubMed Central

Brown, Jennie; Trafimow, David

2017-01-01

Evolutionary theory was applied to Reeder and Brewer's schematic theory and Trafimow's affect theory to extend this area of research with five new predictions involving affect and ability attributions, comparing morality and ability attributions, gender differences, and reaction times for affect and attribution ratings. The design included a 2 (Trait Dimension Type: HR, PR) × 2 (Behavior Type: morality, ability) × 2 (Valence: positive, negative) × 2 (Replication: original, replication) × 2 (Sex: female or male actor) × 2 (Gender: female or male participant) × 2 (Order: attribution portion first, affect portion first) mixed design. All factors were within participants except the order and participant gender. Participants were presented with 32 different scenarios in which an actor engaged in a concrete behavior after which they made attributions and rated their affect in response to the behavior. Reaction times were measured during attribution and affect ratings. In general, the findings from the experiment supported the new predictions. Affect was related to attributions for both morality and ability related behaviors. Morality related behaviors received more extreme attribution and affect ratings than ability related behaviors. Female actors received stronger attribution and affect ratings for diagnostic morality behaviors compared to male actors. Male and female actors received similar attribution and affect ratings for diagnostic ability behaviors. Diagnostic behaviors were associated with lower reaction times than non-diagnostic behaviors. These findings demonstrate the utility of evolutionary theory in creating new hypotheses and empirical findings in the domain of attribution. PMID:29312092

Evolutionary Influences on Attribution and Affect.

PubMed

Brown, Jennie; Trafimow, David

2017-01-01

Evolutionary theory was applied to Reeder and Brewer's schematic theory and Trafimow's affect theory to extend this area of research with five new predictions involving affect and ability attributions, comparing morality and ability attributions, gender differences, and reaction times for affect and attribution ratings. The design included a 2 (Trait Dimension Type: HR, PR) × 2 (Behavior Type: morality, ability) × 2 (Valence: positive, negative) × 2 (Replication: original, replication) × 2 (Sex: female or male actor) × 2 (Gender: female or male participant) × 2 (Order: attribution portion first, affect portion first) mixed design. All factors were within participants except the order and participant gender. Participants were presented with 32 different scenarios in which an actor engaged in a concrete behavior after which they made attributions and rated their affect in response to the behavior. Reaction times were measured during attribution and affect ratings. In general, the findings from the experiment supported the new predictions. Affect was related to attributions for both morality and ability related behaviors. Morality related behaviors received more extreme attribution and affect ratings than ability related behaviors. Female actors received stronger attribution and affect ratings for diagnostic morality behaviors compared to male actors. Male and female actors received similar attribution and affect ratings for diagnostic ability behaviors. Diagnostic behaviors were associated with lower reaction times than non-diagnostic behaviors. These findings demonstrate the utility of evolutionary theory in creating new hypotheses and empirical findings in the domain of attribution.

What is the quickest scoring system to predict percutaneous nephrolithotomy outcomes? A comparative study among S.T.O.N.E score, guy's stone score and croes nomogram.

PubMed

Vicentini, Fabio C; Serzedello, Felipe R; Thomas, Kay; Marchini, Giovanni S; Torricelli, Fabio C M; Srougi, Miguel; Mazzucchi, Eduardo

2017-01-01

To compare the application time and the capacity of the nomograms to predict the success of Guy's Stone Score (GSS), S.T.O.N.E. Nephrolithometry (STONE) and Clinical Research Office of the Endourological Society nephrolithometric nomogram (CROES) of percutaneous nephrolithotomy (PCNL), evaluating the most efficient one for clinical use. We studied 48 patients who underwent PCNL by the same surgeon between 2010 and 2011. We calculated GSS, STONE and CROES based on preoperative non-contrast computed tomography (CT) images and clinical data. A single observer, blinded to the outcomes, reviewed all images and assigned scores. We compared the application time of each nomogram. We used an analysis of variance for repeated measures and multiple comparisons by the Tukey test. We compared the area under the ROC curve (AUC) of the three nomograms two by two to determine the most predictive scoring system. The immediate success rate was 66.7% and complications occurred in 16.7% of cases. The average operative time was 122 minutes. Mean application time was significantly lower for the GSS (27.5 seconds) when compared to 300.6 seconds for STONE and 213.4 seconds for CROES (p<0.001). There was no significant difference among the GSS (AUC=0.653), STONE (AUC=0.563) and CROES (AUC=0.641) in the ability to predict immediate success of PCNL. All three nomograms showed similar ability to predict success of PCNL, however the GSS was the quickest to be applied, what is an important issue for routine clinical use when counseling patients who are candidates to PCNL. Copyright® by the International Brazilian Journal of Urology.

What is the quickest scoring system to predict percutaneous nephrolithotomy outcomes? A comparative study among S.T.O.N.E score, Guy's Stone Ccore and CROES nomogram

PubMed Central

Vicentini, Fabio C.; Serzedello, Felipe R.; Thomas, Kay; Marchini, Giovanni S.; Torricelli, Fabio C. M.; Srougi, Miguel; Mazzucchi, Eduardo

2017-01-01

ABSTRACT Objective: To compare the application time and the capacity of the nomograms to predict the success of Guy's Stone Score (GSS), S.T.O.N.E. Nephrolithometry (STONE) and Clinical Research Office of the Endourological Society nephrolithometric nomogram (CROES) of percutaneous nephrolithotomy (PCNL), evaluating the most efficient one for clinical use. Materials and Methods: We studied 48 patients who underwent PCNL by the same surgeon between 2010 and 2011. We calculated GSS, STONE and CROES based on pre-operative non-contrast computed tomography (CT) images and clinical data. A single observer, blinded to the outcomes, reviewed all images and assigned scores. We compared the application time of each nomogram. We used an analysis of variance for repeated measures and multiple comparisons by the Tukey test. We compared the area under the ROC curve (AUC) of the three nomograms two by two to determine the most predictive scoring system. Results: The immediate success rate was 66.7% and complications occurred in 16.7% of cases. The average operative time was 122 minutes. Mean application time was significantly lower for the GSS (27.5 seconds) when compared to 300.6 seconds for STONE and 213.4 seconds for CROES (p<0.001). There was no significant difference among the GSS (AUC=0.653), STONE (AUC=0.563) and CROES (AUC=0.641) in the ability to predict immediate success of PCNL. Conclusions: All three nomograms showed similar ability to predict success of PCNL, however the GSS was the quickest to be applied, what is an important issue for routine clinical use when counseling patients who are candidates to PCNL. PMID:28338303

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Grammatical pattern learning by human infants and cotton-top tamarin monkeys

PubMed Central

Saffran, Jenny; Hauser, Marc; Seibel, Rebecca; Kapfhamer, Joshua; Tsao, Fritz; Cushman, Fiery

2008-01-01

There is a surprising degree of overlapping structure evident across the languages of the world. One factor leading to cross-linguistic similarities may be constraints on human learning abilities. Linguistic structures that are easier for infants to learn should predominate in human languages. If correct, then (a) human infants should more readily acquire structures that are consistent with the form of natural language, whereas (b) non-human primates’ patterns of learning should be less tightly linked to the structure of human languages. Prior experiments have not directly compared laboratory-based learning of grammatical structures by human infants and non-human primates, especially under comparable testing conditions and with similar materials. Five experiments with 12-month-old human infants and adult cotton-top tamarin monkeys addressed these predictions, employing comparable methods (familiarization-discrimination) and materials. Infants rapidly acquired complex grammatical structures by using statistically predictive patterns, failing to learn structures that lacked such patterns. In contrast, the tamarins only exploited predictive patterns when learning relatively simple grammatical structures. Infant learning abilities may serve both to facilitate natural language acquisition and to impose constraints on the structure of human languages. PMID:18082676

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

Comparison between model predictions and observations of ELF radio atmospherics generated by rocket-triggered lightning

NASA Astrophysics Data System (ADS)

Dupree, N. A.; Moore, R. C.

2011-12-01

Model predictions of the ELF radio atmospheric generated by rocket-triggered lightning are compared with observations performed at Arrival Heights, Antarctica. The ability to infer source characteristics using observations at great distances may prove to greatly enhance the understanding of lightning processes that are associated with the production of transient luminous events (TLEs) as well as other ionospheric effects associated with lightning. The modeling of the sferic waveform is carried out using a modified version of the Long Wavelength Propagation Capability (LWPC) code developed by the Naval Ocean Systems Center over a period of many years. LWPC is an inherently narrowband propagation code that has been modified to predict the broadband response of the Earth-ionosphere waveguide to an impulsive lightning flash while preserving the ability of LWPC to account for an inhomogeneous waveguide. ELF observations performed at Arrival Heights, Antarctica during rocket-triggered lightning experiments at the International Center for Lightning Research and Testing (ICLRT) located at Camp Blanding, Florida are presented. The lightning current waveforms directly measured at the base of the lightning channel (at the ICLRT) are used together with LWPC to predict the sferic waveform observed at Arrival Heights under various ionospheric conditions. This paper critically compares observations with model predictions.

Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.

PubMed

Hidalgo, André M; Bastiaansen, John W M; Lopes, Marcos S; Harlizius, Barbara; Groenen, Martien A M; de Koning, Dirk-Jan

2015-05-26

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent. Copyright © 2015 Hidalgo et al.

Why did the bear cross the road? Comparing the performance of multiple resistance surfaces and connectivity modeling methods

Treesearch

Samuel A. Cushman; Jesse S. Lewis; Erin L. Landguth

2014-01-01

There have been few assessments of the performance of alternative resistance surfaces, and little is known about how connectivity modeling approaches differ in their ability to predict organism movements. In this paper, we evaluate the performance of four connectivity modeling approaches applied to two resistance surfaces in predicting the locations of highway...

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory

ERIC Educational Resources Information Center

Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N.

2016-01-01

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

Project Evaluation: Validation of a Scale and Analysis of Its Predictive Capacity

ERIC Educational Resources Information Center

Fernandes Malaquias, Rodrigo; de Oliveira Malaquias, Fernanda Francielle

2014-01-01

The objective of this study was to validate a scale for assessment of academic projects. As a complement, we examined its predictive ability by comparing the scores of advised/corrected projects based on the model and the final scores awarded to the work by an examining panel (approximately 10 months after the project design). Results of…

Comparison of clinician-predicted to measured low vision outcomes.

PubMed

Chan, Tiffany L; Goldstein, Judith E; Massof, Robert W

2013-08-01

To compare low-vision rehabilitation (LVR) clinicians' predictions of the probability of success of LVR with patients' self-reported outcomes after provision of usual outpatient LVR services and to determine if patients' traits influence clinician ratings. The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre-and post-LVR to 316 low-vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression, and cognitive status. After patient evaluation, 38 LVR clinicians estimated the probability of outcome success (POS) using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients' baseline traits on predicted outcomes. A regression analysis with a hierarchical random-effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates that the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed-effects regression models show that POS ratings are associated with information about the patient's cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. Clinicians' predictions of LVR outcomes seem to be influenced by knowledge of patients' cognitive functioning and the combination of visual acuity and functional ability-information clinicians acquire from the patient's history and examination. However, clinicians' predictions do not agree with observed changes in functional ability from the patient's perspective; they are no better than chance.

Serial evaluation of the MODS, SOFA and LOD scores to predict ICU mortality in mixed critically ill patients.

PubMed

Khwannimit, Bodin

2008-09-01

To perform a serial assessment and compare ability in predicting the intensive care unit (ICU) mortality of the multiple organ dysfunction score (MODS), sequential organ failure assessment (SOFA) and logistic organ dysfunction (LOD) score. The data were collected prospectively on consecutive ICU admissions over a 24-month period at a tertiary referral university hospital. The MODS, SOFA, and LOD scores were calculated on initial and repeated every 24 hrs. Two thousand fifty four patients were enrolled in the present study. The maximum and delta-scores of all the organ dysfunction scores correlated with ICU mortality. The maximum score of all models had better ability for predicting ICU mortality than initial or delta score. The areas under the receiver operating characteristic curve (AUC) for maximum scores was 0.892 for the MODS, 0.907 for the SOFA, and 0.92for the LOD. No statistical difference existed between all maximum scores and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Serial assessment of organ dysfunction during the ICU stay is reliable with ICU mortality. The maximum scores is the best discrimination comparable with APACHE II score in predicting ICU mortality.

Learning disabled and average readers' working memory and comprehension: does metacognition play a role?

PubMed

Swanson, H L; Trahan, M

1996-09-01

The present study investigates (a) whether learning disabled readers' working memory deficits that underlie poor reading comprehension are related to a general system, and (b) whether metacognition contributes to comprehension beyond what is predicted by working memory and word knowledge. To this end, performance between learning and disabled (N = 60) and average readers (N = 60) was compared on the reading comprehension, reading rate, and vocabulary subtests of the Nelson Skills Reading Test, Sentence Span test composed of high and low imagery words, and a Metacognitive Questionnaire. As expected, differences between groups in working memory, vocabulary, and reading measures emerged, whereas ability groups were statistically comparable on the Metacognitive Questionnaire. A within-group analysis indicated that the correlation patterns between working memory, vocabulary, metacognition, and reading comprehension were not the same between ability groups. For predicting reading comprehension, the metacognitive questionnaire best predicted learning disabled readers' performance, whereas the working memory span measure that included low-imagery words best predicted average achieving readers' comprehension. Overall, the results suggest that the relationship between learning disabled readers' generalised working memory deficits and poor reading comprehension may be mediated by metacognition.

ELF Sferics Observed at Large Distances

NASA Astrophysics Data System (ADS)

Dupree, N. A.; Moore, R. C.

2012-12-01

Model predictions of the ELF radio atmospheric generated by rocket-triggered lightning are compared with observations performed at at large (>1 Mm) distances. The ability to infer source characteristics using observations at great distances may prove to greatly enhance the understanding of lightning processes that are associated with the production of transient luminous events (TLEs) as well as other ionospheric effects associated with lightning. The modeling of the sferic waveform is carried out using a modified version of the Long Wavelength Propagation Capability (LWPC) code developed by the Naval Ocean Systems Center over a period of many years. LWPC is an inherently narrowband propagation code that has been modified to predict the broadband response of the Earth-ionosphere waveguide to an impulsive lightning flash while preserving the ability of LWPC to account for an inhomogeneous waveguide. ELF observations performed in Alaska and Antarctica during rocket-triggered lightning experiments at the International Center for Lightning Research and Testing (ICLRT) located at Camp Blanding, Florida are presented. The lightning current waveforms directly measured at the base of the lightning channel (at the ICLRT) are used together with LWPC to predict the sferic waveform observed at the receiver locations under various ionospheric conditions. This paper critically compares observations with model predictions.

High Reynolds number analysis of an axisymmetric afterbody with flow separation

NASA Technical Reports Server (NTRS)

Carlson, John R.; Reubush, David E.

1996-01-01

The ability of a three-dimensional Navier-Stokes method, PAB3D, to predict nozzle afterbody flow at high Reynolds number was assessed. Predicted surface pressure coefficient distributions and integrated afterbody drag are compared with experimental data obtained from the NASA-Langley 0.3 m Transonic Cryogenic Tunnel. Predicted afterbody surface pressures matched experimental data fairly closely. The change in the pressure coefficient distribution with Reynolds number was slightly over-predicted. Integrated afterbody drag was typically high compared to the experimental data. The change in afterbody pressure drag with Reynolds number was fairly small. The predicted point of flow separation on the nozzle was slightly downstream of that observed from oilflow data at low Reynolds numbers and had a very slight Reynolds number dependence, moving slightly further downstream as Reynolds number increased.

Analysis of the predictive qualities of betting odds and FIFA World Ranking: evidence from the 2006, 2010 and 2014 Football World Cups.

PubMed

Wunderlich, Fabian; Memmert, Daniel

2016-12-01

The present study aims to investigate the ability of a new framework enabling to derive more detailed model-based predictions from ranking systems. These were compared to predictions from the bet market including data from the World Cups 2006, 2010, and 2014. The results revealed that the FIFA World Ranking has essentially improved its predictive qualities compared to the bet market since the mode of calculation was changed in 2006. While both predictors were useful to obtain accurate predictions in general, the world ranking was able to outperform the bet market significantly for the World Cup 2014 and when the data from the World Cups 2010 and 2014 were pooled. Our new framework can be extended in future research to more detailed prediction tasks (i.e., predicting the final scores of a match or the tournament progress of a team).

Emotional Intelligence and cognitive abilities - associations and sex differences.

PubMed

Pardeller, Silvia; Frajo-Apor, Beatrice; Kemmler, Georg; Hofer, Alex

2017-09-01

In order to expand on previous research, this cross-sectional study investigated the relationship between Emotional Intelligence (EI) and cognitive abilities in healthy adults with a special focus on potential sex differences. EI was assessed by means of the Mayer-Salovey-Caruso-Emotional-Intelligence Test (MSCEIT), whereas cognitive abilities were investigated using the Brief Assessment of Cognition in Schizophrenia (BACS), which measures key aspects of cognitive functioning, i.e. verbal memory, working memory, motor speed, verbal fluency, attention and processing speed, and reasoning and problem solving. 137 subjects (65% female) with a mean age of 38.7 ± 11.8 years were included into the study. While males and females were comparable with regard to EI, men achieved significantly higher BACS composite scores and outperformed women in the BACS subscales motor speed, attention and processing speed, and reasoning and problem solving. Verbal fluency significantly predicted EI, whereas the MSCEIT subscale understanding emotions significantly predicted the BACS composite score. Our findings support previous research and emphasize the relevance of considering cognitive abilities when assessing ability EI in healthy individuals.

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

PubMed

Fei, Y; Hu, J; Li, W-Q; Wang, W; Zong, G-Q

2017-03-01

Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicting PSMVT. Additional predictive factors may be incorporated into artificial neural networks. Objective To construct and validate artificial neural networks (ANNs) for predicting the occurrence of portosplenomesenteric venous thrombosis (PSMVT) and compare the predictive ability of the ANNs with that of logistic regression. Methods The ANNs and logistic regression modeling were constructed using simple clinical and laboratory data of 72 acute pancreatitis (AP) patients. The ANNs and logistic modeling were first trained on 48 randomly chosen patients and validated on the remaining 24 patients. The accuracy and the performance characteristics were compared between these two approaches by SPSS17.0 software. Results The training set and validation set did not differ on any of the 11 variables. After training, the back propagation network training error converged to 1 × 10 -20 , and it retained excellent pattern recognition ability. When the ANNs model was applied to the validation set, it revealed a sensitivity of 80%, specificity of 85.7%, a positive predictive value of 77.6% and negative predictive value of 90.7%. The accuracy was 83.3%. Differences could be found between ANNs modeling and logistic regression modeling in these parameters (10.0% [95% CI, -14.3 to 34.3%], 14.3% [95% CI, -8.6 to 37.2%], 15.7% [95% CI, -9.9 to 41.3%], 11.8% [95% CI, -8.2 to 31.8%], 22.6% [95% CI, -1.9 to 47.1%], respectively). When ANNs modeling was used to identify PSMVT, the area under receiver operating characteristic curve was 0.849 (95% CI, 0.807-0.901), which demonstrated better overall properties than logistic regression modeling (AUC = 0.716) (95% CI, 0.679-0.761). Conclusions ANNs modeling was a more accurate tool than logistic regression in predicting the occurrence of PSMVT following AP. More clinical factors or biomarkers may be incorporated into ANNs modeling to improve its predictive ability. © 2016 International Society on Thrombosis and Haemostasis.

Chronic Conditions and Mortality Among the Oldest Old

PubMed Central

Lee, Sei J.; Go, Alan S.; Lindquist, Karla; Bertenthal, Daniel; Covinsky, Kenneth E.

2008-01-01

Objectives. We sought to determine whether chronic conditions and functional limitations are equally predictive of mortality among older adults. Methods. Participants in the 1998 wave of the Health and Retirement Study (N=19430) were divided into groups by decades of age, and their vital status in 2004 was determined. We used multivariate Cox regression to determine the ability of chronic conditions and functional limitations to predict mortality. Results. As age increased, the ability of chronic conditions to predict mortality declined rapidly, whereas the ability of functional limitations to predict mortality declined more slowly. In younger participants (aged 50–59 years), chronic conditions were stronger predictors of death than were functional limitations (Harrell C statistic 0.78 vs. 0.73; P=.001). In older participants (aged 90–99 years), functional limitations were stronger predictors of death than were chronic conditions (Harrell C statistic 0.67 vs. 0.61; P=.004). Conclusions. The importance of chronic conditions as a predictor of death declined rapidly with increasing age. Therefore, risk-adjustment models that only consider comorbidities when comparing mortality rates across providers may be inadequate for adults older than 80 years. PMID:18511714

Predicting the ability to produce emerald ash borer: a comparison of riparian and upland ash forests in southern lower Michigan

Treesearch

Susan J. Crocker; Deborah G. McCullough; Nathan W. Siegert

2009-01-01

Concern for the future of ash trees in the United States has risen since the 2002 discovery of emerald ash borer (EAB) (Agrilus planipennis Fairmaire) in southeastern Michigan. The ability of ash forests in the Southern Lower Peninsula of Michigan to produce EAB was compared by physiographic class and stand size. Results showed that EAB production...

A procedure for predicting internal and external noise fields of blowdown wind tunnels

NASA Technical Reports Server (NTRS)

Hosier, R. N.; Mayes, W. H.

1972-01-01

The noise generated during the operation of large blowdown wind tunnels is considered. Noise calculation procedures are given to predict the test-section overall and spectrum level noise caused by both the tunnel burner and turbulent boundary layer. External tunnel noise levels due to the tunnel burner and circular jet exhaust flow are also calculated along with their respective cut-off frequency and spectrum peaks. The predicted values are compared with measured data, and the ability of the prediction procedure to estimate blowdown-wind-tunnel noise levels is shown.

Predictive value of background experiences and visual spatial ability testing on laparoscopic baseline performance among residents entering postgraduate surgical training.

PubMed

Louridas, Marisa; Quinn, Lauren E; Grantcharov, Teodor P

2016-03-01

Emerging evidence suggests that despite dedicated practice, not all surgical trainees have the ability to reach technical competency in minimally invasive techniques. While selecting residents that have the ability to reach technical competence is important, evidence to guide the incorporation of technical ability into selection processes is limited. Therefore, the purpose of the present study was to evaluate whether background experiences and 2D-3D visual spatial test results are predictive of baseline laparoscopic skill for the novice surgical trainee. First-year residents were studied. Demographic data and background surgical and non-surgical experiences were obtained using a questionnaire. Visual spatial ability was evaluated using the PicSOr, cube comparison (CC) and card rotation (CR) tests. Technical skill was assessed using the camera navigation (LCN) task and laparoscopic circle cut (LCC) task. Resident performance on these technical tasks was compared and correlated with the questionnaire and visual spatial findings. Previous experience in observing laparoscopic procedures was associated with significantly better LCN performance, and experience in navigating the laparoscopic camera was associated with significantly better LCC task results. Residents who scored higher on the CC test demonstrated a more accurate LCN path length score (r s(PL) = -0.36, p = 0.03) and angle path (r s(AP) = -0.426, p = 0.01) score when completing the LCN task. No other significant correlations were found between the visual spatial tests (PicSOr, CC or CR) and LCC performance. While identifying selection tests for incoming surgical trainees that predict technical skill performance is appealing, the surrogate markers evaluated correlate with specific metrics of surgical performance related to a single task but do not appear to reliably predict technical performance of different laparoscopic tasks. Predicting the acquisition of technical skills will require the development of a series of evidence-based tests that measure a number of innate abilities as well as their inherent interactions.

Fine Motor Skills Predict Maths Ability Better than They Predict Reading Ability in the Early Primary School Years

PubMed Central

Pitchford, Nicola J.; Papini, Chiara; Outhwaite, Laura A.; Gulliford, Anthea

2016-01-01

Fine motor skills have long been recognized as an important foundation for development in other domains. However, more precise insights into the role of fine motor skills, and their relationships to other skills in mediating early educational achievements, are needed to support the development of optimal educational interventions. We explored concurrent relationships between two components of fine motor skills, Fine Motor Precision and Fine Motor Integration, and early reading and maths development in two studies with primary school children of low-to-mid socio-economic status in the UK. Two key findings were revealed. First, despite being in the first 2 years of primary school education, significantly better performance was found in reading compared to maths across both studies. This may reflect the protective effects of recent national-level interventions to promote early literacy skills in young children in the UK that have not been similarly promoted for maths. Second, fine motor skills were a better predictor of early maths ability than they were of early reading ability. Hierarchical multiple regression revealed that fine motor skills did not significantly predict reading ability when verbal short-term memory was taken into account. In contrast, Fine Motor Integration remained a significant predictor of maths ability, even after the influence of non-verbal IQ had been accounted for. These results suggest that fine motor skills should have a pivotal role in educational interventions designed to support the development of early mathematical skills. PMID:27303342

Fine Motor Skills Predict Maths Ability Better than They Predict Reading Ability in the Early Primary School Years.

PubMed

Pitchford, Nicola J; Papini, Chiara; Outhwaite, Laura A; Gulliford, Anthea

2016-01-01

Fine motor skills have long been recognized as an important foundation for development in other domains. However, more precise insights into the role of fine motor skills, and their relationships to other skills in mediating early educational achievements, are needed to support the development of optimal educational interventions. We explored concurrent relationships between two components of fine motor skills, Fine Motor Precision and Fine Motor Integration, and early reading and maths development in two studies with primary school children of low-to-mid socio-economic status in the UK. Two key findings were revealed. First, despite being in the first 2 years of primary school education, significantly better performance was found in reading compared to maths across both studies. This may reflect the protective effects of recent national-level interventions to promote early literacy skills in young children in the UK that have not been similarly promoted for maths. Second, fine motor skills were a better predictor of early maths ability than they were of early reading ability. Hierarchical multiple regression revealed that fine motor skills did not significantly predict reading ability when verbal short-term memory was taken into account. In contrast, Fine Motor Integration remained a significant predictor of maths ability, even after the influence of non-verbal IQ had been accounted for. These results suggest that fine motor skills should have a pivotal role in educational interventions designed to support the development of early mathematical skills.

Thyroid-specific questions on work ability showed known-groups validity among Danes with thyroid diseases.

PubMed

Nexo, Mette Andersen; Watt, Torquil; Bonnema, Steen Joop; Hegedüs, Laszlo; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla; Bjorner, Jakob Bue

2015-07-01

We aimed to identify the best approach to work ability assessment in patients with thyroid disease by evaluating the factor structure, measurement equivalence, known-groups validity, and predictive validity of a broad set of work ability items. Based on the literature and interviews with thyroid patients, 24 work ability items were selected from previous questionnaires, revised, or developed anew. Items were tested among 632 patients with thyroid disease (non-toxic goiter, toxic nodular goiter, Graves' disease (with or without orbitopathy), autoimmune hypothyroidism, and other thyroid diseases), 391 of which had participated in a study 5 years previously. Responses to select items were compared to general population data. We used confirmatory factor analyses for categorical data, logistic regression analyses and tests of differential item function, and head-to-head comparisons of relative validity in distinguishing known groups. Although all work ability items loaded on a common factor, the optimal factor solution included five factors: role physical, role emotional, thyroid-specific limitations, work limitations (without disease attribution), and work performance. The scale on thyroid-specific limitations showed the most power in distinguishing clinical groups and time since diagnosis. A global single item proved useful for comparisons with the general population, and a thyroid-specific item predicted labor market exclusion within the next 5 years (OR 5.0, 95 % CI 2.7-9.1). Items on work limitations with attribution to thyroid disease were most effective in detecting impact on work ability and showed good predictive validity. Generic work ability items remain useful for general population comparisons.

Comparing Mammography Abnormality Features and Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy

PubMed Central

Burnside, Elizabeth S.; Liu, Jie; Wu, Yirong; Onitilo, Adedayo A.; McCarty, Catherine; Page, C. David; Peissig, Peggy; Trentham-Dietz, Amy; Kitchner, Terrie; Fan, Jun; Yuan, Ming

2015-01-01

Rationale and Objectives The discovery of germline genetic variants associated with breast cancer has engendered interest in risk stratification for improved, targeted detection and diagnosis. However, there has yet to be a comparison of the predictive ability of these genetic variants with mammography abnormality descriptors. Materials and Methods Our IRB-approved, HIPAA-compliant study utilized a personalized medicine registry in which participants consented to provide a DNA sample and participate in longitudinal follow-up. In our retrospective, age-matched, case-controlled study of 373 cases and 395 controls who underwent breast biopsy, we collected risk factors selected a priori based on the literature including: demographic variables based on the Gail model, common germline genetic variants, and diagnostic mammography findings according to BI-RADS. We developed predictive models using logistic regression to determine the predictive ability of: 1) demographic variables, 2) 10 selected genetic variants, or 3) mammography BI-RADS features. We evaluated each model in turn by calculating a risk score for each patient using 10-fold cross validation; used this risk estimate to construct ROC curves; and compared the AUC of each using the DeLong method. Results The performance of the regression model using demographic risk factors was not statistically different from the model using genetic variants (p=0.9). The model using mammography features (AUC = 0.689) was superior to both the demographic model (AUC = .598; p<0.001) and the genetic model (AUC = .601; p<0.001). Conclusion BI-RADS features exceeded the ability of demographic and 10 selected germline genetic variants to predict breast cancer in women recommended for biopsy. PMID:26514439

Risk-Based Questionnaires Fail to Detect Adolescent Iron Deficiency and Anemia.

PubMed

Sekhar, Deepa L; Murray-Kolb, Laura E; Schaefer, Eric W; Paul, Ian M

2017-08-01

To evaluate the predictive ability of screening questionnaires to identify adolescent women at high-risk for iron deficiency or iron deficiency anemia who warrant objective laboratory testing. Cross-sectional study of 96 female individuals 12-21 years old seen at an academic medical center. Participants completed an iron deficiency risk assessment questionnaire including the 4 Bright Futures Adolescent Previsit Questionnaire anemia questions, along with depression, attention, food insecurity, and daytime sleepiness screens. Multiple linear regression controlling for age, race, and hormonal contraception use compared the predictive ability of 2 models for adolescent iron deficiency (defined as ferritin <12 mcg/L) and anemia (hemoglobin <12 g/dL). Model 1, the Bright Futures questions, was compared with model 2, which included the 4 aforementioned screens and body mass index percentile. Among participants, 18% (17/96) had iron deficiency and 5% (5/96) had iron deficiency anemia. Model 1 (Bright Futures) poorly predicted ferritin and hemoglobin values (R 2  = 0.03 and 0.08, respectively). Model 2 demonstrated similarly poor predictive ability (R 2  = 0.05 and 0.06, respectively). Mean differences for depressive symptoms (0.3, 95% CI -0.2, 0.8), attention difficulty (-0.1, 95% CI -0.5, 0.4), food insecurity (0.04, 95% CI -0.5, 0.6), daytime sleepiness (0.1, 95% CI -0.1, 0.3), and body mass index percentile (-0.04, 95% CI -0.3, 0.2) were not significantly associated with ferritin in model 2. Mean differences for hemoglobin were also nonsignificant. Risk-based surveys poorly predict objective measures of iron status using ferritin and hemoglobin. Next steps are to establish the optimal timing for objective assessment of adolescent iron deficiency and anemia. Copyright © 2017 Elsevier Inc. All rights reserved.

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.

PubMed

Perišić, Ognjen

2018-03-16

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM's weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol's ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner's interacting scaffold is more flexible and adaptable.

Evaluation and comparison of the ability of online available prediction programs to predict true linear B-cell epitopes.

PubMed

Costa, Juan G; Faccendini, Pablo L; Sferco, Silvano J; Lagier, Claudia M; Marcipar, Iván S

2013-06-01

This work deals with the use of predictors to identify useful B-cell linear epitopes to develop immunoassays. Experimental techniques to meet this goal are quite expensive and time consuming. Therefore, we tested 5 free, online prediction methods (AAPPred, ABCpred, BcePred, BepiPred and Antigenic) widely used for predicting linear epitopes, using the primary structure of the protein as the only input. We chose a set of 65 experimentally well documented epitopes obtained by the most reliable experimental techniques as our true positive set. To compare the quality of the predictor methods we used their positive predictive value (PPV), i.e. the proportion of the predicted epitopes that are true, experimentally confirmed epitopes, in relation to all the epitopes predicted. We conclude that AAPPred and ABCpred yield the best results as compared with the other programs and with a random prediction procedure. Our results also indicate that considering the consensual epitopes predicted by several programs does not improve the PPV.

The Predictive Validity of Using Admissions Testing and Multiple Mini-Interviews in Undergraduate University Admissions

ERIC Educational Resources Information Center

Makransky, Guido; Havmose, Philip; Vang, Maria Louison; Andersen, Tonny Elmose; Nielsen, Tine

2017-01-01

The aim of this study was to evaluate the predictive validity of a two-step admissions procedure that included a cognitive ability test followed by multiple mini-interviews (MMIs) used to assess non-cognitive skills, compared to grade-based admissions relative to subsequent drop-out rates and academic achievement after one and two years of study.…

Genetic training of network using chaos concept: application to QSAR studies of vibration modes of tetrahedral halides.

PubMed

Lu, Qingzhang; Shen, Guoli; Yu, Ruqin

2002-11-15

The chaotic dynamical system is introduced in genetic algorithm to train ANN to formulate the CGANN algorithm. Logistic mapping as one of the most important chaotic dynamic mappings provides each new generation a high chance to hold GA's population diversity. This enhances the ability to overcome overfitting in training an ANN. The proposed CGANN has been used for QSAR studies to predict the tetrahedral modes (nu(1)(A1) and nu(2)(E)) of halides [MX(4)](epsilon). The frequencies predicted by QSAR were compared with those calculated by quantum chemistry methods including PM3, AM1, and MNDO/d. The possibility of improving the predictive ability of QSAR by including quantum chemistry parameters as feature variables has been investigated using tetrahedral tetrahalide examples. Copyright 2002 Wiley Periodicals, Inc.

Predicting the toxicity of sediment-associated trace metals with simultaneously extracted trace metal: Acid-volatile sulfide concentrations and dry weight-normalized concentrations: A critical comparison

USGS Publications Warehouse

Long, E.R.; MacDonald, D.D.; Cubbage, J.C.; Ingersoll, C.G.

1998-01-01

The relative abilities of sediment concentrations of simultaneously extracted trace metal: acid-volatile sulfide (SEM: AVS) and dry weight-normalized trace metals to correctly predict both toxicity and nontoxicity were compared by analysis of 77 field-collected samples. Relative to the SEM:AVS concentrations, sediment guidelines based upon dry weight-normalized concentrations were equally or slightly more accurate in predicting both nontoxic and toxic results in laboratory tests.

Genetic Predisposition to Ischemic Stroke

PubMed Central

Kamatani, Yoichiro; Takahashi, Atsushi; Hata, Jun; Furukawa, Ryohei; Shiwa, Yuh; Yamaji, Taiki; Hara, Megumi; Tanno, Kozo; Ohmomo, Hideki; Ono, Kanako; Takashima, Naoyuki; Matsuda, Koichi; Wakai, Kenji; Sawada, Norie; Iwasaki, Motoki; Yamagishi, Kazumasa; Ago, Tetsuro; Ninomiya, Toshiharu; Fukushima, Akimune; Hozawa, Atsushi; Minegishi, Naoko; Satoh, Mamoru; Endo, Ryujin; Sasaki, Makoto; Sakata, Kiyomi; Kobayashi, Seiichiro; Ogasawara, Kuniaki; Nakamura, Motoyuki; Hitomi, Jiro; Kita, Yoshikuni; Tanaka, Keitaro; Iso, Hiroyasu; Kitazono, Takanari; Kubo, Michiaki; Tanaka, Hideo; Tsugane, Shoichiro; Kiyohara, Yutaka; Yamamoto, Masayuki; Sobue, Kenji; Shimizu, Atsushi

2017-01-01

Background and Purpose— The prediction of genetic predispositions to ischemic stroke (IS) may allow the identification of individuals at elevated risk and thereby prevent IS in clinical practice. Previously developed weighted multilocus genetic risk scores showed limited predictive ability for IS. Here, we investigated the predictive ability of a newer method, polygenic risk score (polyGRS), based on the idea that a few strong signals, as well as several weaker signals, can be collectively informative to determine IS risk. Methods— We genotyped 13 214 Japanese individuals with IS and 26 470 controls (derivation samples) and generated both multilocus genetic risk scores and polyGRS, using the same derivation data set. The predictive abilities of each scoring system were then assessed using 2 independent sets of Japanese samples (KyushuU and JPJM data sets). Results— In both validation data sets, polyGRS was shown to be significantly associated with IS, but weighted multilocus genetic risk scores was not. Comparing the highest with the lowest polyGRS quintile, the odds ratios for IS were 1.75 (95% confidence interval, 1.33–2.31) and 1.99 (95% confidence interval, 1.19–3.33) in the KyushuU and JPJM samples, respectively. Using the KyushuU samples, the addition of polyGRS to a nongenetic risk model resulted in a significant improvement of the predictive ability (net reclassification improvement=0.151; P<0.001). Conclusions— The polyGRS was shown to be superior to weighted multilocus genetic risk scores as an IS prediction model. Thus, together with the nongenetic risk factors, polyGRS will provide valuable information for individual risk assessment and management of modifiable risk factors. PMID:28034966

PhyloGibbs-MP: Module Prediction and Discriminative Motif-Finding by Gibbs Sampling

PubMed Central

Siddharthan, Rahul

2008-01-01

PhyloGibbs, our recent Gibbs-sampling motif-finder, takes phylogeny into account in detecting binding sites for transcription factors in DNA and assigns posterior probabilities to its predictions obtained by sampling the entire configuration space. Here, in an extension called PhyloGibbs-MP, we widen the scope of the program, addressing two major problems in computational regulatory genomics. First, PhyloGibbs-MP can localise predictions to small, undetermined regions of a large input sequence, thus effectively predicting cis-regulatory modules (CRMs) ab initio while simultaneously predicting binding sites in those modules—tasks that are usually done by two separate programs. PhyloGibbs-MP's performance at such ab initio CRM prediction is comparable with or superior to dedicated module-prediction software that use prior knowledge of previously characterised transcription factors. Second, PhyloGibbs-MP can predict motifs that differentiate between two (or more) different groups of regulatory regions, that is, motifs that occur preferentially in one group over the others. While other “discriminative motif-finders” have been published in the literature, PhyloGibbs-MP's implementation has some unique features and flexibility. Benchmarks on synthetic and actual genomic data show that this algorithm is successful at enhancing predictions of differentiating sites and suppressing predictions of common sites and compares with or outperforms other discriminative motif-finders on actual genomic data. Additional enhancements include significant performance and speed improvements, the ability to use “informative priors” on known transcription factors, and the ability to output annotations in a format that can be visualised with the Generic Genome Browser. In stand-alone motif-finding, PhyloGibbs-MP remains competitive, outperforming PhyloGibbs-1.0 and other programs on benchmark data. PMID:18769735

Theory of mind reasoning in schizophrenia patients and non-psychotic relatives.

PubMed

Cassetta, Briana; Goghari, Vina

2014-08-15

Research consistently demonstrates that schizophrenia patients have theory of mind (ToM) impairments. Additionally, there is some evidence that family members of schizophrenia patients also demonstrate impairments in ToM, suggesting a genetic vulnerability for the disorder. This study assessed ToM abilities (i.e., sarcasm comprehension) in schizophrenia patients and their first-degree biological relatives during video-taped social interactions, to be representative of real-world interactions and to assess for disease-specific and/or genetic liability effects. Additionally, we assessed whether ToM abilities predicted social and global functioning in schizophrenia patients, and whether symptoms were associated with ToM deficits. Schizophrenia patients demonstrated impairments in sarcasm comprehension compared to controls and relatives, whereas relatives showed intact comprehension. Symptoms of schizophrenia significantly predicted worse ToM abilities. Furthermore, in schizophrenia patients, impaired ToM reasoning predicted worse social and global functioning. Given schizophrenia patients demonstrated impairments in ToM reasoning in a task that resembles real-life interactions, this might be a key area for remediation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Wild Mammalian Biomonitors for Assessing Impacts of Environmental Contamination on Population and Community Ecology

DTIC Science & Technology

1993-06-01

will be compared to common laboratory bioassay tests (fathea minnow survival, rice seed germination test, etc.), relative to their ability to pre- ’dict...rice seed germination , and Ceriodaphnia assays. At the ecosystem level, in situ small mammal total biomass, sex ratios, reproduction, recruit- ment...bioassay tests (fathead minnow survival, rice seed germination test, etc.), relative to their ability to predict ecotoxicity risks (as indexed by

Work ability as a determinant of old age disability severity: evidence from the 28-year Finnish Longitudinal Study on Municipal Employees.

PubMed

von Bonsdorff, Mikaela B; Seitsamo, Jorma; Ilmarinen, Juhani; Nygård, Clas-Håkan; von Bonsdorff, Monika E; Rantanen, Taina

2012-08-01

Lower occupational class correlates with a higher disability risk later in life. However, it is not clear whether the demands made by mental and physical work relative to individual resources in midlife predict well-being in old age. This study investigated prospectively whether work ability in midlife predicts disability severity in activities of everyday living in old age. Data come from the population-based 28-year follow-up called Finnish Longitudinal Study of Municipal Employees. A total of 2879 occupationally active persons aged 44-58 years answered a questionnaire on work ability at baseline in 1981 and activities of daily living in 2009. At baseline, perceived work ability relative to lifetime best was categorized into excellent, moderate, and poor work ability. At follow-up, disability scales were constructed based on the severity and frequency of difficulties reported in self-care activities of daily living (ADL) and instrumental activities of daily living (IADL). There was a graded prevalence of ADL and IADL disability severity, according to excellent, moderate and poor midlife work ability (p<0.001). Employees with moderate midlife work ability had an 11 to 20% higher mean ADL or IADL disability severity score, compared with those with excellent midlife work ability (reference), incidence rate ratios (IRR) ranging from 1.11 (95% CI 1.01-1.22) to 1.20 (95% CI 1.10-1.30). Those with poor midlife work ability had a mean ADL or IADL disability severity score 27 to 38% higher than the referent, IRRs ranging from 1.27 (95% CI 1.09-1.47) to 1.38 (95% CI 1.25-1.53). Adjusting for socio-economics, lifestyle factors and chronic diseases only slightly attenuated the associations. Work ability, an indicator of the de- mands made by mental and physical work relative to individuals' mental and physical resources, predicted disability severity 28 years later among middle-aged municipal employees.

Multi-criteria comparative evaluation of spallation reaction models

NASA Astrophysics Data System (ADS)

Andrianov, Andrey; Andrianova, Olga; Konobeev, Alexandr; Korovin, Yury; Kuptsov, Ilya

2017-09-01

This paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb.

Comparing self-reported health status and diagnosis-based risk adjustment to predict 1- and 2 to 5-year mortality.

PubMed

Pietz, Kenneth; Petersen, Laura A

2007-04-01

To compare the ability of two diagnosis-based risk adjustment systems and health self-report to predict short- and long-term mortality. Data were obtained from the Department of Veterans Affairs (VA) administrative databases. The study population was 78,164 VA beneficiaries at eight medical centers during fiscal year (FY) 1998, 35,337 of whom completed an 36-Item Short Form Health Survey for veterans (SF-36V) survey. We tested the ability of Diagnostic Cost Groups (DCGs), Adjusted Clinical Groups (ACGs), SF-36V Physical Component score (PCS) and Mental Component Score (MCS), and eight SF-36V scales to predict 1- and 2-5 year all-cause mortality. The additional predictive value of adding PCS and MCS to ACGs and DCGs was also evaluated. Logistic regression models were compared using Akaike's information criterion, the c-statistic, and the Hosmer-Lemeshow test. The c-statistics for the eight scales combined with age and gender were 0.766 for 1-year mortality and 0.771 for 2-5-year mortality. For DCGs with age and gender the c-statistics for 1- and 2-5-year mortality were 0.778 and 0.771, respectively. Adding PCS and MCS to the DCG model increased the c-statistics to 0.798 for 1-year and 0.784 for 2-5-year mortality. The DCG model showed slightly better performance than the eight-scale model in predicting 1-year mortality, but the two models showed similar performance for 2-5-year mortality. Health self-report may add health risk information in addition to age, gender, and diagnosis for predicting longer-term mortality.

Comparing Self-Reported Health Status and Diagnosis-Based Risk Adjustment to Predict 1- and 2 to 5-Year Mortality

PubMed Central

Pietz, Kenneth; Petersen, Laura A

2007-01-01

Objectives To compare the ability of two diagnosis-based risk adjustment systems and health self-report to predict short- and long-term mortality. Data Sources/Study Setting Data were obtained from the Department of Veterans Affairs (VA) administrative databases. The study population was 78,164 VA beneficiaries at eight medical centers during fiscal year (FY) 1998, 35,337 of whom completed an 36-Item Short Form Health Survey for veterans (SF-36V) survey. Study Design We tested the ability of Diagnostic Cost Groups (DCGs), Adjusted Clinical Groups (ACGs), SF-36V Physical Component score (PCS) and Mental Component Score (MCS), and eight SF-36V scales to predict 1- and 2–5 year all-cause mortality. The additional predictive value of adding PCS and MCS to ACGs and DCGs was also evaluated. Logistic regression models were compared using Akaike's information criterion, the c-statistic, and the Hosmer–Lemeshow test. Principal Findings The c-statistics for the eight scales combined with age and gender were 0.766 for 1-year mortality and 0.771 for 2–5-year mortality. For DCGs with age and gender the c-statistics for 1- and 2–5-year mortality were 0.778 and 0.771, respectively. Adding PCS and MCS to the DCG model increased the c-statistics to 0.798 for 1-year and 0.784 for 2–5-year mortality. Conclusions The DCG model showed slightly better performance than the eight-scale model in predicting 1-year mortality, but the two models showed similar performance for 2–5-year mortality. Health self-report may add health risk information in addition to age, gender, and diagnosis for predicting longer-term mortality. PMID:17362210

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

Predictive value of hippocampal MR imaging-based high-dimensional mapping in mesial temporal epilepsy: preliminary findings.

PubMed

Hogan, R E; Wang, L; Bertrand, M E; Willmore, L J; Bucholz, R D; Nassif, A S; Csernansky, J G

2006-01-01

We objectively assessed surface structural changes of the hippocampus in mesial temporal sclerosis (MTS) and assessed the ability of large-deformation high-dimensional mapping (HDM-LD) to demonstrate hippocampal surface symmetry and predict group classification of MTS in right and left MTS groups compared with control subjects. Using eigenvector field analysis of HDM-LD segmentations of the hippocampus, we compared the symmetry of changes in the right and left MTS groups with a group of 15 matched controls. To assess the ability of HDM-LD to predict group classification, eigenvectors were selected by a logistic regression procedure when comparing the MTS group with control subjects. Multivariate analysis of variance on the coefficients from the first 9 eigenvectors accounted for 75% of the total variance between groups. The first 3 eigenvectors showed the largest differences between the control group and each of the MTS groups, but with eigenvector 2 showing the greatest difference in the MTS groups. Reconstruction of the hippocampal deformation vector fields due solely to eigenvector 2 shows symmetrical patterns in the right and left MTS groups. A "leave-one-out" (jackknife) procedure correctly predicted group classification in 14 of 15 (93.3%) left MTS subjects and all 15 right MTS subjects. Analysis of principal dimensions of hippocampal shape change suggests that MTS, after accounting for normal right-left asymmetries, affects the right and left hippocampal surface structure very symmetrically. Preliminary analysis using HDM-LD shows it can predict group classification of MTS and control hippocampi in this well-defined population of patients with MTS and mesial temporal lobe epilepsy (MTLE).

Accuracy of Genomic Prediction for Foliar Terpene Traits in Eucalyptus polybractea.

PubMed

Kainer, David; Stone, Eric A; Padovan, Amanda; Foley, William J; Külheim, Carsten

2018-06-11

Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea , a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species. Copyright © 2018, G3: Genes, Genomes, Genetics.

The Predicted Cross Value for Genetic Introgression of Multiple Alleles

PubMed Central

Han, Ye; Cameron, John N.; Wang, Lizhi; Beavis, William D.

2017-01-01

We consider the plant genetic improvement challenge of introgressing multiple alleles from a homozygous donor to a recipient. First, we frame the project as an algorithmic process that can be mathematically formulated. We then introduce a novel metric for selecting breeding parents that we refer to as the predicted cross value (PCV). Unlike estimated breeding values, which represent predictions of general combining ability, the PCV predicts specific combining ability. The PCV takes estimates of recombination frequencies as an input vector and calculates the probability that a pair of parents will produce a gamete with desirable alleles at all specified loci. We compared the PCV approach with existing estimated-breeding-value approaches in two simulation experiments, in which 7 and 20 desirable alleles were to be introgressed from a donor line into a recipient line. Results suggest that the PCV is more efficient and effective for multi-allelic trait introgression. We also discuss how operations research can be used for other crop genetic improvement projects and suggest several future research directions. PMID:28122824

Strategies to predict rheumatoid arthritis development in at-risk populations

PubMed Central

van der Helm-van Mil, Annette H.

2016-01-01

The development of RA is conceived as a multiple hit process and the more hits that are acquired, the greater the risk of developing clinically apparent RA. Several at-risk phases have been described, including the presence of genetic and environmental factors, RA-related autoantibodies and biomarkers and symptoms. Intervention in these preclinical phases may be more effective compared with intervention in the clinical phase. One prerequisite for preventive strategies is the ability to estimate an individual’s risk adequately. This review evaluates the ability to predict the risk of RA in the various preclinical stages. Present data suggest that a combination of genetic and environmental factors is helpful to identify persons at high risk of RA among first-degree relatives. Furthermore, a combination of symptoms, antibody characteristics and environmental factors has been shown to be relevant for risk prediction in seropositive arthralgia patients. Large prospective studies are needed to validate and improve risk prediction in preclinical disease stages. PMID:25096602

Modeling and optimization of reductive degradation of chloramphenicol in aqueous solution by zero-valent bimetallic nanoparticles.

PubMed

Singh, Kunwar P; Singh, Arun K; Gupta, Shikha; Rai, Premanjali

2012-07-01

The present study aims to investigate the individual and combined effects of temperature, pH, zero-valent bimetallic nanoparticles (ZVBMNPs) dose, and chloramphenicol (CP) concentration on the reductive degradation of CP using ZVBMNPs in aqueous medium. Iron-silver ZVBMNPs were synthesized. Batch experimental data were generated using a four-factor statistical experimental design. CP reduction by ZVBMNPs was optimized using the response surface modeling (RSM) and artificial neural network-genetic algorithm (ANN-GA) approaches. The RSM and ANN methodologies were also compared for their predictive and generalization abilities using the same training and validation data set. Reductive by-products of CP were identified using liquid chromatography-mass spectrometry technique. The optimized process variables (RSM and ANN-GA approaches) yielded CP reduction capacity of 57.37 and 57.10 mg g(-1), respectively, as compared to the experimental value of 54.0 mg g(-1) with un-optimized variables. The ANN-GA and RSM methodologies yielded comparable results and helped to achieve a higher reduction (>6%) of CP by the ZVBMNPs as compared to the experimental value. The root mean squared error, relative standard error of prediction and correlation coefficient between the measured and model-predicted values of response variable were 1.34, 3.79, and 0.964 for RSM and 0.03, 0.07, and 0.999 for ANN models for the training and 1.39, 3.47, and 0.996 for RSM and 1.25, 3.11, and 0.990 for ANN models for the validation set. Predictive and generalization abilities of both the RSM and ANN models were comparable. The synthesized ZVBMNPs may be used for an efficient reductive removal of CP from the water.

Transonic Drag Prediction Using an Unstructured Multigrid Solver

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Levy, David W.

2001-01-01

This paper summarizes the results obtained with the NSU-3D unstructured multigrid solver for the AIAA Drag Prediction Workshop held in Anaheim, CA, June 2001. The test case for the workshop consists of a wing-body configuration at transonic flow conditions. Flow analyses for a complete test matrix of lift coefficient values and Mach numbers at a constant Reynolds number are performed, thus producing a set of drag polars and drag rise curves which are compared with experimental data. Results were obtained independently by both authors using an identical baseline grid and different refined grids. Most cases were run in parallel on commodity cluster-type machines while the largest cases were run on an SGI Origin machine using 128 processors. The objective of this paper is to study the accuracy of the subject unstructured grid solver for predicting drag in the transonic cruise regime, to assess the efficiency of the method in terms of convergence, cpu time, and memory, and to determine the effects of grid resolution on this predictive ability and its computational efficiency. A good predictive ability is demonstrated over a wide range of conditions, although accuracy was found to degrade for cases at higher Mach numbers and lift values where increasing amounts of flow separation occur. The ability to rapidly compute large numbers of cases at varying flow conditions using an unstructured solver on inexpensive clusters of commodity computers is also demonstrated.

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

PubMed

Crow, Rebecca S; Lohman, Matthew C; Pidgeon, Dawna; Bruce, Martha L; Bartels, Stephen J; Batsis, John A

2018-03-01

To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools. Analysis of cross-sectional and longitudinal data from NHATS. National Health and Aging Trend Study (NHATS) 2011-2015. Individuals aged 65 and older (N = 7,392). Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaustion, weight loss, low activity, slow gait speed, and weak grip strength. Robust was defined as meeting 0 criteria, prefrailty as 1 or 2 criteria, and frailty as 3 or more criteria. Falls were self-reported and ascertained using NHATS subsequent rounds (2012-2015). We compared the ability of frailty to predict future falls with that of STEADI score, adjusting for age, race, sex, education, comorbidities, hearing and vision impairment, and disability. Of the 7,392 participants (58.5% female), there 3,545 (48.0%) were classified as being at low risk of falling, 2,966 (40.1%) as being at moderate risk, and 881 (11.9%) as being at high risk. The adjusted risk of falling over the 4 subsequent years was 2.5 times as great for the moderate-risk group (hazard ratio (HR) = 2.50, 95% confidence interval (CI) = 2.16-2.89) and almost 4 times as great (HR = 3.79, 95% CI = 2.76-5.21) for the high-risk group as for the low-risk group. Risk of falling was greater for those who were prefrail (HR = 1.34, 95% CI 1.16-1.55) and frail (HR = 1.20, 95% CI = 0.94-1.54) than for those who were robust. STEADI score is a strong predictor of future falls. Addition of frailty status does not improve the ability of the STEADI measure to predict future falls. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

Student assessment by objective structured examination in a neurology clerkship

PubMed Central

Adesoye, Taiwo; Smith, Sandy; Blood, Angela; Brorson, James R.

2012-01-01

Objectives: We evaluated the reliability and predictive ability of an objective structured clinical examination (OSCE) in the assessment of medical students at the completion of a neurology clerkship. Methods: We analyzed data from 195 third-year medical students who took the OSCE. For each student, the OSCE consisted of 2 standardized patient encounters. The scores obtained from each encounter were compared. Faculty clinical evaluations of each student for 2 clinical inpatient rotations were also compared. Hierarchical regression analysis was applied to test the ability of the averaged OSCE scores to predict standardized written examination scores and composite clinical scores. Results: Students' OSCE scores from the 2 standardized patient encounters were significantly correlated with each other (r = 0.347, p < 0.001), and the scores for all students were normally distributed. In contrast, students' faculty clinical evaluation scores from 2 different clinical inpatient rotations were uncorrelated, and scores were skewed toward the highest ratings. After accounting for clerkship order, better OSCE scores were predictive of better National Board of Medical Examiners standardized examination scores (R2Δ = 0.131, p < 0.001) and of better faculty clinical scores (R2Δ = 0.078, p < 0.001). Conclusions: Student assessment by an OSCE provides a reliable and predictive objective assessment of clinical performance in a neurology clerkship. PMID:22855865

GUMICS-4 Year Run: Ground Magnetic Field Predictions

NASA Astrophysics Data System (ADS)

Honkonen, I. J.; Viljanen, A.; Juusola, L.; Facsko, G.; Vanhamäki, H.

2013-12-01

Space weather can have severe effects even at ground level when Geomagnetically Induced Currents (GIC) disrupt power transmission networks, the worst case being a complete blackout affecting millions of people. The importance of space weather forecasting as well as the need for model improvement and validation has been recognized internationally. The recently concluded GUMICS-4 one year run, in which solar wind observations obtained from OMNIWeb for the period 2002-01-29 to 2003-02-02 were given as input to the model, will allow GUMICS to be validated against observations on an unprecedented scale. The performance of GUMICS can be quantified statistically, as a function of, for example, the solar wind driver, various geomagnetic indices, magnetic local time and other parameters. Here we concentrate on the ability of GUMICS to predict ground magnetic field observations for one year of simulated results. The ground magnetic field predictions are compared to observations of the mainland IMAGE magnetometer stations located at CGM latitudes 54-68 N. Furthermore the GIC derived from ground magnetic field predictions are compared to observations along the natural gas pipeline at Mäntsälä, South Finland. Various metrics are used to objectively evaluate the performance of GUMICS as a function of different parameters, thereby providing significant insight into the space weather forecasting ability of models based on first principles.

Comprehensive and critical review of the predictive properties of the various mass models

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

Haustein, P.E.

1984-01-01

Since the publication of the 1975 Mass Predictions approximately 300 new atomic masses have been reported. These data come from a variety of experimental studies using diverse techniques and they span a mass range from the lightest isotopes to the very heaviest. It is instructive to compare these data with the 1975 predictions and several others (Moeller and Nix, Monahan, Serduke, Uno and Yamada which appeared latter. Extensive numerical and graphical analyses have been performed to examine the quality of the mass predictions from the various models and to identify features in these models that require correction. In general, theremore » is only rough correlation between the ability of a particular model to reproduce the measured mass surface which had been used to refine its adjustable parameters and that model's ability to predict correctly the new masses. For some models distinct systematic features appear when the new mass data are plotted as functions of relevant physical variables. Global intercomparisons of all the models are made first, followed by several examples of types of analysis performed with individual mass models.« less

Static and transient performance prediction for CFB boilers using a Bayesian-Gaussian Neural Network

NASA Astrophysics Data System (ADS)

Ye, Haiwen; Ni, Weidou

1997-06-01

A Bayesian-Gaussian Neural Network (BGNN) is put forward in this paper to predict the static and transient performance of Circulating Fluidized Bed (CFB) boilers. The advantages of this network over Back-Propagation Neural Networks (BPNNs), easier determination of topology, simpler and time saving in training process as well as self-organizing ability, make this network more practical in on-line performance prediction for complicated processes. Simulation shows that this network is comparable to the BPNNs in predicting the performance of CFB boilers. Good and practical on-line performance predictions are essential for operation guide and model predictive control of CFB boilers, which are under research by the authors.

Self-esteem, shyness, and sociability in adolescents with specific language impairment (SLI).

PubMed

Wadman, Ruth; Durkin, Kevin; Conti-Ramsden, Gina

2008-08-01

To determine if lower global self-esteem, shyness, and low sociability are outcomes associated with SLI in adolescence. Possible concurrent predictive relationships and gender differences were also examined. Fifty-four adolescents with SLI, aged between 16 and 17 years, were compared with a group of 54 adolescents with typical language abilities on the Rosenberg Self-Esteem scale (Rosenberg, 1965) and the Cheek and Buss Shyness and Sociability scales (Cheek & Buss, 1981). The SLI group had significantly lower global self-esteem scores than the group with typical language abilities. The adolescents with SLI were more shy than their peers, but the groups did not differ in their sociability ratings. Regression analysis found that language ability was not concurrently predictive of self-esteem but shyness was. Mediation analysis suggested that shyness could be a partial but significant mediator in the relationship between language ability and global self-esteem. Older adolescents with SLI are at risk of lower global self-esteem and experience shyness, although they want to interact socially. The relationship between language ability and self-esteem at this point in adolescence is complex, with shyness potentially playing an important mediating role.

Creativity, visualization abilities, and visual cognitive style.

PubMed

Kozhevnikov, Maria; Kozhevnikov, Michael; Yu, Chen Jiao; Blazhenkova, Olesya

2013-06-01

Despite the recent evidence for a multi-component nature of both visual imagery and creativity, there have been no systematic studies on how the different dimensions of creativity and imagery might interrelate. The main goal of this study was to investigate the relationship between different dimensions of creativity (artistic and scientific) and dimensions of visualization abilities and styles (object and spatial). In addition, we compared the contributions of object and spatial visualization abilities versus corresponding styles to scientific and artistic dimensions of creativity. Twenty-four undergraduate students (12 females) were recruited for the first study, and 75 additional participants (36 females) were recruited for an additional experiment. Participants were administered a number of object and spatial visualization abilities and style assessments as well as a number of artistic and scientific creativity tests. The results show that object visualization relates to artistic creativity and spatial visualization relates to scientific creativity, while both are distinct from verbal creativity. Furthermore, our findings demonstrate that style predicts corresponding dimension of creativity even after removing shared variance between style and visualization ability. The results suggest that styles might be a more ecologically valid construct in predicting real-life creative behaviour, such as performance in different professional domains. © 2013 The British Psychological Society.

Survival of the Friendliest: Homo sapiens Evolved via Selection for Prosociality.

PubMed

Hare, Brian

2017-01-03

The challenge of studying human cognitive evolution is identifying unique features of our intelligence while explaining the processes by which they arose. Comparisons with nonhuman apes point to our early-emerging cooperative-communicative abilities as crucial to the evolution of all forms of human cultural cognition, including language. The human self-domestication hypothesis proposes that these early-emerging social skills evolved when natural selection favored increased in-group prosociality over aggression in late human evolution. As a by-product of this selection, humans are predicted to show traits of the domestication syndrome observed in other domestic animals. In reviewing comparative, developmental, neurobiological, and paleoanthropological research, compelling evidence emerges for the predicted relationship between unique human mentalizing abilities, tolerance, and the domestication syndrome in humans. This synthesis includes a review of the first a priori test of the self-domestication hypothesis as well as predictions for future tests.

A-Priori Tuning of Modified Magnussen Combustion Model

NASA Technical Reports Server (NTRS)

Norris, A. T.

2016-01-01

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for that particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor simulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for simulations.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Comparison between a Weibull proportional hazards model and a linear model for predicting the genetic merit of US Jersey sires for daughter longevity.

PubMed

Caraviello, D Z; Weigel, K A; Gianola, D

2004-05-01

Predicted transmitting abilities (PTA) of US Jersey sires for daughter longevity were calculated using a Weibull proportional hazards sire model and compared with predictions from a conventional linear animal model. Culling data from 268,008 Jersey cows with first calving from 1981 to 2000 were used. The proportional hazards model included time-dependent effects of herd-year-season contemporary group and parity by stage of lactation interaction, as well as time-independent effects of sire and age at first calving. Sire variances and parameters of the Weibull distribution were estimated, providing heritability estimates of 4.7% on the log scale and 18.0% on the original scale. The PTA of each sire was expressed as the expected risk of culling relative to daughters of an average sire. Risk ratios (RR) ranged from 0.7 to 1.3, indicating that the risk of culling for daughters of the best sires was 30% lower than for daughters of average sires and nearly 50% lower than than for daughters of the poorest sires. Sire PTA from the proportional hazards model were compared with PTA from a linear model similar to that used for routine national genetic evaluation of length of productive life (PL) using cross-validation in independent samples of herds. Models were compared using logistic regression of daughters' stayability to second, third, fourth, or fifth lactation on their sires' PTA values, with alternative approaches for weighting the contribution of each sire. Models were also compared using logistic regression of daughters' stayability to 36, 48, 60, 72, and 84 mo of life. The proportional hazards model generally yielded more accurate predictions according to these criteria, but differences in predictive ability between methods were smaller when using a Kullback-Leibler distance than with other approaches. Results of this study suggest that survival analysis methodology may provide more accurate predictions of genetic merit for longevity than conventional linear models.

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues

PubMed Central

Perišić, Ognjen

2018-01-01

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM’s weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol’s ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner’s interacting scaffold is more flexible and adaptable. PMID:29547506

A study of the effectiveness of ergonomically-based functional screening tests and their relationship to reducing worker compensation injuries.

PubMed

Anderson, Charles; Briggs, Jim

2008-01-01

This paper summarizes a series of studies of the effectiveness of ergonomically based functional screening tests for post offer pre-placement of applicants for physically demanding jobs, and their relationship to reducing worker compensation injuries. Three predictive validation studies and a meta-analysis of injury rates pre- and post-implementation of physical ability testing at 175 locations are included. The strength and energy expenditure demands of physically-strenuous warehouse jobs in three industries were documented through ergonomic analysis. A battery of strength and endurance tests were developed to assess applicants' abilities to meet the measured physical demands. Predictive validation studies were performed for the jobs in each of the three industries. In each study, new-hires were given the physical ability test battery and then placed on the job. Management was not informed of the results of the tests. Injury experience and work history were then monitored over a two year period in each study. Injury rates and retention were then compared for individuals who passed and individuals who failed the battery. As the battery was implemented in other locations, the injury rate for individuals starting employment in the year prior to implementation was compared to the injury rate for individuals starting employment in the year after implementation. A meta-analysis of the three predictive validation studies indicated that new-hires who passed the battery had a 47% lower worker compensation injury rate and 21% higher retention. A meta-analysis of the 175 pre/post-implementation studies indicated a 41% reduction in worker compensation injuries associated with implementation of ergonomically based physical ability tests.

To Switch or Not to Switch: Role of Cognitive Control in Working Memory Training in Older Adults.

PubMed

Basak, Chandramallika; O'Connell, Margaret A

2016-01-01

It is currently not known what are the best working memory training strategies to offset the age-related declines in fluid cognitive abilities. In this randomized clinical double-blind trial, older adults were randomly assigned to one of two types of working memory training - one group was trained on a predictable memory updating task (PT) and another group was trained on a novel, unpredictable memory updating task (UT). Unpredictable memory updating, compared to predictable, requires greater demands on cognitive control (Basak and Verhaeghen, 2011a). Therefore, the current study allowed us to evaluate the role of cognitive control in working memory training. All participants were assessed on a set of near and far transfer tasks at three different testing sessions - before training, immediately after the training, and 1.5 months after completing the training. Additionally, individual learning rates for a comparison working memory task (performed by both groups) and the trained task were computed. Training on unpredictable memory updating, compared to predictable, significantly enhanced performance on a measure of episodic memory, immediately after the training. Moreover, individuals with faster learning rates showed greater gains in this episodic memory task and another new working memory task; this effect was specific to UT. We propose that the unpredictable memory updating training, compared to predictable memory updating training, may a better strategy to improve selective cognitive abilities in older adults, and future studies could further investigate the role of cognitive control in working memory training.

[Analyzing the Wechsler Intelligence Scale for Children-Revised (WISC-R) in Children With Attention Deficit and Hyperactivity Disorder: Predictive Value of Subtests, Kaufman, and Bannatyne Categories].

PubMed

Tural Hesapçıoğlu, Selma; Çelik, Cihat; Özmen, Sevim; Yiğit, İbrahim

2016-01-01

The aim of this study is to evaluate the predictive value of intelligence quotients scores (IQs), subtests of Wechsler Intelligence Scale for Children-Revised (WISC-R) and Kaufman's and Bannatyne's categories scores which are the sums of subtests of WISC-R in attention deficit hyperactivity disorder (ADHD). Another aim is to examine the difference of some neurocognitive skills between the children with ADHD and their unaffected peers by WISC-R subtests. WISC-R's subtest and IQ scores, and scores of Kaufman's and Bannatyne's categories of the children who were diagnosed with only ADHD were compared with the same scores of the children who were in healthy control group (N= 111) and were in ADHD with co morbidity group (N= 82). It was found that the subtest scores (vocabulary, comprehension, digit span, picture completion and block design) of the children with only ADHD and ADHD with comorbidity were significantly lower than healthy group. It was observed that subtests of comprehension (Wald= 5.47, df= 1, p=0.05), digit span (Wald= 16.79, df= 1, p=0.001) and picture completion (Wald= 5.25, df= 1, p=0.05) predicted significantly ADHD. In addition, the categories of freedom from distractibility (Wald= 8.22, df= 1, p=0.01) and spatial abilities (Wald= 12.22, df= 1, p<0.0001) were predictive for ADHD in this study. Problem solving abilities in social processes, auditory short-term memories, visual-spatial abilities and visual configuration abilities of the children with ADHD was observed to be lower than their healthy peers. It was thought that in WISC-R's profile analysis, the categories of freedom from distractibility and spatial abilities can be distinctive in ADHD diagnose.

Doing many things at a time: Lack of power decreases the ability to multitask.

PubMed

Cai, Ran Alice; Guinote, Ana

2017-09-01

Three studies investigated the effects of power on the ability to pursue multiple, concomitant goals, also known as multitasking. It was predicted that powerless participants will show lower multitasking ability than control and powerful participants. Study 1 focused on self-reported ability to multitask in a sample of executives and subordinate employees. Studies 2 and 3 investigated the ability to dual-task and to switch between tasks, respectively, using dual-task and task-switching paradigms. Across the studies, powerless individuals were less able to effectively multitask compared with control and powerful participants, suggesting that the detrimental effects of lack of power extend beyond single-task environments, shown in past research, into multitasking environments. Underlying mechanisms are discussed. © 2017 The British Psychological Society.

A Comparative Investigation of TPB and Altruism Frameworks for an Empirically Based Communication Approach to Enhance Paper Recycling

ERIC Educational Resources Information Center

Chaisamrej, Rungrat; Zimmerman, Rick S.

2014-01-01

This research compared the ability of the theory of planned behavior (TPB) and the altruism framework (AM) to predict paper-recycling behavior. It was comprised of formative research and a major survey. Data collected from 628 undergraduate students in Thailand were analyzed using structural equation modeling. Results showed that TPB was superior…

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

PubMed

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

"As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players.

PubMed

Gray, Rob; Beilock, Sun L; Carr, Thomas H

2007-08-01

A virtual-reality batting task compared novice and expert baseball players' ability to predict the outcomes of their swings as well as the susceptibility of these outcome predictions to hindsight bias--a measure of strength and resistance to distortion of memory for predicted action outcomes. During each swing the simulation stopped when the bat met the ball. Batters marked where on the field they thought the ball would land. Correct feedback was then displayed, after which batters attempted to remark the location they had indicated prior to feedback. Expert batters were more accurate than less-skilled individuals in the initial marking and showed less hindsight bias in the postfeedback marking. Furthermore, experts' number of hits in the previous block of trials was positively correlated with prediction accuracy and negatively correlated with hindsight bias. The reverse was true for novices. Thus the ability to predict the outcome of one's performance before such information is available in the environment is not only based on one's overall skill level, but how one is performing at a given moment.

Modelling Thin Film Microbending: A Comparative Study of Three Different Approaches

NASA Astrophysics Data System (ADS)

Aifantis, Katerina E.; Nikitas, Nikos; Zaiser, Michael

2011-09-01

Constitutive models which describe crystal microplasticity in a continuum framework can be envisaged as average representations of the dynamics of dislocation systems. Thus, their performance needs to be assessed not only by their ability to correctly represent stress-strain characteristics on the specimen scale but also by their ability to correctly represent the evolution of internal stress and strain patterns. In the present comparative study we consider the bending of a free-standing thin film. We compare the results of 3D DDD simulations with those obtained from a simple 1D gradient plasticity model and a more complex dislocation-based continuum model. Both models correctly reproduce the nontrivial strain patterns predicted by DDD for the microbending problem.

Comparison of Physician-Predicted to Measured Low Vision Outcomes

PubMed Central

Chan, Tiffany L.; Goldstein, Judith E.; Massof, Robert W.

2013-01-01

Purpose To compare low vision rehabilitation (LVR) physicians’ predictions of the probability of success of LVR to patients’ self-reported outcomes after provision of usual outpatient LVR services; and to determine if patients’ traits influence physician ratings. Methods The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre and post-LVR to 316 low vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression and cognitive status. Following patient evaluation, 38 LVR physicians estimated the probability of outcome success (POS), using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients’ baseline traits on predicted outcomes. Results A regression analysis with a hierarchical random effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, Kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed effects regression models show that POS ratings are associated with information about the patient’s cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. Conclusions Physicians’ predictions of LVR outcomes appear to be influenced by knowledge of patients’ cognitive functioning and the combination of visual acuity and functional ability - information physicians acquire from the patient’s history and examination. However, physicians’ predictions do not agree with observed changes in functional ability from the patient’s perspective; they are no better than chance. PMID:23873036

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses.

PubMed

Einarsson, E; Eythórsdóttir, E; Smith, C R; Jónmundsson, J V

2014-07-01

A total of 862 lamb carcasses that were evaluated by both the VIAscan® and the current EUROP classification system were deboned and the actual yield was measured. Models were derived for predicting lean meat yield of the legs (Leg%), loin (Loin%) and shoulder (Shldr%) using the best VIAscan® variables selected by stepwise regression analysis of a calibration data set (n=603). The equations were tested on validation data set (n=259). The results showed that the VIAscan® predicted lean meat yield in the leg, loin and shoulder with an R 2 of 0.60, 0.31 and 0.47, respectively, whereas the current EUROP system predicted lean yield with an R 2 of 0.57, 0.32 and 0.37, respectively, for the three carcass parts. The VIAscan® also predicted the EUROP score of the trial carcasses, using a model derived from an earlier trial. The EUROP classification from VIAscan® and the current system were compared for their ability to explain the variation in lean yield of the whole carcass (LMY%) and trimmed fat (FAT%). The predicted EUROP scores from the VIAscan® explained 36% of the variation in LMY% and 60% of the variation in FAT%, compared with the current EUROP system that explained 49% and 72%, respectively. The EUROP classification obtained by the VIAscan® was tested against a panel of three expert classifiers (n=696). The VIAscan® classification agreed with 82% of conformation and 73% of the fat classes assigned by a panel of expert classifiers. It was concluded that VIAscan® provides a technology that can directly predict LMY% of lamb carcasses with more accuracy than the current EUROP classification system. The VIAscan® is also capable of classifying lamb carcasses into EUROP classes with an accuracy that fulfils minimum demands for the Icelandic sheep industry. Although the VIAscan® prediction of the Loin% is low, it is comparable to the current EUROP system, and should not hinder the adoption of the technology to estimate the yield of Icelandic lambs as it delivered a more accurate prediction for the Leg%, Shldr% and overall LMY% with negligible prediction bias.

Quantification of hazard prediction ability at hazard prediction training (Kiken-Yochi Training: KYT) by free-response receiver-operating characteristic (FROC) analysis.

PubMed

Hashida, Masahiro; Kamezaki, Ryousuke; Goto, Makoto; Shiraishi, Junji

2017-03-01

The ability to predict hazards in possible situations in a general X-ray examination room created for Kiken-Yochi training (KYT) is quantified by use of free-response receiver-operating characteristics (FROC) analysis for determining whether the total number of years of clinical experience, involvement in general X-ray examinations, occupation, and training each have an impact on the hazard prediction ability. Twenty-three radiological technologists (RTs) (years of experience: 2-28), four nurses (years of experience: 15-19), and six RT students observed 53 scenes of KYT: 26 scenes with hazardous points (hazardous points are those that might cause injury to patients) and 27 scenes without points. Based on the results of these observations, we calculated the alternative free-response receiver-operating characteristic (AFROC) curve and the figure of merit (FOM) to quantify the hazard prediction ability. The results showed that the total number of years of clinical experience did not have any impact on hazard prediction ability, whereas recent experience with general X-ray examinations greatly influenced this ability. In addition, the hazard prediction ability varied depending on the occupations of the observers while they were observing the same scenes in KYT. The hazard prediction ability of the radiologic technology students was improved after they had undergone patient safety training. This proposed method with FROC observer study enabled the quantification and evaluation of the hazard prediction capability, and the application of this approach to clinical practice may help to ensure the safety of examinations and treatment in the radiology department.

Reading Comprehension in Children with ADHD: Cognitive Underpinnings of the Centrality Deficit

PubMed Central

Miller, Amanda C.; Keenan, Janice M.; Betjemann, Rebecca S.; Willcutt, Erik; Pennington, Bruce F.; Olson, Richard K.

2012-01-01

We examined reading comprehension in children with ADHD by assessing their ability to build a coherent mental representation that allows them to recall central and peripheral information. We compared children with ADHD (mean age 9.78) to word reading-matched controls (mean age 9.89) on their ability to retell a passage. We found that even though children with ADHD recalled more central than peripheral information, they showed their greatest deficit, relative to controls, on central information – a centrality deficit (Miller & Keenan, 2009). We explored the cognitive underpinnings of this deficit using regressions to compare how well cognitive factors (working memory, inhibition, processing speed, and IQ) predicted the ability to recall central information, after controlling for word reading ability, and whether these cognitive factors interacted with ADHD symptoms. Working memory accounted for the most unique variance. Although previous evidence for reading comprehension difficulties in children with ADHD have been mixed, this study suggests that even when word reading ability is controlled, children with ADHD have difficulty building a coherent mental representation, and this difficulty is likely related to deficits in working memory. PMID:23054132

Predicting functional ability in mild cognitive impairment with the Dementia Rating Scale-2.

PubMed

Greenaway, Melanie C; Duncan, Noah L; Hanna, Sherrie; Smith, Glenn E

2012-06-01

We examined the utility of cognitive evaluation to predict instrumental activities of daily living (IADLs) and decisional ability in Mild Cognitive Impairment (MCI). Sixty-seven individuals with single-domain amnestic MCI were administered the Dementia Rating Scale-2 (DRS-2) as well as the Everyday Cognition assessment form to assess functional ability. The DRS-2 Total Scores and Initiation/Perseveration and Memory subscales were found to be predictive of IADLs, with Total Scores accounting for 19% of the variance in IADL performance on average. In addition, the DRS-2 Initiation/Perseveration and Total Scores were predictive of ability to understand information, and the DRS-2 Conceptualization helped predict ability to communicate with others, both key variables in decision-making ability. These findings suggest that performance on the DRS-2, and specific subscales related to executive function and memory, is significantly related to IADLs in individuals with MCI. These cognitive measures are also associated with decision-making-related abilities in MCI.

Prediction model of sinoatrial node field potential using high order partial least squares.

PubMed

Feng, Yu; Cao, Hui; Zhang, Yanbin

2015-01-01

High order partial least squares (HOPLS) is a novel data processing method. It is highly suitable for building prediction model which has tensor input and output. The objective of this study is to build a prediction model of the relationship between sinoatrial node field potential and high glucose using HOPLS. The three sub-signals of the sinoatrial node field potential made up the model's input. The concentration and the actuation duration of high glucose made up the model's output. The results showed that on the premise of predicting two dimensional variables, HOPLS had the same predictive ability and a lower dispersion degree compared with partial least squares (PLS).

Affective forecasting in an orangutan: predicting the hedonic outcome of novel juice mixes.

PubMed

Sauciuc, Gabriela-Alina; Persson, Tomas; Bååth, Rasmus; Bobrowicz, Katarzyna; Osvath, Mathias

2016-11-01

Affective forecasting is an ability that allows the prediction of the hedonic outcome of never-before experienced situations, by mentally recombining elements of prior experiences into possible scenarios, and pre-experiencing what these might feel like. It has been hypothesised that this ability is uniquely human. For example, given prior experience with the ingredients, but in the absence of direct experience with the mixture, only humans are said to be able to predict that lemonade tastes better with sugar than without it. Non-human animals, on the other hand, are claimed to be confined to predicting-exclusively and inflexibly-the outcome of previously experienced situations. Relying on gustatory stimuli, we devised a non-verbal method for assessing affective forecasting and tested comparatively one Sumatran orangutan and ten human participants. Administered as binary choices, the test required the participants to mentally construct novel juice blends from familiar ingredients and to make hedonic predictions concerning the ensuing mixes. The orangutan's performance was within the range of that shown by the humans. Both species made consistent choices that reflected independently measured taste preferences for the stimuli. Statistical models fitted to the data confirmed the predictive accuracy of such a relationship. The orangutan, just like humans, thus seems to have been able to make hedonic predictions concerning never-before experienced events.

Fan Noise Prediction with Applications to Aircraft System Noise Assessment

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Envia, Edmane; Burley, Casey L.

2009-01-01

This paper describes an assessment of current fan noise prediction tools by comparing measured and predicted sideline acoustic levels from a benchmark fan noise wind tunnel test. Specifically, an empirical method and newly developed coupled computational approach are utilized to predict aft fan noise for a benchmark test configuration. Comparisons with sideline noise measurements are performed to assess the relative merits of the two approaches. The study identifies issues entailed in coupling the source and propagation codes, as well as provides insight into the capabilities of the tools in predicting the fan noise source and subsequent propagation and radiation. In contrast to the empirical method, the new coupled computational approach provides the ability to investigate acoustic near-field effects. The potential benefits/costs of these new methods are also compared with the existing capabilities in a current aircraft noise system prediction tool. The knowledge gained in this work provides a basis for improved fan source specification in overall aircraft system noise studies.

Theoretical investigation on the microstructure of triethylene glycol based deep eutectic solvents: COSMO-RS and TURBOMOLE prediction

NASA Astrophysics Data System (ADS)

Aissaoui, Tayeb; Benguerba, Yacine; AlNashef, Inas M.

2017-08-01

The in-silico combination mechanism of triethylene glycol based DESs has been studied. COSMO-RS and graphical user interface TmoleX software were used to predict the interaction mechanism of hydrogen bond donors (HBDs) with hydrogen bond acceptors (HBA) to form DESs. The predicted IR results were compared with the previously reported experimental FT-IR analysis for the same studied DESs. The sigma profiles for the HBD, HBAs and formed DESs were interpreted to identify qualitatively molecular properties like polarity or hydrogen bonding donor and acceptor abilities. The predicted physicochemical properties reported in this study were in good agreement with experimental ones.

Comparing basal area growth models, consistency of parameters, and accuracy of prediction

Treesearch

J.J. Colbert; Michael Schuckers; Desta Fekedulegn

2002-01-01

We fit alternative sigmoid growth models to sample tree basal area historical data derived from increment cores and disks taken at breast height. We examine and compare the estimated parameters for these models across a range of sample sites. Models are rated on consistency of parameters and on their ability to fit growth data from four sites that are located across a...

Predicting Gender-Role Attitudes in Adolescent Females: Ability, Agency, and Parental Factors.

ERIC Educational Resources Information Center

Ahrens, Julia A.; O'Brien, Karen M.

1996-01-01

Investigated the contribution of ability, agency, and parental factors to the prediction of gender-role attitudes of 409 adolescent females in a private, college-preparatory high school. Findings indicate that ability and agency were predictive of gender-role attitudes, whereas parental factors were not significant contributors. Recommendations…

Acceptance alone is a better predictor of psychopathology and well-being than emotional competence, emotion regulation and mindfulness.

PubMed

Kotsou, Ilios; Leys, Christophe; Fossion, Pierre

2018-01-15

Emotional competence, emotion regulation, mindfulness and acceptance have all been strongly associated to emotional disorders and psychological well-being in multiple studies. However little research has compared the unique predictive ability of these different constructs. We hypothesised that they will all share a large proportion of common variance and that when compared to the broader constructs emotional competence, emotion regulation and mindfulness, acceptance alone would predict a larger proportion of unique variance METHODS: 228 participants from a community sample completed anonymously measures of anxiety, depression, happiness, acceptance, mindfulness, emotional competence and emotion regulation. We then ran multiple regressions to assess and compare the predictive ability of these different constructs. For measures of psychological distress, the acceptance measure uniquely accounted for between 4 and 30 times the variance that the emotional competence, emotion regulation and mindfulness measures did. These results are based on cross-sectional designs and non-clinical samples, longitudinal and experimental studies as clinical samples may be useful in order to assess the potential protective power of acceptance over time. Another limitation is the use of self-report questionnaires. Results confirmed our hypothesis, supporting the research on the importance of acceptance as a central factor in the understanding of the onset and maintenance of emotional disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Predictive value of the DASH tool for predicting return to work of injured workers with musculoskeletal disorders of the upper extremity.

PubMed

Armijo-Olivo, Susan; Woodhouse, Linda J; Steenstra, Ivan A; Gross, Douglas P

2016-12-01

To determine whether the Disabilities of the Arm, Shoulder, and Hand (DASH) tool added to the predictive ability of established prognostic factors, including patient demographic and clinical outcomes, to predict return to work (RTW) in injured workers with musculoskeletal (MSK) disorders of the upper extremity. A retrospective cohort study using a population-based database from the Workers' Compensation Board of Alberta (WCB-Alberta) that focused on claimants with upper extremity injuries was used. Besides the DASH, potential predictors included demographic, occupational, clinical and health usage variables. Outcome was receipt of compensation benefits after 3 months. To identify RTW predictors, a purposeful logistic modelling strategy was used. A series of receiver operating curve analyses were performed to determine which model provided the best discriminative ability. The sample included 3036 claimants with upper extremity injuries. The final model for predicting RTW included the total DASH score in addition to other established predictors. The area under the curve for this model was 0.77, which is interpreted as fair discrimination. This model was statistically significantly different than the model of established predictors alone (p<0.001). When comparing the DASH total score versus DASH item 23, a non-significant difference was obtained between the models (p=0.34). The DASH tool together with other established predictors significantly helped predict RTW after 3 months in participants with upper extremity MSK disorders. An appealing result for clinicians and busy researchers is that DASH item 23 has equal predictive ability to the total DASH score. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

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.

Is Approximate Number Precision a Stable Predictor of Math Ability?

ERIC Educational Resources Information Center

Libertus, Melissa E.; Feigenson, Lisa; Halberda, Justin

2013-01-01

Previous research shows that children's ability to estimate numbers of items using their Approximate Number System (ANS) predicts later math ability. To more closely examine the predictive role of early ANS acuity on later abilities, we assessed the ANS acuity, math ability, and expressive vocabulary of preschoolers twice, six months apart. We…

Predicting Arithmetic Abilities: The Role of Preparatory Arithmetic Markers and Intelligence

ERIC Educational Resources Information Center

Stock, Pieter; Desoete, Annemie; Roeyers, Herbert

2009-01-01

Arithmetic abilities acquired in kindergarten are found to be strong predictors for later deficient arithmetic abilities. This longitudinal study (N = 684) was designed to examine if it was possible to predict the level of children's arithmetic abilities in first and second grade from their performance on preparatory arithmetic abilities in…

Spectrotemporal Modulation Sensitivity as a Predictor of Speech Intelligibility for Hearing-Impaired Listeners

PubMed Central

Bernstein, Joshua G.W.; Mehraei, Golbarg; Shamma, Shihab; Gallun, Frederick J.; Theodoroff, Sarah M.; Leek, Marjorie R.

2014-01-01

Background A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals. Purpose The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners. Research Design The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000measured using the notched-noise method at 500, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 10002 Hz frequency-modulation detection thresholds for 500, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study. Study Sample Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated. Data Collection and Analysis STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index. Results STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index. Conclusions Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of speech intelligibility than audiometric measures alone. These results suggest a significant likelihood of success for an STM-based model of speech intelligibility for HI listeners. PMID:23636210

Somatic symptoms: an important index in predicting the outcome of depression at six-month and two-year follow-up points among outpatients with major depressive disorder.

PubMed

Hung, Ching-I; Liu, Chia-Yih; Wang, Shuu-Jiun; Juang, Yeong-Yuh; Yang, Ching-Hui

2010-09-01

Few studies have simultaneously compared the ability of depression, anxiety, and somatic symptoms to predict the outcome of major depressive disorder (MDD). This study aimed to compare the MDD outcome predictive ability of depression, anxiety, and somatic severity at 6-month and 2-year follow-ups. One-hundred and thirty-five outpatients (men/women=34/101) with MDD were enrolled. Depression and anxiety were evaluated by the Hamilton Depression Rating Scale, Hospital Anxiety and Depression Scale, and depression subscale of the Depression and Somatic Symptoms Scale (DSSS). Somatic severity was evaluated by the somatic subscale of the DSSS. Subjects undergoing pharmacotherapy in the follow-up month were categorized into the treatment group; the others were categorized into the no-treatment group. Multiple linear regressions were used to identify the scales most powerful in predicting MDD outcome. Among the 135 subjects, 119 and 106 completed the 6-month and 2-year follow-ups, respectively. Somatic severity at baseline was correlated with the outcomes of the three scales at the two follow-ups. After controlling for demographic variables, somatic severity independently predicted most outcomes of the three scales at the two follow-ups in the no-treatment group and the cost of pharmacotherapy and DSSS score at the 6-month follow-up in the treatment group. Division of the subjects into treatment and no-treatment groups was not based on randomization and bias might have been introduced. Somatic severity was the most powerful index in predicting MDD outcome. Psychometric scales with appropriate somatic symptom items may be more accurate in predicting MDD outcome. 2010 Elsevier B.V. All rights reserved.

Serum Mac-2 binding protein glycosylation isomer predicts grade F4 liver fibrosis in patients with biliary atresia.

PubMed

Yamada, Naoya; Sanada, Yukihiro; Tashiro, Masahisa; Hirata, Yuta; Okada, Noriki; Ihara, Yoshiyuki; Urahashi, Taizen; Mizuta, Koichi

2017-02-01

Mac-2 Binding Protein Glycosylation Isomer (M2BPGi) is a novel fibrosis marker. We examined the ability of M2BPGi to predict liver fibrosis in patients with biliary atresia. Sixty-four patients who underwent living donor liver transplantation (LDLT) were included [median age, 1.1 years (range 0.4-16.0), male 16 patients (25.0 %)]. We examined M2BPGi levels in serum obtained the day before LDLT, and we compared the value of the preoperative M2BPGi levels with the histological evaluation of fibrosis using the METAVIR fibrosis score. Subsequently, we assessed the ability of M2BPGi levels to predict fibrosis. The median M2BPGi level in patients with BA was 6.02 (range, 0.36-20.0), and 0, 1, 1, 11, and 51 patients had METAVIR fibrosis scores of F0, F1, F2, F3, and F4, respectively. In patients with F4 fibrosis, the median M2BPGi level was 6.88 (quartile; 5.235, 12.10), significantly higher than that in patients with F3 fibrosis who had a median level of 2.42 (quartile; 1.93, 2.895, p < 0.01). Area under the curve analysis for the ability of M2BPGi level to predict grade fibrosis was 0.917, with a specificity and sensitivity of 0.923 and 0.941, respectively. In comparison with other fibrosis markers such as hyaluronic acid, procollagen-III-peptide, type IV collagen 7 s, and aspartate aminotransferase platelet ratio index, M2BPGi showed the strongest ability to predict grade F4 fibrosis. M2BPGi is a novel fibrosis marker for evaluating the status of the liver in patients with BA, especially when predicting grade F4 fibrosis.

Analytical and Experimental Vibration Analysis of a Faulty Gear System.

DTIC Science & Technology

1994-10-01

Wigner - Ville Distribution ( WVD ) was used to give a comprehensive comparison of the predicted and...experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD’s ability to...of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

PP087. Multicenter external validation and recalibration of a model for preconceptional prediction of recurrent early-onset preeclampsia.

PubMed

van Kuijk, Sander; Delahaije, Denise; Dirksen, Carmen; Scheepers, Hubertina C J; Spaanderman, Marc; Ganzevoort, W; Duvekot, Hans; Oudijk, M A; van Pampus, M G; Dadelszen, Peter von; Peeters, Louis L; Smiths, Luc

2013-04-01

In an earlier paper we reported on the development of a model aimed at the prediction of preeclampsia recurrence, based on variables obtained before the next pregnancy (fasting glucose, BMI, previous birth of a small-for-gestational-age infant, duration of the previous pregnancy, and the presence of hypertension). To externally validate and recalibrate the prediction model for the risk of recurrence of early-onset preeclampsia. We collected data about course and outcome of the next ongoing pregnancy in 229 women with a history of early-onset preeclampsia. Recurrence was defined as preeclampsia requiring delivery before 34 weeks. We computed risk of recurrence and assessed model performance. In addition, we constructed a table comparing sensitivity, specificity, and predictive values for different suggested risk-thresholds. Early-onset preeclampsia recurred in 6.6% of women. The model systematically underestimated recurrence risk. The model's discriminative ability was modest, the area under the receiver operating characteristic curve was 58.9% (95% CI: 45.1 - 72.7). Using relevant risk-thresholds, the model created groups that were only moderately different in terms of their average risk of recurrent preeclampsia (Table 1). Compared to an AUC of 65% in the development cohort, the discriminate ability of the model was diminished. It had inadequate performance to classify women into clinically relevant risk groups. Copyright © 2013. Published by Elsevier B.V.

Predicting student performance in sonographic scanning using spatial ability as an ability determinent of skill acquisition

NASA Astrophysics Data System (ADS)

Clem, Douglas Wayne

Spatial ability refers to an individual's capacity to visualize and mentally manipulate three dimensional objects. Since sonographers manually manipulate 2D and 3D sonographic images to generate multi-viewed, logical, sequential renderings of an anatomical structure, it can be assumed that spatial ability is central to the perception and interpretation of these medical images. Using Ackerman's theory of ability determinants of skilled performance as a conceptual framework, this study explored the relationship of spatial ability and learning sonographic scanning. Beginning first year sonography students from four different educational institutions were administered a spatial abilities test prior to their initial scanning lab coursework. The students' spatial test scores were compared with their scanning competency performance scores. A significant relationship between the students' spatial ability scores and their scanning performance scores was found. This result suggests that the use of spatial ability tests for admission to sonography programs may improve candidate selection, as well as assist programs in adjusting instruction and curriculum for students who demonstrate low spatial ability.

Predictors of occupational burnout among nurses: a dominance analysis of job stressors.

PubMed

Sun, Ji-Wei; Bai, Hua-Yu; Li, Jia-Huan; Lin, Ping-Zhen; Zhang, Hui-Hui; Cao, Feng-Lin

2017-12-01

To quantitatively compare dimensions of job stressors' effects on nurses' burnout. Nurses, a key group of health service providers, often experience stressors at work. Extensive research has examined the relationship between job stressors and burnout; however, less has specifically compared the effects of job stressor domains on nurses' burnout. A quantitative cross-sectional survey examined three general hospitals in Jinan, China. Participants were 602 nurses. We compared five potential stressors' ability to predict nurses' burnout using dominance analysis and assuming that each stressor was intercorrelated. Strong positive correlations were found between all five job stressors and burnout. Interpersonal relationships and management issues most strongly predicted participants' burnout (11·3% of average variance). Job stressors, and particularly interpersonal relationships and management issues, significantly predict nurses' job burnout. Understanding the relative effect of job stressors may help identify fruitful areas for intervention and improve nurse recruitment and retention. © 2017 John Wiley & Sons Ltd.

An investigation of immune system disorder as a "marker" for anomalous dominance.

PubMed

Rich, D A; McKeever, W F

1990-01-01

Geschwind and Galaburda (1987) proposed that immune disorder (ID) susceptibility, along with left handedness and familial sinistrality (FS), is a "marker" for anomalous dominance. The theory predicts lesser left lateralization for language processes, lessened left hemisphere abilities, and enhanced right hemisphere abilities. We assessed language laterality (dichotic consonant vowel task) and performances on spatial and verbal tasks. Subjects were 128 college students. The factors of handedness, sex, FS, and immune disorder history (negative or positive) were perfectly counterbalanced. Left-handers were significantly less lateralized for language and scored lower than right-handers on the spatial tasks. Females scored lower on mental rotation than males, but performed comparably to males on the spatial relations task. The only effect of ID was by way of interaction with FS on both spatial tasks--subjects who were either negative or positive on both FS and ID status factors scored significantly higher than subjects negative for one but positive for the other factor. A speculative explanatory model for this interaction was proposed. The model incorporates the notion that FS and ID factors are comparably correlated, but in opposite directions, with hormonal factors implicated by other research as relevant for spatial ability differences. Finally, no support for the "anomalous dominance" hypothesis predictions was found.

Predictive Factors for Visual Field Conversion: Comparison of Scanning Laser Polarimetry and Optical Coherence Tomography.

PubMed

Diekmann, Theresa; Schrems-Hoesl, Laura M; Mardin, Christian Y; Laemmer, Robert; Horn, Folkert K; Kruse, Friedrich E; Schrems, Wolfgang A

2018-02-01

The purpose of this study was to compare the ability of scanning laser polarimetry (SLP) and spectral-domain optical coherence tomography (SD-OCT) to predict future visual field conversion of subjects with ocular hypertension and early glaucoma. All patients were recruited from the Erlangen glaucoma registry and examined using standard automated perimetry, 24-hour intraocular pressure profile, and optic disc photography. Peripapillary retinal nerve fiber layer thickness (RNFL) measurements were obtained by SLP (GDx-VCC) and SD-OCT (Spectralis OCT). Positive and negative predictive values (PPV, NPV) were calculated for morphologic parameters of SLP and SD-OCT. Kaplan-Meier survival curves were plotted and log-rank tests were performed to compare the survival distributions. Contingency tables and Venn-diagrams were calculated to compare the predictive ability. The study included 207 patients-75 with ocular hypertension, 85 with early glaucoma, and 47 controls. Median follow-up was 4.5 years. A total of 29 patients (14.0%) developed visual field conversion during follow-up. SLP temporal-inferior RNFL [0.667; 95% confidence interval (CI), 0.281-0.935] and SD-OCT temporal-inferior RNFL (0.571; 95% CI, 0.317-0.802) achieved the highest PPV; nerve fiber indicator (0.923; 95% CI, 0.876-0.957) and SD-OCT mean (0.898; 95% CI, 0.847-0.937) achieved the highest NPV of all investigated parameters. The Kaplan-Meier curves confirmed significantly higher survival for subjects within normal limits of measurements of both devices (P<0.001). Venn diagrams tested with McNemar test statistics showed no significant difference for PPV (P=0.219) or NPV (P=0.678). Both GDx-VCC and SD-OCT demonstrate comparable results in predicting future visual field conversion if taking typical scans for GDx-VCC. In addition, the likelihood ratios suggest that GDx-VCC's nerve fiber indicator<30 may be the most useful parameter to confirm future nonconversion. (http://www.ClinicalTrials.gov number, NTC00494923; Erlangen Glaucoma Registry).

Determinants of work ability and its predictive value for disability.

PubMed

Alavinia, S M; de Boer, A G E M; van Duivenbooden, J C; Frings-Dresen, M H W; Burdorf, A

2009-01-01

Maintaining the ability of workers to cope with physical and psychosocial demands at work becomes increasingly important in prolonging working life. To analyse the effects of work-related factors and individual characteristics on work ability and to determine the predictive value of work ability on receiving a work-related disability pension. A longitudinal study was conducted among 850 construction workers aged 40 years and older, with average follow-up period of 23 months. Disability was defined as receiving a disability pension, granted to workers unable to continue working in their regular job. Work ability was assessed using the work ability index (WAI). Associations between work-related factors and individual characteristics with work ability at baseline were evaluated using linear regression analysis, and Cox regression analysis was used to evaluate the predictive value of work ability for disability. Work-related factors were associated with a lower work ability at baseline, but had little prognostic value for disability during follow-up. The hazard ratios for disability among workers with a moderate and poor work ability at baseline were 8 and 32, respectively. All separate scales in the WAI had predictive power for future disability with the highest influence of current work ability in relation to job demands and lowest influence of diseases diagnosed by a physician. A moderate or poor work ability was highly predictive for receiving a disability pension. Preventive measures should facilitate a good balance between work performance and health in order to prevent quitting labour participation.

75 FR 80354 - Satellite Television Extension and Localism Act of 2010 and Satellite Home Viewer Extension and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-22

... Commission, adopts a point-to-point predictive model for determining the ability of individual locations to... predictive model for reliably and presumptively determining the ability of individual locations, through the... adopted a point-to-point predictive model for determining the ability of individual locations to receive...

Numerical predictors of arithmetic success in grades 1-6.

PubMed

Lyons, Ian M; Price, Gavin R; Vaessen, Anniek; Blomert, Leo; Ansari, Daniel

2014-09-01

Math relies on mastery and integration of a wide range of simpler numerical processes and concepts. Recent work has identified several numerical competencies that predict variation in math ability. We examined the unique relations between eight basic numerical skills and early arithmetic ability in a large sample (N = 1391) of children across grades 1-6. In grades 1-2, children's ability to judge the relative magnitude of numerical symbols was most predictive of early arithmetic skills. The unique contribution of children's ability to assess ordinality in numerical symbols steadily increased across grades, overtaking all other predictors by grade 6. We found no evidence that children's ability to judge the relative magnitude of approximate, nonsymbolic numbers was uniquely predictive of arithmetic ability at any grade. Overall, symbolic number processing was more predictive of arithmetic ability than nonsymbolic number processing, though the relative importance of symbolic number ability appears to shift from cardinal to ordinal processing. © 2014 John Wiley & Sons Ltd.

New equations for predicting postoperative risk in patients with hip fracture.

PubMed

Hirose, Jun; Ide, Junji; Irie, Hiroki; Kikukawa, Kenshi; Mizuta, Hiroshi

2009-12-01

Predicting the postoperative course of patients with hip fractures would be helpful for surgical planning and risk management. We therefore established equations to predict the morbidity and mortality rates in candidates for hip fracture surgery using the Estimation of Physiologic Ability and Surgical Stress (E-PASS) risk-scoring system. First we evaluated the correlation between the E-PASS scores and postoperative morbidity and mortality rates in all 722 patients surgically treated for hip fractures during the study period (Group A). Next we established equations to predict morbidity and mortality rates. We then applied these equations to all 633 patients with hip fractures treated at seven other hospitals (Group B) and compared the predicted and actual morbidity and mortality rates to assess the predictive ability of the E-PASS and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems. The ratio of actual to predicted morbidity and mortality rates was closer to 1.0 with the E-PASS than the POSSUM system. Our data suggest the E-PASS scoring system is useful for defining postoperative risk and its underlying algorithm accurately predicts morbidity and mortality rates in patients with hip fractures before surgery. This information then can be used to manage their condition and potentially improve treatment outcomes. Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Predicting space telerobotic operator training performance from human spatial ability assessment

NASA Astrophysics Data System (ADS)

Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

2013-11-01

Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds.

PubMed

Cuyabano, B C D; Su, G; Rosa, G J M; Lund, M S; Gianola, D

2015-10-01

This study compared the accuracy of genome-enabled prediction models using individual single nucleotide polymorphisms (SNP) or haplotype blocks as covariates when using either a single breed or a combined population of Nordic Red cattle. The main objective was to compare predictions of breeding values of complex traits using a combined training population with haplotype blocks, with predictions using a single breed as training population and individual SNP as predictors. To compare the prediction reliabilities, bootstrap samples were taken from the test data set. With the bootstrapped samples of prediction reliabilities, we built and graphed confidence ellipses to allow comparisons. Finally, measures of statistical distances were used to calculate the gain in predictive ability. Our analyses are innovative in the context of assessment of predictive models, allowing a better understanding of prediction reliabilities and providing a statistical basis to effectively calibrate whether one prediction scenario is indeed more accurate than another. An ANOVA indicated that use of haplotype blocks produced significant gains mainly when Bayesian mixture models were used but not when Bayesian BLUP was fitted to the data. Furthermore, when haplotype blocks were used to train prediction models in a combined Nordic Red cattle population, we obtained up to a statistically significant 5.5% average gain in prediction accuracy, over predictions using individual SNP and training the model with a single breed. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Recognition of facial expressions of emotion by adults with intellectual disability: Is there evidence for the emotion specificity hypothesis?

PubMed

Scotland, Jennifer L; McKenzie, Karen; Cossar, Jill; Murray, Aja; Michie, Amanda

2016-01-01

This study aimed to evaluate the emotion recognition abilities of adults (n=23) with an intellectual disability (ID) compared with a control group of children (n=23) without ID matched for estimated cognitive ability. The study examined the impact of: task paradigm, stimulus type and preferred processing style (global/local) on accuracy. We found that, after controlling for estimated cognitive ability, the control group performed significantly better than the individuals with ID. This provides some support for the emotion specificity hypothesis. Having a more local processing style did not significantly mediate the relation between having ID and emotion recognition, but did significantly predict emotion recognition ability after controlling for group. This suggests that processing style is related to emotion recognition independently of having ID. The availability of contextual information improved emotion recognition for people with ID when compared with line drawing stimuli, and identifying a target emotion from a choice of two was relatively easier for individuals with ID, compared with the other task paradigms. The results of the study are considered in the context of current theories of emotion recognition deficits in individuals with ID. Copyright © 2015 Elsevier Ltd. All rights reserved.

Specific Intellectual Deficits in Children with Early Onset Diabetes Mellitus.

ERIC Educational Resources Information Center

Rovet, Joanne F.; And Others

1988-01-01

Compares 27 children with early onset diabetes (EOD) with 24 children with late onset diabetes (LOD) and 30 sibling controls in performance on tests of intellectual functioning and school achievement. Results revealed that duration of illness, age of onset, and hypoglycemic convulsions significantly predicted spatial ability. (Author/RWB)

Emotion-Work Performance among Dual-Earner Couples: Testing Four Theoretical Perspectives

ERIC Educational Resources Information Center

Minnotte, Krista Lynn; Stevens, Daphne Pedersen; Minnotte, Michael C.; Kiger, Gary

2007-01-01

This study compares four theories of domestic labor in their ability to predict relative emotion-work performance among dual-earner couples. Specifically, the authors investigate the effects of gender ideology, time availability, relative resources, and crossover factors on the dependent variable of relative emotion-work performance using…

Meditation in Higher Education: Does It Enhance Cognition?

ERIC Educational Resources Information Center

Helber, Casey; Zook, Nancy A.; Immergut, Matthew

2012-01-01

We predicted that students in a sociology course that included contemplative practices (i.e., mindfulness meditation) would show an increase in performance on higher level cognitive abilities (executive functions) over the semester compared to a control group of students. Change in executive functions performance was not significantly different…

Imitation in Fragile X Syndrome: Implications for Autism

ERIC Educational Resources Information Center

Macedoni-Luksic, Marta; Greiss-Hess, Laura; Rogers, Sally J.; Gosar, David; Lemons-Chitwood, Kerrie; Hagerman, Randi

2009-01-01

To address the specific impairment of imitation in autism, the imitation abilities of 22 children with fragile X syndrome (FXS) with and without autism were compared. Based on previous research, we predicted that children with FXS and autism would have significantly more difficulty with non-meaningful imitation tasks. After controlling for…

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Does social environment influence learning ability in a family-living lizard?

PubMed

Riley, Julia L; Noble, Daniel W A; Byrne, Richard W; Whiting, Martin J

2017-05-01

Early developmental environment can have profound effects on individual physiology, behaviour, and learning. In birds and mammals, social isolation during development is known to negatively affect learning ability; yet in other taxa, like reptiles, the effect of social isolation during development on learning ability is unknown. We investigated how social environment affects learning ability in the family-living tree skink (Egernia striolata). We hypothesized that early social environment shapes cognitive development in skinks and predicted that skinks raised in social isolation would have reduced learning ability compared to skinks raised socially. Offspring were separated at birth into two rearing treatments: (1) raised alone or (2) in a pair. After 1 year, we quantified spatial learning ability of skinks in these rearing treatments (N = 14 solitary, 14 social). We found no effect of rearing treatment on learning ability. The number of skinks to successfully learn the task, the number of trials taken to learn the task, the latency to perform the task, and the number of errors in each trial did not differ between isolated and socially reared skinks. Our results were unexpected, yet the facultative nature of this species' social system may result in a reduced effect of social isolation on behaviour when compared to species with obligate sociality. Overall, our findings do not provide evidence that social environment affects development of spatial learning ability in this family-living lizard.

Diagnostic accuracy of liver fibrosis based on red cell distribution width (RDW) to platelet ratio with fibroscan in chronic hepatitis B

NASA Astrophysics Data System (ADS)

Sembiring, J.; Jones, F.

2018-03-01

Red cell Distribution Width (RDW) and platelet ratio (RPR) can predict liver fibrosis and cirrhosis in chronic hepatitis B with relatively high accuracy. RPR was superior to other non-invasive methods to predict liver fibrosis, such as AST and ALT ratio, AST and platelet ratio Index and FIB-4. The aim of this study was to assess diagnostic accuracy liver fibrosis by using RDW and platelets ratio in chronic hepatitis B patients based on compared with Fibroscan. This cross-sectional study was conducted at Adam Malik Hospital from January-June 2015. We examine 34 patients hepatitis B chronic, screen RDW, platelet, and fibroscan. Data were statistically analyzed. The result RPR with ROC procedure has an accuracy of 72.3% (95% CI: 84.1% - 97%). In this study, the RPR had a moderate ability to predict fibrosis degree (p = 0.029 with AUC> 70%). The cutoff value RPR was 0.0591, sensitivity and spesificity were 71.4% and 60%, Positive Prediction Value (PPV) was 55.6% and Negative Predictions Value (NPV) was 75%, positive likelihood ratio was 1.79 and negative likelihood ratio was 0.48. RPR have the ability to predict the degree of liver fibrosis in chronic hepatitis B patients with moderate accuracy.

[Establishment of the prediction model for ischemic cardiovascular disease of elderly male population under current health care program].

PubMed

Chen, Jin-hong; Wu, Hai-yun; He, Kun-lun; He, Yao; Qin, Yin-he

2010-10-01

To establish and verify the prediction model for ischemic cardiovascular disease (ICVD) among the elderly population who were under the current health care programs. Statistical analysis on data from physical examination, hospitalization of the past years, from questionnaire and telephone interview was carried out in May, 2003. Data was from a hospital which implementing a health care program. Baseline population with a proportion of 4:1 was randomly selected to generate both module group and verification group. Baseline data was induced to make the verification group into regression model of module group and to generate the predictive value. Distinguished ability with area under ROC curve and the predictive veracity were verified through comparing the predictive incidence rate and actual incidence rate of every deciles group by Hosmer-Lemeshow test. Predictive veracity of the prediction model at population level was verified through comparing the predictive 6-year incidence rates of ICVD with actual 6-year accumulative incidence rates of ICVD with error rate calculated. The samples included 2271 males over the age of 65 with 1817 people for modeling population and 454 for verified population. All of the samples were stratified into two layers to establish hierarchical Cox proportional hazard regression model, including one advanced age group (greater than or equal to 75 years old), and another elderly group (less than 75 years old). Data from the statically analysis showed that the risk factors in aged group were age, systolic blood pressure, serum creatinine level, fasting blood glucose level, while protective factor was high density lipoprotein;in advanced age group, the risk factors were body weight index, systolic blood pressure, serum total cholesterol level, serum creatinine level, fasting blood glucose level, while protective factor was HDL-C. The area under the ROC curve (AUC) and 95%CI were 0.723 and 0.687 - 0.759 respectively. Discriminating power was good. All individual predictive ICVD cumulative incidence and actual incidence were analyzed using Hosmer-Lemeshow test, χ(2) = 1.43, P = 0.786, showing that the predictive veracity was good. The stratified Cox Hazards Regression model was used to establish prediction model of the aged male population under a certain health care program. The common prediction factor of the two age groups were: systolic blood pressure, serum creatinine level, fasting blood glucose level and HDL-C. The area under the ROC curve of the verification group was 0.723, showing that the distinguished ability was good and the predict ability at the individual level and at the group level were also satisfactory. It was feasible to using Cox Proportional Hazards Regression Model for predicting the population groups.

Comparison and relationship of thyroid hormones, IL-6, IL-10 and albumin as mortality predictors in case-mix critically ill patients.

PubMed

Quispe E, Álvaro; Li, Xiang-Min; Yi, Hong

2016-05-01

To compare the ability of thyroid hormones, IL-6, IL-10, and albumin to predict mortality, and to assess their relationship in case-mix acute critically ill patients. APACHE II scores and serum thyroid hormones (FT3, FT4, and TSH), IL-6, IL-10, and albumin were obtained at EICU admission for 79 cases of mix acute critically ill patients without previous history of thyroid disease. Patients were followed for 28 days with patient's death as the primary outcome. All mean values were compared, correlations assessed with Pearson' test, and mortality prediction assessed by multivariate logistic regression and ROC. Non survivors were older, with higher APACHE II score (p=0.000), IL-6 (p<0.05), IL-10 (p=0.000) levels, and lower albumin (p=0.000) levels compared to survivors at 28 days. IL-6 and IL-10 had significant negative correlation with albumin (p=0.001) and FT3 (p ⩽ 0.05) respectively, while low albumin had a direct correlation with FT3 (p<0.05). In the mortality prediction assessment, IL-10, albumin and APACHE II were independent morality predictors and showed to have a good (0.70-0.79) AUC-ROC (p<0.05). Despite that the entire cohort showed low FT3 serum levels (p=0.000), there was not statistical difference between survivors and non-survivors; neither showed any significance as mortality predictor. IL-6 and IL-10 are correlated with Low FT3 and hypoalbuminemia. Thyroid hormones assessed at EICU admission did not have any predictive value in our study. And finally, high levels of IL-6 and IL-10 in conjunction with albumin could improve our ability to evaluate disease's severity and predict mortality in the critically ill patients. When use in combination with APACHE II scores, our model showed improved mortality prediction. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Prosodic development in middle childhood and adolescence in high-functioning autism.

PubMed

Lyons, Megan; Schoen Simmons, Elizabeth; Paul, Rhea

2014-04-01

The present study aims to investigate the perception and production of several domains of prosodic performance in a cross-sectional sample of preadolescents and adolescents with and without high-functioning autism (HFA). To look at the role of language abilities on prosodic performance, the HFA groups were subdivided based on "high" and "low" language performance on the Clinical Evaluation of Language Fundamentals-Fourth Edition (CELF-4) (Semel, Wiig, & Secord). Social and cognitive abilities were also examined to determine their relationship to prosodic performance. No significant differences were seen in prosody scores in the younger versus older subgroups in typically developing (TD) group with age-appropriate language. There was small but significant improvement in performance with age in the groups with HFA. Comparing performance at each age level across diagnostic groups showed that preteens with HFA and higher language levels perform similarly to their TD peers on all prosodic tasks, whereas those with lower language skills scored significantly worse than both their higher language and TD peers when looking at composite perception and production findings. Teens with HFA showed no deficits on perception tasks; however, those with low language levels had difficulty on several production tasks when compared to the TD group. Regression analyses suggested that, for the preteen group with HFA, language was the strongest predictor of prosodic perception, whereas nonverbal IQ was most highly predictive of prosodic production. For adolescents with HFA, social skills significantly contributed to the prediction of prosodic perception and, along with language abilities, predicted prosodic production. Implications of these findings will be discussed. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

Are There Age-Related Differences in the Ability to Learn Configural Responses?

PubMed Central

Clark, Rachel; Freedberg, Michael; Hazeltine, Eliot; Voss, Michelle W.

2015-01-01

Age is often associated with a decline in cognitive abilities that are important for maintaining functional independence, such as learning new skills. Many forms of motor learning appear to be relatively well preserved with age, while learning tasks that involve associative binding tend to be negatively affected. The current study aimed to determine whether age differences exist on a configural response learning task, which includes aspects of motor learning and associative binding. Young (M = 24 years) and older adults (M = 66.5 years) completed a modified version of a configural learning task. Given the requirement of associative binding in the configural relationships between responses, we predicted older adults would show significantly less learning than young adults. Older adults demonstrated lower performance (slower reaction time and lower accuracy). However, contrary to our prediction, older adults showed similar rates of learning as indexed by a configural learning score compared to young adults. These results suggest that the ability to acquire knowledge incidentally about configural response relationships is largely unaffected by cognitive aging. The configural response learning task provides insight into the task demands that constrain learning abilities in older adults. PMID:26317773

Narrative Fiction and Expository Nonfiction Differentially Predict Verbal Ability

ERIC Educational Resources Information Center

Mar, Raymond A.; Rain, Marina

2015-01-01

Although reading is known to be an important contributor to language abilities, it is not yet well established whether different text genres are uniquely associated with verbal abilities. We examined how exposure to narrative fiction and expository nonfiction predict language ability among university students. Exposure was measured both with…

Development of a bedside viable ultrasound protocol to quantify appendicular lean tissue mass.

PubMed

Paris, Michael T; Lafleur, Benoit; Dubin, Joel A; Mourtzakis, Marina

2017-10-01

Ultrasound is a non-invasive and readily available tool that can be prospectively applied at the bedside to assess muscle mass in clinical settings. The four-site protocol, which images two anatomical sites on each quadriceps, may be a viable bedside method, but its ability to predict musculature has not been compared against whole-body reference methods. Our primary objectives were to (i) compare the four-site protocol's ability to predict appendicular lean tissue mass from dual-energy X-ray absorptiometry; (ii) optimize the predictability of the four-site protocol with additional anatomical muscle thicknesses and easily obtained covariates; and (iii) assess the ability of the optimized protocol to identify individuals with low lean tissue mass. This observational cross-sectional study recruited 96 university and community dwelling adults. Participants underwent ultrasound scans for assessment of muscle thickness and whole-body dual-energy X-ray absorptiometry scans for assessment of appendicular lean tissue. Ultrasound protocols included (i) the nine-site protocol, which images nine anterior and posterior muscle groups in supine and prone positions, and (ii) the four-site protocol, which images two anterior sites on each quadriceps muscle group in a supine position. The four-site protocol was strongly associated (R 2  = 0.72) with appendicular lean tissue mass, but Bland-Altman analysis displayed wide limits of agreement (-5.67, 5.67 kg). Incorporating the anterior upper arm muscle thickness, and covariates age and sex, alongside the four-site protocol, improved the association (R 2  = 0.91) with appendicular lean tissue and displayed narrower limits of agreement (-3.18, 3.18 kg). The optimized protocol demonstrated a strong ability to identify low lean tissue mass (area under the curve = 0.89). The four-site protocol can be improved with the addition of the anterior upper arm muscle thickness, sex, and age when predicting appendicular lean tissue mass. This optimized protocol can accurately identify low lean tissue mass, while still being easily applied at the bedside. © 2017 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of the Society on Sarcopenia, Cachexia and Wasting Disorders.

Development of a bedside viable ultrasound protocol to quantify appendicular lean tissue mass

PubMed Central

Paris, Michael T.; Lafleur, Benoit; Dubin, Joel A.

2017-01-01

Abstract Background Ultrasound is a non‐invasive and readily available tool that can be prospectively applied at the bedside to assess muscle mass in clinical settings. The four‐site protocol, which images two anatomical sites on each quadriceps, may be a viable bedside method, but its ability to predict musculature has not been compared against whole‐body reference methods. Our primary objectives were to (i) compare the four‐site protocol's ability to predict appendicular lean tissue mass from dual‐energy X‐ray absorptiometry; (ii) optimize the predictability of the four‐site protocol with additional anatomical muscle thicknesses and easily obtained covariates; and (iii) assess the ability of the optimized protocol to identify individuals with low lean tissue mass. Methods This observational cross‐sectional study recruited 96 university and community dwelling adults. Participants underwent ultrasound scans for assessment of muscle thickness and whole‐body dual‐energy X‐ray absorptiometry scans for assessment of appendicular lean tissue. Ultrasound protocols included (i) the nine‐site protocol, which images nine anterior and posterior muscle groups in supine and prone positions, and (ii) the four‐site protocol, which images two anterior sites on each quadriceps muscle group in a supine position. Results The four‐site protocol was strongly associated (R 2 = 0.72) with appendicular lean tissue mass, but Bland–Altman analysis displayed wide limits of agreement (−5.67, 5.67 kg). Incorporating the anterior upper arm muscle thickness, and covariates age and sex, alongside the four‐site protocol, improved the association (R 2 = 0.91) with appendicular lean tissue and displayed narrower limits of agreement (−3.18, 3.18 kg). The optimized protocol demonstrated a strong ability to identify low lean tissue mass (area under the curve = 0.89). Conclusions The four‐site protocol can be improved with the addition of the anterior upper arm muscle thickness, sex, and age when predicting appendicular lean tissue mass. This optimized protocol can accurately identify low lean tissue mass, while still being easily applied at the bedside. PMID:28722298

Watching novice action degrades expert motor performance: Causation between action production and outcome prediction of observed actions by humans

PubMed Central

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2014-01-01

Our social skills are critically determined by our ability to understand and appropriately respond to actions performed by others. However despite its obvious importance, the mechanisms enabling action understanding in humans have remained largely unclear. A popular but controversial belief is that parts of the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral paradigm, we investigated this belief by examining a causal relation between action production, and a component of action understanding - outcome prediction, the ability of a person to predict the outcome of observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert's ability to predict watched actions while controlling the other experimental factors, and exhibited that a change (improvement) in their outcome prediction ability results in a progressive and proportional deterioration in the expert's own darts performance. This causal relationship supports involvement of the motor system in outcome prediction by humans of actions observed in others. PMID:25384755

"Wish You Were Here": Examining Characteristics, Outcomes, and Statistical Solutions for Missing Cases in Web-Based Psychotherapeutic Trials.

PubMed

Karin, Eyal; Dear, Blake F; Heller, Gillian Z; Crane, Monique F; Titov, Nickolai

2018-04-19

Missing cases following treatment are common in Web-based psychotherapy trials. Without the ability to directly measure and evaluate the outcomes for missing cases, the ability to measure and evaluate the effects of treatment is challenging. Although common, little is known about the characteristics of Web-based psychotherapy participants who present as missing cases, their likely clinical outcomes, or the suitability of different statistical assumptions that can characterize missing cases. Using a large sample of individuals who underwent Web-based psychotherapy for depressive symptoms (n=820), the aim of this study was to explore the characteristics of cases who present as missing cases at posttreatment (n=138), their likely treatment outcomes, and compare between statistical methods for replacing their missing data. First, common participant and treatment features were tested through binary logistic regression models, evaluating the ability to predict missing cases. Second, the same variables were screened for their ability to increase or impede the rate symptom change that was observed following treatment. Third, using recontacted cases at 3-month follow-up to proximally represent missing cases outcomes following treatment, various simulated replacement scores were compared and evaluated against observed clinical follow-up scores. Missing cases were dominantly predicted by lower treatment adherence and increased symptoms at pretreatment. Statistical methods that ignored these characteristics can overlook an important clinical phenomenon and consequently produce inaccurate replacement outcomes, with symptoms estimates that can swing from -32% to 70% from the observed outcomes of recontacted cases. In contrast, longitudinal statistical methods that adjusted their estimates for missing cases outcomes by treatment adherence rates and baseline symptoms scores resulted in minimal measurement bias (<8%). Certain variables can characterize and predict missing cases likelihood and jointly predict lesser clinical improvement. Under such circumstances, individuals with potentially worst off treatment outcomes can become concealed, and failure to adjust for this can lead to substantial clinical measurement bias. Together, this preliminary research suggests that missing cases in Web-based psychotherapeutic interventions may not occur as random events and can be systematically predicted. Critically, at the same time, missing cases may experience outcomes that are distinct and important for a complete understanding of the treatment effect. ©Eyal Karin, Blake F Dear, Gillian Z Heller, Monique F Crane, Nickolai Titov. Originally published in JMIR Mental Health (http://mental.jmir.org), 19.04.2018.

“Wish You Were Here”: Examining Characteristics, Outcomes, and Statistical Solutions for Missing Cases in Web-Based Psychotherapeutic Trials

PubMed Central

Dear, Blake F; Heller, Gillian Z; Crane, Monique F; Titov, Nickolai

2018-01-01

Background Missing cases following treatment are common in Web-based psychotherapy trials. Without the ability to directly measure and evaluate the outcomes for missing cases, the ability to measure and evaluate the effects of treatment is challenging. Although common, little is known about the characteristics of Web-based psychotherapy participants who present as missing cases, their likely clinical outcomes, or the suitability of different statistical assumptions that can characterize missing cases. Objective Using a large sample of individuals who underwent Web-based psychotherapy for depressive symptoms (n=820), the aim of this study was to explore the characteristics of cases who present as missing cases at posttreatment (n=138), their likely treatment outcomes, and compare between statistical methods for replacing their missing data. Methods First, common participant and treatment features were tested through binary logistic regression models, evaluating the ability to predict missing cases. Second, the same variables were screened for their ability to increase or impede the rate symptom change that was observed following treatment. Third, using recontacted cases at 3-month follow-up to proximally represent missing cases outcomes following treatment, various simulated replacement scores were compared and evaluated against observed clinical follow-up scores. Results Missing cases were dominantly predicted by lower treatment adherence and increased symptoms at pretreatment. Statistical methods that ignored these characteristics can overlook an important clinical phenomenon and consequently produce inaccurate replacement outcomes, with symptoms estimates that can swing from −32% to 70% from the observed outcomes of recontacted cases. In contrast, longitudinal statistical methods that adjusted their estimates for missing cases outcomes by treatment adherence rates and baseline symptoms scores resulted in minimal measurement bias (<8%). Conclusions Certain variables can characterize and predict missing cases likelihood and jointly predict lesser clinical improvement. Under such circumstances, individuals with potentially worst off treatment outcomes can become concealed, and failure to adjust for this can lead to substantial clinical measurement bias. Together, this preliminary research suggests that missing cases in Web-based psychotherapeutic interventions may not occur as random events and can be systematically predicted. Critically, at the same time, missing cases may experience outcomes that are distinct and important for a complete understanding of the treatment effect. PMID:29674311

Work ability as prognostic risk marker of disability pension: single-item work ability score versus multi-item work ability index.

PubMed

Roelen, Corné A M; van Rhenen, Willem; Groothoff, Johan W; van der Klink, Jac J L; Twisk, Jos W R; Heymans, Martijn W

2014-07-01

Work ability predicts future disability pension (DP). A single-item work ability score (WAS) is emerging as a measure for work ability. This study compared single-item WAS with the multi-item work ability index (WAI) in its ability to identify workers at risk of DP. This prospective cohort study comprised 11 537 male construction workers, who completed the WAI at baseline and reported DP after a mean 2.3 years of follow-up. WAS and WAI were calibrated for DP risk predictions with the Hosmer-Lemeshow (H-L) test and their ability to discriminate between high- and low-risk construction workers was investigated with the area under the receiver operating characteristic curve (AUC). At follow-up, 336 (3%) construction workers reported DP. Both WAS [odds ratio (OR) 0.72, 95% confidence interval (95% CI) 0.66-0.78] and WAI (OR 0.57, 95% CI 0.52-0.63) scores were associated with DP at follow-up. The WAS showed miscalibration (H-L model χ (�)=10.60; df=3; P=0.01) and poorly discriminated between high- and low-risk construction workers (AUC 0.67, 95% CI 0.64-0.70). In contrast, calibration (H-L model χ �=8.20; df=8; P=0.41) and discrimination (AUC 0.78, 95% CI 0.75-0.80) were both adequate for the WAI. Although associated with the risk of future DP, the single-item WAS poorly identified male construction workers at risk of DP. We recommend using the multi-item WAI to screen for risk of DP in occupational health practice.

Relation between Peak Power Output in Sprint Cycling and Maximum Voluntary Isometric Torque Production.

PubMed

Kordi, Mehdi; Goodall, Stuart; Barratt, Paul; Rowley, Nicola; Leeder, Jonathan; Howatson, Glyn

2017-08-01

From a cycling paradigm, little has been done to understand the relationships between maximal isometric strength of different single joint lower body muscle groups and their relation with, and ability to predict PPO and how they compare to an isometric cycling specific task. The aim of this study was to establish relationships between maximal voluntary torque production from isometric single-joint and cycling specific tasks and assess their ability to predict PPO. Twenty male trained cyclists participated in this study. Peak torque was measured by performing maximum voluntary contractions (MVC) of knee extensors, knee flexors, dorsi flexors and hip extensors whilst instrumented cranks measured isometric peak torque from MVC when participants were in their cycling specific position (ISOCYC). A stepwise regression showed that peak torque of the knee extensors was the only significant predictor of PPO when using SJD and accounted for 47% of the variance. However, when compared to ISOCYC, the only significant predictor of PPO was ISOCYC, which accounted for 77% of the variance. This suggests that peak torque of the knee extensors was the best single-joint predictor of PPO in sprint cycling. Furthermore, a stronger prediction can be made from a task specific isometric task. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative Study on Prediction Effects of Short Fatigue Crack Propagation Rate by Two Different Calculation Methods

NASA Astrophysics Data System (ADS)

Yang, Bing; Liao, Zhen; Qin, Yahang; Wu, Yayun; Liang, Sai; Xiao, Shoune; Yang, Guangwu; Zhu, Tao

2017-05-01

To describe the complicated nonlinear process of the fatigue short crack evolution behavior, especially the change of the crack propagation rate, two different calculation methods are applied. The dominant effective short fatigue crack propagation rates are calculated based on the replica fatigue short crack test with nine smooth funnel-shaped specimens and the observation of the replica films according to the effective short fatigue cracks principle. Due to the fast decay and the nonlinear approximation ability of wavelet analysis, the self-learning ability of neural network, and the macroscopic searching and global optimization of genetic algorithm, the genetic wavelet neural network can reflect the implicit complex nonlinear relationship when considering multi-influencing factors synthetically. The effective short fatigue cracks and the dominant effective short fatigue crack are simulated and compared by the Genetic Wavelet Neural Network. The simulation results show that Genetic Wavelet Neural Network is a rational and available method for studying the evolution behavior of fatigue short crack propagation rate. Meanwhile, a traditional data fitting method for a short crack growth model is also utilized for fitting the test data. It is reasonable and applicable for predicting the growth rate. Finally, the reason for the difference between the prediction effects by these two methods is interpreted.

Mechanical behaviour of a fibrous scaffold for ligament tissue engineering: finite elements analysis vs. X-ray tomography imaging.

PubMed

Laurent, Cédric P; Latil, Pierre; Durville, Damien; Rahouadj, Rachid; Geindreau, Christian; Orgéas, Laurent; Ganghoffer, Jean-François

2014-12-01

The use of biodegradable scaffolds seeded with cells in order to regenerate functional tissue-engineered substitutes offers interesting alternative to common medical approaches for ligament repair. Particularly, finite element (FE) method enables the ability to predict and optimise both the macroscopic behaviour of these scaffolds and the local mechanic signals that control the cell activity. In this study, we investigate the ability of a dedicated FE code to predict the geometrical evolution of a new braided and biodegradable polymer scaffold for ligament tissue engineering by comparing scaffold geometries issued from FE simulations and from X-ray tomographic imaging during a tensile test. Moreover, we compare two types of FE simulations the initial geometries of which are issued either from X-ray imaging or from a computed idealised configuration. We report that the dedicated FE simulations from an idealised reference configuration can be reasonably used in the future to predict the global and local mechanical behaviour of the braided scaffold. A valuable and original dialog between the fields of experimental and numerical characterisation of such fibrous media is thus achieved. In the future, this approach should enable to improve accurate characterisation of local and global behaviour of tissue-engineering scaffolds. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of a numerical model's ability to predict bed load transport observed in braided river experiments

NASA Astrophysics Data System (ADS)

Javernick, Luke; Redolfi, Marco; Bertoldi, Walter

2018-05-01

New data collection techniques offer numerical modelers the ability to gather and utilize high quality data sets with high spatial and temporal resolution. Such data sets are currently needed for calibration, verification, and to fuel future model development, particularly morphological simulations. This study explores the use of high quality spatial and temporal data sets of observed bed load transport in braided river flume experiments to evaluate the ability of a two-dimensional model, Delft3D, to predict bed load transport. This study uses a fixed bed model configuration and examines the model's shear stress calculations, which are the foundation to predict the sediment fluxes necessary for morphological simulations. The evaluation is conducted for three flow rates, and model setup used highly accurate Structure-from-Motion (SfM) topography and discharge boundary conditions. The model was hydraulically calibrated using bed roughness, and performance was evaluated based on depth and inundation agreement. Model bed load performance was evaluated in terms of critical shear stress exceedance area compared to maps of observed bed mobility in a flume. Following the standard hydraulic calibration, bed load performance was tested for sensitivity to horizontal eddy viscosity parameterization and bed morphology updating. Simulations produced depth errors equal to the SfM inherent errors, inundation agreement of 77-85%, and critical shear stress exceedance in agreement with 49-68% of the observed active area. This study provides insight into the ability of physically based, two-dimensional simulations to accurately predict bed load as well as the effects of horizontal eddy viscosity and bed updating. Further, this study highlights how using high spatial and temporal data to capture the physical processes at work during flume experiments can help to improve morphological modeling.

Can non‐clinical repolarization assays predict the results of clinical thorough QT studies? Results from a research consortium

PubMed Central

Park, Eunjung; Gintant, Gary A; Bi, Daoqin; Kozeli, Devi; Pettit, Syril D; Skinner, Matthew; Willard, James; Wisialowski, Todd; Koerner, John; Valentin, Jean‐Pierre

2018-01-01

Background and Purpose Translation of non‐clinical markers of delayed ventricular repolarization to clinical prolongation of the QT interval corrected for heart rate (QTc) (a biomarker for torsades de pointes proarrhythmia) remains an issue in drug discovery and regulatory evaluations. We retrospectively analysed 150 drug applications in a US Food and Drug Administration database to determine the utility of established non‐clinical in vitro IKr current human ether‐à‐go‐go‐related gene (hERG), action potential duration (APD) and in vivo (QTc) repolarization assays to detect and predict clinical QTc prolongation. Experimental Approach The predictive performance of three non‐clinical assays was compared with clinical thorough QT study outcomes based on free clinical plasma drug concentrations using sensitivity and specificity, receiver operating characteristic (ROC) curves, positive (PPVs) and negative predictive values (NPVs) and likelihood ratios (LRs). Key Results Non‐clinical assays demonstrated robust specificity (high true negative rate) but poor sensitivity (low true positive rate) for clinical QTc prolongation at low‐intermediate (1×–30×) clinical exposure multiples. The QTc assay provided the most robust PPVs and NPVs (ability to predict clinical QTc prolongation). ROC curves (overall test accuracy) and LRs (ability to influence post‐test probabilities) demonstrated overall marginal performance for hERG and QTc assays (best at 30× exposures), while the APD assay demonstrated minimal value. Conclusions and Implications The predictive value of hERG, APD and QTc assays varies, with drug concentrations strongly affecting translational performance. While useful in guiding preclinical candidates without clinical QT prolongation, hERG and QTc repolarization assays provide greater value compared with the APD assay. PMID:29181850

Predicting grief intensity after recent perinatal loss.

PubMed

Hutti, Marianne H; Myers, John; Hall, Lynne A; Polivka, Barbara J; White, Susan; Hill, Janice; Kloenne, Elizabeth; Hayden, Jaclyn; Grisanti, Meredith McGrew

2017-10-01

The Perinatal Grief Intensity Scale (PGIS) was developed for clinical use to identify and predict intense grief and need for follow-up after perinatal loss. This study evaluates the validity of the PGIS via its ability to predict future intense grief based on a PGIS score obtained early after a loss. A prospective observational study was conducted with 103 international, English-speaking women recruited at hospital discharge or via the internet who experienced a miscarriage, stillbirth, or neonatal death within the previous 8weeks. Survey data were collected at baseline using the PGIS and the Perinatal Grief Scale (PGS). Follow-up data on the PGS were obtained 3months later. Data analysis included descriptive statistics, Cronbach's alpha, receiver operating characteristic curve analysis, and confirmatory factor analysis. Cronbach's alphas were ≥0.70 for both instruments. PGIS factor analysis yielded three factors as predicted, explaining 57.7% of the variance. The optimal cutoff identified for the PGIS was 3.535. No difference was found when the ability of the PGIS to identify intense grief was compared to the PGS (p=0.754). The PGIS was not inferior to the PGS (AUC=0.78, 95% CI 0.68-0.88, p<0.001) in predicting intense grief at the follow-up. A PGIS score≥3.53 at baseline was associated with increased grief intensity at Time 2 (PGS: OR=1.97, 95% CI 1.59-2.34, p<0.001). The PGIS is comparable to the PGS, has a lower response burden, and can reliably and validly predict women who may experience future intense grief associated with perinatal loss. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

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

PubMed Central

Ihlen, Espen A. F.; van Schooten, Kimberley S.; Bruijn, Sjoerd M.; van Dieën, Jaap H.; Vereijken, Beatrix; Helbostad, Jorunn L.; Pijnappels, Mirjam

2018-01-01

Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME), and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016). The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME (p < 0.0001) of their trunk acceleration at 60% of their step cycle when compared with non-fallers. No significant differences were found between PGME of multiple-time fallers and non-fallers, but PGME was found to improve the prediction model of multiple-time fallers when combined with other gait features. These findings suggest that taking into account phase-dependent changes in the stability of the gait dynamics has additional value for predicting falls in older people, especially for single-time prospective fallers. PMID:29556188

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

PubMed

Ihlen, Espen A F; van Schooten, Kimberley S; Bruijn, Sjoerd M; van Dieën, Jaap H; Vereijken, Beatrix; Helbostad, Jorunn L; Pijnappels, Mirjam

2018-01-01

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

Prediction of hamstring injury in professional soccer players by isokinetic measurements

PubMed Central

Dauty, Marc; Menu, Pierre; Fouasson-Chailloux, Alban; Ferréol, Sophie; Dubois, Charles

2016-01-01

Summary Objectives previous studies investigating the ability of isokinetic strength ratios to predict hamstring injuries in soccer players have reported conflicting results. Hypothesis to determine if isokinetic ratios are able to predict hamstring injury occurring during the season in professional soccer players. Study Design case-control study; Level of evidence: 3. Methods from 2001 to 2011, 350 isokinetic tests were performed in 136 professional soccer players at the beginning of the soccer season. Fifty-seven players suffered hamstring injury during the season that followed the isokinetic tests. These players were compared with the 79 uninjured players. The bilateral concentric ratio (hamstring-to-hamstring), ipsilateral concentric ratio (hamstring-to-quadriceps), and mixed ratio (eccentric/concentric hamstring-to-quadriceps) were studied. The predictive ability of each ratio was established based on the likelihood ratio and post-test probability. Results the mixed ratio (30 eccentric/240 concentric hamstring-to-quadriceps) <0.8, ipsilateral ratio (180 concentric hamstring-to-quadriceps) <0.47, and bilateral ratio (60 concentric hamstring-to-hamstring) <0.85 were the most predictive of hamstring injury. The ipsilateral ratio <0.47 allowed prediction of the severity of the hamstring injury, and was also influenced by the length of time since administration of the isokinetic tests. Conclusion isokinetic ratios are useful for predicting the likelihood of hamstring injury in professional soccer players during the competitive season. PMID:27331039

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley.

PubMed

Li, Zuo; Philipp, Norman; Spiller, Monika; Stiewe, Gunther; Reif, Jochen C; Zhao, Yusheng

2017-03-01

Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L.) and maize ( L.) adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP) and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP). Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups. Copyright © 2017 Crop Science Society of America.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

PubMed

Peñagaricano, F; Urioste, J I; Naya, H; de los Campos, G; Gianola, D

2011-04-01

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep. © 2010 Blackwell Verlag GmbH.

Analysis backpropagation methods with neural network for prediction of children's ability in psychomotoric

NASA Astrophysics Data System (ADS)

Izhari, F.; Dhany, H. W.; Zarlis, M.; Sutarman

2018-03-01

A good age in optimizing aspects of development is at the age of 4-6 years, namely with psychomotor development. Psychomotor is broader, more difficult to monitor but has a meaningful value for the child's life because it directly affects his behavior and deeds. Therefore, there is a problem to predict the child's ability level based on psychomotor. This analysis uses backpropagation method analysis with artificial neural network to predict the ability of the child on the psychomotor aspect by generating predictions of the child's ability on psychomotor and testing there is a mean squared error (MSE) value at the end of the training of 0.001. There are 30% of children aged 4-6 years have a good level of psychomotor ability, excellent, less good, and good enough.

Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows.

PubMed

Pacheco, D; Patton, R A; Parys, C; Lapierre, H

2012-02-01

The objective of this analysis was to compare the rumen submodel predictions of 4 commonly used dairy ration programs to observed values of duodenal flows of crude protein (CP), protein fractions, and essential AA (EAA). The literature was searched and 40 studies, including 154 diets, were used to compare observed values with those predicted by AminoCow (AC), Agricultural Modeling and Training Systems (AMTS), Cornell-Penn-Miner (CPM), and National Research Council 2001 (NRC) models. The models were evaluated based on their ability to predict the mean, their root mean square prediction error (RMSPE), error bias, and adequacy of regression equations for each protein fraction. The models predicted the mean duodenal CP flow within 5%, with more than 90% of the variation due to random disturbance. The models also predicted within 5% the mean microbial CP flow except CPM, which overestimated it by 27%. Only NRC, however, predicted mean rumen-undegraded protein (RUP) flows within 5%, whereas AC and AMTS underpredicted it by 8 to 9% and CPM by 24%. Regarding duodenal flows of individual AA, across all diets, CPM predicted substantially greater (>10%) mean flows of Arg, His, Ile, Met, and Lys; AMTS predicted greater flow for Arg and Met, whereas AC and NRC estimations were, on average, within 10% of observed values. Overpredictions by the CPM model were mainly related to mean bias, whereas the NRC model had the highest proportion of bias in random disturbance for flows of EAA. Models tended to predict mean flows of EAA more accurately on corn silage and alfalfa diets than on grass-based diets, more accurately on corn grain-based diets than on non-corn-based diets, and finally more accurately in the mid range of diet types. The 4 models were accurate at predicting mean dry matter intake. The AC, AMTS, and NRC models were all sufficiently accurate to be used for balancing EAA in dairy rations under field conditions. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Functional outcome instruments used for cervical spondylotic myelopathy: interscale correlation and prediction of preference-based quality of life.

PubMed

Whitmore, Robert G; Ghogawala, Zoher; Petrov, Dmitriy; Schwartz, J Sanford; Stein, Sherman C

2013-08-01

There is limited literature comparing different functional outcome measures used for cervical spondylotic myelopathy (CSM). To determine the correlation among five functional outcome measures used in CSM patient assessment and their ability to predict preference-based quality of life (QOL). Prospective observational study. Patients, aged 40 to 85 years, with CSM and cervical spinal cord compression at two or more levels from degenerative spondylosis were enrolled from seven sites over a 2-year period. The modified Japanese Orthopedic Association scale, Oswestry neck disability index (Oswestry NDI or Oswestry), Nurick scale, norm-based short-form 36 physical component summary, and EuroQol-5D (EQ-5D) were collected. The Jean and David Wallace foundation provided funding for this study. Cervical spondylotic myelopathy patients undergoing either anterior or posterior surgery were prospectively followed with five different functional outcome measures over 1 year. Correlations among scales were tested using the Spearman rank correlation test. The sensitivity and specificity of each scale for predicting the global index of the EQ-5D were determined, and receiver-operating characteristic analysis was used to compare each scale's ability to discriminate QOL. A total of 106 patients were initially enrolled; 103 were operated on for CSM and followed for 1 year. Their ages ranged from 40 to 82 years (mean 61.9), and 61.3% were men. Correlations among the various functional outcome instruments were all highly significant (p<.001), but the degree of correlation varied greatly. Correlation between the EQ-5D scale and the Nurick scale was the least (Spearman rho 0.5539); correlation was the highest with the Oswestry NDI (Spearman rho 0.8306). The Oswestry NDI also had the greatest ability to discriminate favorable from adverse QOL compared with the other outcome instruments (p=.023). Preference-based quality-of-life instruments, such as the EQ-5D, are important measures for studying spinal disorders. Among the various commonly used outcome instruments for CSM, the Oswestry NDI is the most predictive of preference-based QOL. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Stinis, Panagiotis

We present a comparative study of two methods for thereduction of the dimensionality of a system of ordinary differentialequations that exhibits time-scale separation. Both methods lead to areduced system of stochastic differential equations. The novel feature ofthese methods is that they allow the use, in the reduced system, ofhigher order terms in the resolved variables. The first method, proposedby Majda, Timofeyev and Vanden-Eijnden, is based on an asymptoticstrategy developed by Kurtz. The second method is a short-memoryapproximation of the Mori-Zwanzig projection formalism of irreversiblestatistical mechanics, as proposed by Chorin, Hald and Kupferman. Wepresent conditions under which the reduced models arisingmore » from the twomethods should have similar predictive ability. We apply the two methodsto test cases that satisfy these conditions. The form of the reducedmodels and the numerical simulations show that the two methods havesimilar predictive ability as expected.« less

Quantitative computed tomography-based predictions of vertebral strength in anterior bending.

PubMed

Buckley, Jenni M; Cheng, Liu; Loo, Kenneth; Slyfield, Craig; Xu, Zheng

2007-04-20

This study examined the ability of QCT-based structural assessment techniques to predict vertebral strength in anterior bending. The purpose of this study was to compare the abilities of QCT-based bone mineral density (BMD), mechanics of solids models (MOS), e.g., bending rigidity, and finite element analyses (FE) to predict the strength of isolated vertebral bodies under anterior bending boundary conditions. Although the relative performance of QCT-based structural measures is well established for uniform compression, the ability of these techniques to predict vertebral strength under nonuniform loading conditions has not yet been established. Thirty human thoracic vertebrae from 30 donors (T9-T10, 20 female, 10 male; 87 +/- 5 years of age) were QCT scanned and destructively tested in anterior bending using an industrial robot arm. The QCT scans were processed to generate specimen-specific FE models as well as trabecular bone mineral density (tBMD), integral bone mineral density (iBMD), and MOS measures, such as axial and bending rigidities. Vertebral strength in anterior bending was poorly to moderately predicted by QCT-based BMD and MOS measures (R2 = 0.14-0.22). QCT-based FE models were better strength predictors (R2 = 0.34-0.40); however, their predictive performance was not statistically different from MOS bending rigidity (P > 0.05). Our results suggest that the poor clinical performance of noninvasive structural measures may be due to their inability to predict vertebral strength under bending loads. While their performance was not statistically better than MOS bending rigidities, QCT-based FE models were moderate predictors of both compressive and bending loads at failure, suggesting that this technique has the potential for strength prediction under nonuniform loads. The current FE modeling strategy is insufficient, however, and significant modifications must be made to better mimic whole bone elastic and inelastic material behavior.

Nonstandard Lumbar Region in Predicting Fracture Risk.

PubMed

Alajlouni, Dima; Bliuc, Dana; Tran, Thach; Pocock, Nicholas; Nguyen, Tuan V; Eisman, John A; Center, Jacqueline R

Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1-L2 BMD with standard L2-L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1-L2, L2-L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1-L2 BMD T-score was significantly lower than L2-L4 T-score in both genders (p < 0.0001). L1-L2 and L2-L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68-0.79) vs 0.68 (95% confidence interval, 0.62-0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1-L2 or L2-L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1-L2 is as good as but not better than L2-L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory

ERIC Educational Resources Information Center

Bergner, Yoav; Droschler, Stefan; Kortemeyer, Gerd; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

2012-01-01

We apply collaborative filtering (CF) to dichotomously scored student response data (right, wrong, or no interaction), finding optimal parameters for each student and item based on cross-validated prediction accuracy. The approach is naturally suited to comparing different models, both unidimensional and multidimensional in ability, including a…

Semantic Differential Comparisons of Attributions and Dimensions among Seven Nations.

ERIC Educational Resources Information Center

Chandler, Theodore A.; Spies, Carl J.

The classifications of 11 attributions according to dimensions of locus, stability, controllability, predictability, and globality by participants in 7 countries (China, France, Germany, Hong Kong, Israel, Spain, and the United States) were compared in a cross-cultural study. The attributions were: (1) bias; (2) help; (3) luck; (4) ability; (5)…

Memory and Suggestibility in Maltreated Children: Age, Stress Arousal, Dissociation, and Psychopathology.

ERIC Educational Resources Information Center

Eisen, Mitchell L.; Qin, Jianjian; Goodman, Gail S.; Davis, Suzanne L.

2002-01-01

This study assessed 3- to 17-year-olds' memory and suggestibility in the context of ongoing child maltreatment investigations. Results from 189 subjects indicated that general psychopathology, short-term memory, and intellectual ability predicted facets of children's memory performance. Older compared to young children evinced fewer memory errors…

A Computational Study of the Energy Dissipation Through an Acrylic Target Impacted by Various Size FSP

DTIC Science & Technology

2009-06-01

data, and then returns an array that describes the line. This function, when compared to the LOGEST statistical function of the Microsoft Excel, which...threats continues to grow, the ability to predict materials performances using advanced modeling tools increases. The current paper has demonstrated

Narrative Abilities, Memory and Attention in Children with a Specific Language Impairment

ERIC Educational Resources Information Center

Duinmeijer, Iris; de Jong, Jan; Scheper, Annette

2012-01-01

Background: While narrative tasks have proven to be valid measures for detecting language disorders, measuring communicative skills and predicting future academic performance, research into the comparability of different narrative tasks has shown that outcomes are dependent on the type of task used. Although many of the studies detecting task…

Comparing Three Patterns of Strengths and Weaknesses Models for the Identification of Specific Learning Disabilities

ERIC Educational Resources Information Center

Miller, Daniel C.; Maricle, Denise E.; Jones, Alicia M.

2016-01-01

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by…

Language Ability Predicts Cortical Structure and Covariance in Boys with Autism Spectrum Disorder.

PubMed

Sharda, Megha; Foster, Nicholas E V; Tryfon, Ana; Doyle-Thomas, Krissy A R; Ouimet, Tia; Anagnostou, Evdokia; Evans, Alan C; Zwaigenbaum, Lonnie; Lerch, Jason P; Lewis, John D; Hyde, Krista L

2017-03-01

There is significant clinical heterogeneity in language and communication abilities of individuals with Autism Spectrum Disorders (ASD). However, no consistent pathology regarding the relationship of these abilities to brain structure has emerged. Recent developments in anatomical correlation-based approaches to map structural covariance networks (SCNs), combined with detailed behavioral characterization, offer an alternative for studying these relationships. In this study, such an approach was used to study the integrity of SCNs of cortical thickness and surface area associated with language and communication, in 46 high-functioning, school-age children with ASD compared with 50 matched, typically developing controls (all males) with IQ > 75. Findings showed that there was alteration of cortical structure and disruption of fronto-temporal cortical covariance in ASD compared with controls. Furthermore, in an analysis of a subset of ASD participants, alterations in both cortical structure and covariance were modulated by structural language ability of the participants, but not communicative function. These findings indicate that structural language abilities are related to altered fronto-temporal cortical covariance in ASD, much more than symptom severity or cognitive ability. They also support the importance of better characterizing ASD samples while studying brain structure and for better understanding individual differences in language and communication abilities in ASD. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Comparison between urine albumin-to-creatinine ratio and urine protein dipstick testing for prevalence and ability to predict the risk for chronic kidney disease in the general population (Iwate-KENCO study): a prospective community-based cohort study.

PubMed

Koeda, Yorihiko; Tanaka, Fumitaka; Segawa, Toshie; Ohta, Mutsuko; Ohsawa, Masaki; Tanno, Kozo; Makita, Shinji; Ishibashi, Yasuhiro; Itai, Kazuyoshi; Omama, Shin-Ichi; Onoda, Toshiyuki; Sakata, Kiyomi; Ogasawara, Kuniaki; Okayama, Akira; Nakamura, Motoyuki

2016-05-12

This study compared the combination of estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) vs. eGFR and urine protein reagent strip testing to determine chronic kidney disease (CKD) prevalence, and each method's ability to predict the risk for cardiovascular events in the general Japanese population. Baseline data including eGFR, UACR, and urine dipstick tests were obtained from the general population (n = 22 975). Dipstick test results (negative, trace, positive) were allocated to three levels of UACR (<30, 30-300, >300), respectively. In accordance with Kidney Disease Improving Global Outcomes CKD prognosis heat mapping, the cohort was classified into four risk grades (green: grade 1; yellow: grade 2; orange: grade 3, red: grade 4) based on baseline eGFR and UACR levels or dipstick tests. During the mean follow-up period of 5.6 years, 708 new onset cardiovascular events were recorded. For CKD identified by eGFR and dipstick testing (dipstick test ≥ trace and eGFR <60 mL/min/1.73 m(2)), the incidence of CKD was found to be 9 % in the general population. In comparison to non-CKD (grade 1), although cardiovascular risk was significantly higher in risk grades ≥3 (relative risk (RR) = 1.70; 95 % CI: 1.28-2.26), risk predictive ability was not significant in risk grade 2 (RR = 1.20; 95 % CI: 0.95-1.52). When CKD was defined by eGFR and UACR (UACR ≥30 mg/g Cr and eGFR <60 mL/min/1.73 m(2)), prevalence was found to be 29 %. Predictive ability in risk grade 2 (RR = 1.41; 95 % CI: 1.19-1.66) and risk grade ≥3 (RR = 1.76; 95 % CI: 1.37-2.28) were both significantly greater than for non-CKD. Reclassification analysis showed a significant improvement in risk predictive abilities when CKD risk grading was based on UACR rather than on dipstick testing in this population (p < 0.001). Although prevalence of CKD was higher when detected by UACR rather than urine dipstick testing, the predictive ability for cardiovascular events from UACR-based risk grading was superior to that of dipstick-based risk grading in the general population.

Stroke survivors over-estimate their medication self-administration (MSA) ability, predicting memory loss.

PubMed

Barrett, A M; Galletta, Elizabeth E; Zhang, Jun; Masmela, Jenny R; Adler, Uri S

2014-01-01

Medication self-administration (MSA) may be cognitively challenging after stroke, but guidelines are currently lacking for identifying high-functioning stroke survivors who may have difficulty with this task. Complicating this matter, stroke survivors may not be aware of their cognitive problems (cognitive anosognosia) and may over-estimate their MSA competence. The authors wished to evaluate medication self-administration and MSA self-awareness in 24 consecutive acute stroke survivors undergoing inpatient rehabilitation, to determine if they would over-estimate their medication self-administration and if this predicted memory disorder. Stroke survivors were tested on the Hopkins Medication Schedule and also their memory, naming mood and dexterity were evaluated, comparing their performance to 17 matched controls. The anosognosia ratio indicated MSA over-estimation in stroke survivors compared with controls--no other over-estimation errors were noted relative to controls. A strong correlation was observed between over-estimation of MSA ability and verbal memory deficit, suggesting that formally assessing MSA and MSA self-awareness may help detect cognitive deficits. Assessing medication self-administration and MSA self-awareness may be useful in rehabilitation and successful community-return after stroke.

Cognitive ability predicts motor learning on a virtual reality game in patients with TBI.

PubMed

O'Neil, Rochelle L; Skeel, Reid L; Ustinova, Ksenia I

2013-01-01

Virtual reality games and simulations have been utilized successfully for motor rehabilitation of individuals with traumatic brain injury (TBI). Little is known, however, how TBI-related cognitive decline affects learning of motor tasks in virtual environments. To fill this gap, we examined learning within a virtual reality game involving various reaching motions in 14 patients with TBI and 15 healthy individuals with different cognitive abilities. All participants practiced ten 90-second gaming trials to assess various aspects of motor learning. Cognitive abilities were assessed with a battery of tests including measures of memory, executive functioning, and visuospatial ability. Overall, participants with TBI showed both reduced performance and a slower learning rate in the virtual reality game compared to healthy individuals. Numerous correlations between overall performance and several of the cognitive ability domains were revealed for both the patient and control groups, with the best predictor being overall cognitive ability. The results may provide a starting point for rehabilitation programs regarding which cognitive domains interact with motor learning.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women.

PubMed

Azagra, Rafael; Zwart, Marta; Encabo, Gloria; Aguyé, Amada; Martin-Sánchez, Juan Carlos; Puchol-Ruiz, Nuria; Gabriel-Escoda, Paula; Ortiz-Alinque, Sergio; Gené, Emilio; Iglesias, Milagros; Moriña, David; Diaz-Herrera, Miguel Angel; Utzet, Mireia; Manresa, Josep Maria

2016-06-17

The FRAX® tool estimates the risk of a fragility fracture among the population and many countries have been evaluating its performance among their populations since its creation in 2007. The purpose of this study is to update the first FRIDEX cohort analysis comparing FRAX with the bone mineral density (BMD) model, and its predictive abilities. The discriminatory ability of the FRAX was assessed using the 'area under curve' of the receiver operating characteristic (AUC-ROC). Predictive ability was assessed by comparing estimated risk fractures with incidence fractures after a 10-year follow up period. One thousand three hundred eight women ≥ 40 and ≤ 90 years followed up during a 10-year period. The AUC for major osteoporotic fractures using FRAX without DXA was 0.686 (95 % CI 0.630-0.742) and using FN T-score of DXA 0.714 (95 % CI 0.661-0.767). Using only the traditional parameters of DXA (FN T-score), the AUC was 0.706 (95 % CI 0.652-0.760). The AUC for hip osteoporotic fracture was 0.883 (95 % CI 0.827-0.938), 0.857 (95 % CI 0.773-0.941), and 0.814 (95 % CI 0.712-0.916) respectively. For major osteoporotic fractures, the overall predictive value using the ratio Observed fractures/Expected fractures calculated with FRAX without T-score of DXA was 2.29 and for hip fractures 2.28 and with the inclusion of the T-score 2.01 and 1.83 respectively. However, for hip fracture in women < 65 years was 1.53 and 1.24 respectively. The FRAX tool has been found to show a good discriminatory capacity for detecting women at high risk of fragility fracture, and is better for hip fracture than major fracture. The test of sensibility shows that it is, at least, not inferior than when using BMD model alone. The predictive capacity of FRAX tool needs some adjustment. This capacity is better for hip fracture prediction and better for women < 65 years. Further studies in Catalonia and other regions of Spain are needed to fine tune the FRAX tool's predictive capability.

Comparative evaluation of urinary PCA3 and TMPRSS2: ERG scores and serum PHI in predicting prostate cancer aggressiveness.

PubMed

Tallon, Lucile; Luangphakdy, Devillier; Ruffion, Alain; Colombel, Marc; Devonec, Marian; Champetier, Denis; Paparel, Philippe; Decaussin-Petrucci, Myriam; Perrin, Paul; Vlaeminck-Guillem, Virginie

2014-07-30

It has been suggested that urinary PCA3 and TMPRSS2:ERG fusion tests and serum PHI correlate to cancer aggressiveness-related pathological criteria at prostatectomy. To evaluate and compare their ability in predicting prostate cancer aggressiveness, PHI and urinary PCA3 and TMPRSS2:ERG (T2) scores were assessed in 154 patients who underwent radical prostatectomy for biopsy-proven prostate cancer. Univariate and multivariate analyses using logistic regression and decision curve analyses were performed. All three markers were predictors of a tumor volume≥0.5 mL. Only PHI predicted Gleason score≥7. T2 score and PHI were both independent predictors of extracapsular extension(≥pT3), while multifocality was only predicted by PCA3 score. Moreover, when compared to a base model (age, digital rectal examination, serum PSA, and Gleason sum at biopsy), the addition of both PCA3 score and PHI to the base model induced a significant increase (+12%) when predicting tumor volume>0.5 mL. PHI and urinary PCA3 and T2 scores can be considered as complementary predictors of cancer aggressiveness at prostatectomy.

Differences in the ability to predict and prepare for sexual activity between HIV-infected and HIV-uninfected young South African Women.

PubMed

Sadeghi, Rokhsanna; Alio, Amina; Bennie, Thola; Wallace, Melissa; Cai, Shubing; Abar, Beau; Bekker, Linda-Gail; Adler, David

2018-01-01

The Human Research Council's National HIV Prevalence, Incidence and Behavior Survey ranks South Africa first in HIV incidence in the world with 400,000 new infections in 2012 and found the HIV incidence rate among female youth aged 15 to 24 years to be 2.5% that year. The objective of this study was to compare the pattern and predictability of sexual activity between HIV-infected and HIV-uninfected young South African women. Sexually active young women between the ages of 16 and 21 years old completed a study survey between October 2012 and 2014 at two Desmond Tutu HIV Foundation centers. 100 young women with a mean age of 19.04 years responded to the survey. 51 women (51%) were HIV-infected and 49 were HIV-uninfected (49%). HIV-infected young women were found to be statistically less likely to have a temporal pattern to their sexual activity as compared to HIV-uninfected young women (56.9 vs. 95.9%, p<0.0001). While controlling for frequency of sex and lifetime sexual partners, HIV status remains a significant predictor of having a pattern of sexual activity (OR=16.13, p=0.0004) and a predictor of having sex on the weekend only (OR=4.41, p=0.0022). The ability to predict when sexual activity will occur enables a woman to prepare for its associated risks. HIV-uninfected young women are more likely to have a predictable pattern to their sexual activity as compared to HIV-infected young women. Knowledge of the sexual behavior patterns of this high-risk population will aid in the development of effective HIV prevention campaigns.

Analysis of Machine Learning Techniques for Heart Failure Readmissions.

PubMed

Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

2016-11-01

The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

Variability in wood-frame building damage using broad-band synthetic ground motions: a comparative numerical study with recorded motions

USGS Publications Warehouse

Pei, Shiling; van de Lindt, John W.; Hartzell, Stephen; Luco, Nicolas

2014-01-01

Earthquake damage to light-frame wood buildings is a major concern for North America because of the volume of this construction type. In order to estimate wood building damage using synthetic ground motions, we need to verify the ability of synthetically generated ground motions to simulate realistic damage for this structure type. Through a calibrated damage potential indicator, four different synthetic ground motion models are compared with the historically recorded ground motions at corresponding sites. We conclude that damage for sites farther from the fault (>20 km) is under-predicted on average and damage at closer sites is sometimes over-predicted.

Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis.

PubMed

Xie, Yuanchang; Lord, Dominique; Zhang, Yunlong

2007-09-01

Statistical models have frequently been used in highway safety studies. They can be utilized for various purposes, including establishing relationships between variables, screening covariates and predicting values. Generalized linear models (GLM) and hierarchical Bayes models (HBM) have been the most common types of model favored by transportation safety analysts. Over the last few years, researchers have proposed the back-propagation neural network (BPNN) model for modeling the phenomenon under study. Compared to GLMs and HBMs, BPNNs have received much less attention in highway safety modeling. The reasons are attributed to the complexity for estimating this kind of model as well as the problem related to "over-fitting" the data. To circumvent the latter problem, some statisticians have proposed the use of Bayesian neural network (BNN) models. These models have been shown to perform better than BPNN models while at the same time reducing the difficulty associated with over-fitting the data. The objective of this study is to evaluate the application of BNN models for predicting motor vehicle crashes. To accomplish this objective, a series of models was estimated using data collected on rural frontage roads in Texas. Three types of models were compared: BPNN, BNN and the negative binomial (NB) regression models. The results of this study show that in general both types of neural network models perform better than the NB regression model in terms of data prediction. Although the BPNN model can occasionally provide better or approximately equivalent prediction performance compared to the BNN model, in most cases its prediction performance is worse than the BNN model. In addition, the data fitting performance of the BPNN model is consistently worse than the BNN model, which suggests that the BNN model has better generalization abilities than the BPNN model and can effectively alleviate the over-fitting problem without significantly compromising the nonlinear approximation ability. The results also show that BNNs could be used for other useful analyses in highway safety, including the development of accident modification factors and for improving the prediction capabilities for evaluating different highway design alternatives.

Ability among adolescents for the metabolic syndrome to predict elevations in factors associated with type 2 diabetes and cardiovascular disease: data from the national health and nutrition examination survey 1999-2006.

PubMed

DeBoer, Mark D; Gurka, Matthew J

2010-08-01

The aim of this study was to compare currently proposed sets of pediatric metabolic syndrome criteria for the ability to predict elevations in "surrogate" factors that are associated with metabolic syndrome and with future cardiovascular disease and type 2 diabetes mellitus. These surrogate factors were fasting insulin, hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hsCRP), and uric acid. Waist circumference (WC), blood pressure, triglycerides, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, HbA1c, hsCRP, and uric acid measurements were obtained from 2,624 adolescent (12-18 years old) participants of the 1999-2006 National Health and Nutrition Examination Surveys. We identified children with metabolic syndrome as defined by six commonly used sets of pediatric metabolic syndrome criteria. We then defined elevations in the surrogate factors as values in the top 5% for the cohort and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each set of metabolic syndrome criteria and for each surrogate factor. Current pediatric metabolic syndrome criteria exhibited variable sensitivity and specificity for surrogate predictions. Metabolic syndrome criteria had the highest sensitivity for predicting fasting insulin (40-70%), followed by uric acid (31-54%), hsCRP (13-31%), and HbA1c (7-21%). The criteria of de Ferranti (which includes children with WC >75(th) percentile, compared to all other sets including children with WC >90(th) percentile) exhibited the highest sensitivity for predicting each of the surrogates, with only modest decrease in specificity compared to the other sets of criteria. However, the de Ferranti criteria also exhibited the lowest PPV values. Conversely, the pediatric International Diabetes Federation criteria exhibited the lowest sensitivity and the highest specificity. Pediatric metabolic syndrome criteria exhibit moderate sensitivity for detecting elevations in surrogate factors associated with metabolic syndrome and with risk for future disease. Inclusion of children with more modestly elevated WC improved sensitivity.

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients.

PubMed

Kontodimopoulos, Nick; Bozios, Panagiotis; Yfantopoulos, John; Niakas, Dimitris

2013-04-01

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined. A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D. The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states. This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.

Comparison of prognostic nomograms based on different nodal staging systems in patients with resected gastric cancer.

PubMed

Wang, Zi-Xian; Qiu, Miao-Zhen; Jiang, Yu-Ming; Zhou, Zhi-Wei; Li, Guo-Xin; Xu, Rui-Hua

2017-01-01

Purpose: Previous studies addressing the optimal nodal staging system in patients with resected gastric cancer have shown inconsistent results, and the optimal system for development of prognostic nomograms remains unclear. In this study, we compared prognostic nomograms based on the metastatic lymph node (MLN) count, lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS) to predict the 5-year overall survival in patients with resected gastric cancer. Methods: We analysed 15,320 patients with resected gastric cancer in the Surveillance, Epidemiology, and End Results (SEER) database between 1988 and 2010. Missing data were handled using multiple imputation. When assessed as a continuous covariate with restricted cubic splines, each MLN, LNR, and LODDS variable was incorporated into a nomogram with other significant prognosticators to predict the 5-year overall survival. A two-centre Chinese dataset (1,595 cases) was used as external validation data. Results: The discriminatory abilities of the MLN-, LNR-, and LODDS-based nomograms were comparable (concordance indices: 0.744, 0.741, and 0.744, respectively, in the SEER set, P > 0.152 for all pairwise comparisons; 0.715, 0.712, and 0.713, respectively, in the Chinese set, P > 0.445 for all pairwise comparisons). The discriminatory abilities of the three nomograms were all superior to the American Joint Committee on Cancer (AJCC) TNM classification (concordance indices: 0.713, P < 0.001 for all in the SEER set; and 0.693, P < 0.001 for all in the Chinese set). The discriminatory abilities of the nomograms were comparable regardless of the number of nodes examined. Moreover, decision curve analyses indicated similar net benefits of using the nomograms. Conclusion: MLN-, LNR-, and LODDS should be considered equally in the development of multivariate prognostic models and nomograms to refine the prediction of survival among patients with resected gastric cancer.

Young children's non-numerical ordering ability at the start of formal education longitudinally predicts their symbolic number skills and academic achievement in maths.

PubMed

O'Connor, Patrick A; Morsanyi, Kinga; McCormack, Teresa

2018-01-25

Ordinality is a fundamental feature of numbers and recent studies have highlighted the role that number ordering abilities play in mathematical development (e.g., Lyons et al., ), as well as mature mathematical performance (e.g., Lyons & Beilock, ). The current study tested the novel hypothesis that non-numerical ordering ability, as measured by the ordering of familiar sequences of events, also plays an important role in maths development. Ninety children were tested in their first school year and 87 were followed up at the end of their second school year, to test the hypothesis that ordinal processing, including the ordering of non-numerical materials, would be related to their maths skills both cross-sectionally and longitudinally. The results confirmed this hypothesis. Ordinal processing measures were significantly related to maths both cross-sectionally and longitudinally, and children's non-numerical ordering ability in their first year of school (as measured by order judgements for everyday events and the parents' report of their child's everyday ordering ability) was the strongest longitudinal predictor of maths one year later, when compared to several measures that are traditionally considered to be important predictors of early maths development. Children's everyday ordering ability, as reported by parents, also significantly predicted growth in formal maths ability between Year 1 and Year 2, although this was not the case for the event ordering task. The present study provides strong evidence that domain-general ordering abilities play an important role in the development of children's maths skills at the beginning of formal education. © 2018 John Wiley & Sons Ltd.

A comparator-hypothesis account of biased contingency detection.

PubMed

Vadillo, Miguel A; Barberia, Itxaso

2018-02-12

Our ability to detect statistical dependencies between different events in the environment is strongly biased by the number of coincidences between them. Even when there is no true covariation between a cue and an outcome, if the marginal probability of either of them is high, people tend to perceive some degree of statistical contingency between both events. The present paper explores the ability of the Comparator Hypothesis to explain the general pattern of results observed in this literature. Our simulations show that this model can account for the biasing effects of the marginal probabilities of cues and outcomes. Furthermore, the overall fit of the Comparator Hypothesis to a sample of experimental conditions from previous studies is comparable to that of the popular Rescorla-Wagner model. These results should encourage researchers to further explore and put to the test the predictions of the Comparator Hypothesis in the domain of biased contingency detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Finger gnosis predicts a unique but small part of variance in initial arithmetic performance.

PubMed

Wasner, Mirjam; Nuerk, Hans-Christoph; Martignon, Laura; Roesch, Stephanie; Moeller, Korbinian

2016-06-01

Recent studies indicated that finger gnosis (i.e., the ability to perceive and differentiate one's own fingers) is associated reliably with basic numerical competencies. In this study, we aimed at examining whether finger gnosis is also a unique predictor for initial arithmetic competencies at the beginning of first grade-and thus before formal math instruction starts. Therefore, we controlled for influences of domain-specific numerical precursor competencies, domain-general cognitive ability, and natural variables such as gender and age. Results from 321 German first-graders revealed that finger gnosis indeed predicted a unique and relevant but nevertheless only small part of the variance in initial arithmetic performance (∼1%-2%) as compared with influences of general cognitive ability and numerical precursor competencies. Taken together, these results substantiated the notion of a unique association between finger gnosis and arithmetic and further corroborate the theoretical idea of finger-based representations contributing to numerical cognition. However, the only small part of variance explained by finger gnosis seems to limit its relevance for diagnostic purposes. Copyright © 2016. Published by Elsevier Inc.

Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study.

PubMed

Poveda, Alaitz; Koivula, Robert W; Ahmad, Shafqat; Barroso, Inês; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Franks, Paul W

2016-03-01

We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

Pulmonary hypertension due to left heart disease: diagnostic and prognostic value of CT in chronic systolic heart failure.

PubMed

Colin, Geoffrey C; Gerber, Bernhard L; de Meester de Ravenstein, Christophe; Byl, David; Dietz, Anna; Kamga, Michele; Pasquet, Agnes; Vancraeynest, David; Vanoverschelde, Jean-Louis; D'Hondt, Anne-Marie; Ghaye, Benoit; Pouleur, Anne-Catherine

2018-05-14

To evaluate the ability of chest computed tomography (CT) to predict pulmonary hypertension (PH) and outcome in chronic heart failure with reduced ejection fraction (HFrEF). We reviewed 119 consecutive patients with HFrEF by CT, transthoracic echocardiography (TTE) and right heart catheterization (RHC). CT-derived pulmonary artery (PA) diameter and PA to ascending aorta diameter ratio (PA:A ratio), left atrial, right atrial, right ventricular (RV) and left ventricular volumes were correlated with RHC mean pulmonary arterial pressure (mPAP) . Diagnostic accuracy to predict PH and ability to predict primary composite endpoint of all-cause mortality and HF events were evaluated. RV volume was significantly higher in 81 patients with PH compared to 38 patients without PH (133 ml/m 2 vs. 79 ml/m 2 , p < 0.001) and was moderately correlated with mPAP (r=0.55, p < 0.001). Also, RV volume had higher ability to predict PH (area under the curve: 0.88) than PA diameter (0.79), PA:A ratio (0.76) by CT and tricuspid regurgitation gradient (0.83) and RV basal diameter by TTE (0.84, all p < 0.001). During the follow-up period (median: 3.4 years), 51 patients (43%) had HF events or died. After correction for important clinical, TTE and RHC parameters, RV volume (adjusted hazard ratio [HR]: 1.71, 95% CI 1.31-2.23, p < 0.001) and PA diameter (HR: 1.61, 95% CI 1.18-2.22, p = 0.003) were independent predictors of the primary endpoint. In patients with HFrEF, measurement of RV volume and PA diameter on ungated CT are non-invasive markers of PH and may help to predict the patient outcome. • Right ventricular (RV) volume measured by chest CT has good ability to identify pulmonary hypertension (PH) in patients with chronic heart failure (HF) and reduced ejection fraction (HFrEF). • The accuracy of pulmonary artery (PA) diameter and PA to ascending aorta diameter ratio (PA:A ratio) to predict PH was similar to previous studies, however, with lower cut-offs (28.1 mm and 0.92, respectively). • Chest CT-derived PA diameter and RV volume independently predict all-cause mortality and HF events and improve outcome prediction in patients with advanced HFrEF.

Inhibition and Updating, but Not Switching, Predict Developmental Dyslexia and Individual Variation in Reading Ability

PubMed Central

Doyle, Caoilainn; Smeaton, Alan F.; Roche, Richard A. P.; Boran, Lorraine

2018-01-01

To elucidate the core executive function profile (strengths and weaknesses in inhibition, updating, and switching) associated with dyslexia, this study explored executive function in 27 children with dyslexia and 29 age matched controls using sensitive z-mean measures of each ability and controlled for individual differences in processing speed. This study found that developmental dyslexia is associated with inhibition and updating, but not switching impairments, at the error z-mean composite level, whilst controlling for processing speed. Inhibition and updating (but not switching) error composites predicted both dyslexia likelihood and reading ability across the full range of variation from typical to atypical. The predictive relationships were such that those with poorer performance on inhibition and updating measures were significantly more likely to have a diagnosis of developmental dyslexia and also demonstrate poorer reading ability. These findings suggest that inhibition and updating abilities are associated with developmental dyslexia and predict reading ability. Future studies should explore executive function training as an intervention for children with dyslexia as core executive functions appear to be modifiable with training and may transfer to improved reading ability. PMID:29892245

Validation of the CRASH model in the prediction of 18-month mortality and unfavorable outcome in severe traumatic brain injury requiring decompressive craniectomy.

PubMed

Honeybul, Stephen; Ho, Kwok M; Lind, Christopher R P; Gillett, Grant R

2014-05-01

The goal in this study was to assess the validity of the corticosteroid randomization after significant head injury (CRASH) collaborators prediction model in predicting mortality and unfavorable outcome at 18 months in patients with severe traumatic brain injury (TBI) requiring decompressive craniectomy. In addition, the authors aimed to assess whether this model was well calibrated in predicting outcome across a wide spectrum of severity of TBI requiring decompressive craniectomy. This prospective observational cohort study included all patients who underwent a decompressive craniectomy following severe TBI at the two major trauma hospitals in Western Australia between 2004 and 2012 and for whom 18-month follow-up data were available. Clinical and radiological data on initial presentation were entered into the Web-based model and the predicted outcome was compared with the observed outcome. In validating the CRASH model, the authors used area under the receiver operating characteristic curve to assess the ability of the CRASH model to differentiate between favorable and unfavorable outcomes. The ability of the CRASH 6-month unfavorable prediction model to differentiate between unfavorable and favorable outcomes at 18 months after decompressive craniectomy was good (area under the receiver operating characteristic curve 0.85, 95% CI 0.80-0.90). However, the model's calibration was not perfect. The slope and the intercept of the calibration curve were 1.66 (SE 0.21) and -1.11 (SE 0.14), respectively, suggesting that the predicted risks of unfavorable outcomes were not sufficiently extreme or different across different risk strata and were systematically too high (or overly pessimistic), respectively. The CRASH collaborators prediction model can be used as a surrogate index of injury severity to stratify patients according to injury severity. However, clinical decisions should not be based solely on the predicted risks derived from the model, because the number of patients in each predicted risk stratum was still relatively small and hence the results were relatively imprecise. Notwithstanding these limitations, the model may add to a clinician's ability to have better-informed conversations with colleagues and patients' relatives about prognosis.

Do Teachers' Perceptions of Children's Math and Reading Related Ability and Effort Predict Children's Self-Concept of Ability in Math and Reading?

ERIC Educational Resources Information Center

Upadyaya, Katja; Eccles, Jacquelynne

2015-01-01

This study investigated to what extent primary school teachers' perceptions of their students' ability and effort predict developmental changes in children's self-concepts of ability in math and reading after controlling for students' academic performance and general intelligence. Three cohorts (N?=?849) of elementary school children and their…

Sensor fusion display evaluation using information integration models in enhanced/synthetic vision applications

NASA Technical Reports Server (NTRS)

Foyle, David C.

1993-01-01

Based on existing integration models in the psychological literature, an evaluation framework is developed to assess sensor fusion displays as might be implemented in an enhanced/synthetic vision system. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The pilot's performance with the sensor fusion image is compared to models' predictions based on the pilot's performance when viewing the original component sensor images prior to fusion. This allows for the determination as to when a sensor fusion system leads to: poorer performance than one of the original sensor displays, clearly an undesirable system in which the fused sensor system causes some distortion or interference; better performance than with either single sensor system alone, but at a sub-optimal level compared to model predictions; optimal performance compared to model predictions; or, super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays.

Self-regulating the effortful "social dos".

PubMed

Cortes, Kassandra; Kammrath, Lara K; Scholer, Abigail A; Peetz, Johanna

2014-03-01

In the current research, we explored differences in the self-regulation of the personal dos (i.e., engaging in active and effortful behaviors that benefit the self) and in the self-regulation of the social dos (engaging in those same effortful behaviors to benefit someone else). In 6 studies, we examined whether the same trait self-control abilities that predict task persistence on personal dos would also predict task persistence on social dos. That is, would the same behavior, such as persisting through a tedious and attentionally demanding task, show different associations with trait self-control when it is framed as benefitting the self versus someone else? In Studies 1-3, we directly compared the personal and social dos and found that trait self-control predicted self-reported and behavioral personal dos but not social dos, even when the behaviors were identical and when the incentives were matched. Instead, trait agreeableness--a trait linked to successful self-regulation within the social domain--predicted the social dos. Trait self-control did not predict the social dos even when task difficulty increased (Study 4), but it did predict the social don'ts, consistent with past research (Studies 5-6). The current studies provide support for the importance of distinguishing different domains of self-regulated behaviors and suggest that social dos can be successfully performed through routes other than traditional self-control abilities. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Usefulness of Midregional Proadrenomedullin to Predict Poor Outcome in Patients with Community Acquired Pneumonia

PubMed Central

Gordo-Remartínez, Susana; Sevillano-Fernández, José A.; Álvarez-Sala, Luis A.; Andueza-Lillo, Juan A.; de Miguel-Yanes, José M.

2015-01-01

Background midregional proadrenomedullin (MR-proADM) is a prognostic biomarker in patients with community-acquired pneumonia (CAP). We sought to confirm whether MR-proADM added to Pneumonia Severity Index (PSI) improves the potential prognostic value of PSI alone, and tested to what extent this combination could be useful in predicting poor outcome of patients with CAP in an Emergency Department (ED). Methods Consecutive patients diagnosed with CAP were enrolled in this prospective, single-centre, observational study. We analyzed the ability of MR-proADM added to PSI to predict poor outcome using receiver operating characteristic (ROC) curves, logistic regression and risk reclassification and comparing it with the ability of PSI alone. The primary outcome was “poor outcome”, defined as the incidence of an adverse event (ICU admission, hospital readmission, or mortality at 30 days after CAP diagnosis). Results 226 patients were included; 33 patients (14.6%) reached primary outcome. To predict primary outcome the highest area under curve (AUC) was found for PSI (0.74 [0.64-0.85]), which was not significantly higher than for MR-proADM (AUC 0.72 [0.63-0.81, p > 0.05]). The combination of PSI and MR-proADM failed to improve the predictive potential of PSI alone (AUC 0.75 [0.65-0.85, p=0.56]). Ten patients were appropriately reclassified when the combined PSI and MR-proADM model was used as compared with the model of PSI alone. Net reclassification improvement (NRI) index was statistically significant (7.69%, p = 0.03) with an improvement percentage of 3.03% (p = 0.32) for adverse event, and 4.66% (P = 0.02) for no adverse event. Conclusion MR-proADM in combination with PSI may be helpful in individual risk stratification for short-term poor outcome of CAP patients, allowing a better reclassification of patients compared with PSI alone. PMID:26030588

Left ventricular hypertrophy by ECG versus cardiac MRI as a predictor for heart failure.

PubMed

Oseni, Abdullahi O; Qureshi, Waqas T; Almahmoud, Mohamed F; Bertoni, Alain G; Bluemke, David A; Hundley, William G; Lima, Joao A C; Herrington, David M; Soliman, Elsayed Z

2017-01-01

To determine if there is a significant difference in the predictive abilities of left ventricular hypertrophy (LVH) detected by ECG-LVH versus LVH ascertained by cardiac MRI-LVH in a model similar to the Framingham Heart Failure Risk Score (FHFRS). This study included 4745 (mean age 61±10 years, 53.5% women, 61.7% non-whites) participants in the Multi-Ethnic Study of Atherosclerosis. ECG-LVH was defined using Cornell voltage product while MRI-LVH was derived from left ventricular mass. Cox proportional hazard regression was used to examine the association between ECG-LVH and MRI-LVH with incident heart failure (HF). Harrell's concordance C-index was used to estimate the predictive ability of the model when either ECG-LVH or MRI-LVH was included as one of its components. ECG-LVH was present in 291 (6.1%), while MRI-LVH was present in 499 (10.5%) of the participants. Both ECG-LVH (HR 2.25, 95% CI 1.38 to 3.69) and MRI-LVH (HR 3.80, 95% CI 1.56 to 5.63) were predictive of HF. The absolute risk of developing HF was 8.81% for MRI-LVH versus 2.26% for absence of MRI-LVH with a relative risk of 3.9. With ECG-LVH, the absolute risk of developing HF 6.87% compared with 2.69% for absence of ECG-LVH with a relative risk of 2.55. The ability of the model to predict HF was better with MRI-LVH (C-index 0.871, 95% CI 0.842 to 0.899) than with ECG-LVH (C-index 0.860, 95% CI 0.833 to 0.888) (p<0.0001). ECG-LVH and MRI-LVH are predictive of HF. Substituting MRI-LVH for ECG-LVH improves the predictive ability of a model similar to the FHFRS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

The Added Value of Collecting Information on Pain Experience When Predicting Time on Benefits for Injured Workers with Back Pain.

PubMed

Steenstra, Ivan A; Franche, Renée-Louise; Furlan, Andrea D; Amick, Ben; Hogg-Johnson, Sheilah

2016-06-01

Objectives Some injured workers with work-related, compensated back pain experience a troubling course in return to work. A prediction tool was developed in an earlier study, using administrative data only. This study explored the added value of worker reported data in identifying those workers with back pain at higher risk of being on benefits for a longer period of time. Methods This was a cohort study of workers with compensated back pain in 2005 in Ontario. Workplace Safety and Insurance Board (WSIB) data was used. As well, we examined the added value of patient-reported prognostic factors obtained from a prospective cohort study. Improvement of model fit was determined by comparing area under the curve (AUC) statistics. The outcome measure was time on benefits during a first workers' compensation claim for back pain. Follow-up was 2 years. Results Among 1442 workers with WSIB data still on full benefits at 4 weeks, 113 were also part of the prospective cohort study. Model fit of an established rule in the smaller dataset of 113 workers was comparable to the fit previously established in the larger dataset. Adding worker rating of pain at baseline improved the rule substantially (AUC = 0.80, 95 % CI 0.68, 0.91 compared to benefit status at 180 days, AUC = 0.88, 95 % CI 0.74, 1.00 compared to benefits status at 360 days). Conclusion Although data routinely collected by workers' compensation boards show some ability to predict prolonged time on benefits, adding information on experienced pain reported by the worker improves the predictive ability of the model from 'fairly good' to 'good'. In this study, a combination of prognostic factors, reported by multiple stakeholders, including the worker, could identify those at high risk of extended duration on disability benefits and in potentially in need of additional support at the individual level.

Ability of commonly used prediction equations to predict resting energy expenditure in children with inflammatory bowel disease.

PubMed

Hill, Rebecca J; Lewindon, Peter J; Withers, Geoffrey D; Connor, Frances L; Ee, Looi C; Cleghorn, Geoffrey J; Davies, Peter S W

2011-07-01

Paediatric onset inflammatory bowel disease (IBD) may cause alterations in energy requirements and invalidate the use of standard prediction equations. Our aim was to evaluate four commonly used prediction equations for resting energy expenditure (REE) in children with IBD. Sixty-three children had repeated measurements of REE as part of a longitudinal research study yielding a total of 243 measurements. These were compared with predicted REE from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict equations using the Bland-Altman method. Mean (±SD) age of the patients was 14.2 (2.4) years. Mean measured REE was 1566 (336) kcal per day compared with 1491 (236), 1441 (255), 1481 (232), and 1435 (212) kcal per day calculated from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict, respectively. While the Schofield equation demonstrated the least difference between measured and predicted REE, it, along with the other equations tested, did not perform uniformly across all subjects, indicating greater errors at either end of the spectrum of energy expenditure. Smaller differences were found for all prediction equations for Crohn's disease compared with ulcerative colitis. Of the commonly used equations, the equation of Schofield should be used in pediatric patients with IBD when measured values are not able to be obtained. Copyright © 2010 Crohn's & Colitis Foundation of America, Inc.

Noise Prediction of NASA SR2 Propeller in Transonic Conditions

NASA Astrophysics Data System (ADS)

Gennaro, Michele De; Caridi, Domenico; Nicola, Carlo De

2010-09-01

In this paper we propose a numerical approach for noise prediction of high-speed propellers for Turboprop applications. It is based on a RANS approach for aerodynamic simulation coupled with Ffowcs Williams-Hawkings (FW-H) Acoustic Analogy for propeller noise prediction. The test-case geometry adopted for this study is the 8-bladed NASA SR2 transonic cruise propeller, and simulated Sound Pressure Levels (SPL) have been compared with experimental data available from Wind Tunnel and Flight Tests for different microphone locations in a range of Mach numbers between 0.78 and 0.85 and rotational velocities between 7000 and 9000 rpm. Results show the ability of this approach to predict noise to within a few dB of experimental data. Moreover corrections are provided to be applied to acoustic numerical results in order for them to be compared with Wind Tunnel and Flight Test experimental data, as well computational grid requirements and guidelines in order to perform complete aerodynamic and aeroacoustic calculations with highly competitive computational cost.

Academic performance, career potential, creativity, and job performance: can one construct predict them all?

PubMed

Kuncel, Nathan R; Hezlett, Sarah A; Ones, Deniz S

2004-01-01

This meta-analysis addresses the question of whether 1 general cognitive ability measure developed for predicting academic performance is valid for predicting performance in both educational and work domains. The validity of the Miller Analogies Test (MAT; W. S. Miller, 1960) for predicting 18 academic and work-related criteria was examined. MAT correlations with other cognitive tests (e.g., Raven's Matrices [J. C. Raven, 1965]; Graduate Record Examinations) also were meta-analyzed. The results indicate that the abilities measured by the MAT are shared with other cognitive ability instruments and that these abilities are generalizably valid predictors of academic and vocational criteria, as well as evaluations of career potential and creativity. These findings contradict the notion that intelligence at work is wholly different from intelligence at school, extending the voluminous literature that supports the broad importance of general cognitive ability (g).

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

The Relationship between Social-Emotional Learning Ability and Perceived Social Support in Gifted Students

ERIC Educational Resources Information Center

Ogurlu, Üzeyir; Sevgi-Yalin, Hatun; Yavuz-Birben, Fazilet

2018-01-01

This study aimed to examine the relationship between social-emotional learning skills and perceived social support of gifted students. Based on this relationship, the authors also examined to what extent social and emotional learning skills were predictive of social support. In addition, gender variables were compared in social and emotional…

Size Matters: Early Vocabulary as a Predictor of Language and Literacy Competence

ERIC Educational Resources Information Center

Lee, Joanne

2011-01-01

This paper investigated the predictive ability of expressive vocabulary size and lexical composition at age 2 on later language and literacy skills from ages 3 through 11. Multivariate analysis of covariance was performed to compare 16 language and literacy outcomes between children with large expressive vocabulary size at 24 months (N = 1,073)…

The Relative Importance of Psychological Acceptance and Emotional Intelligence to Workplace Well-Being

ERIC Educational Resources Information Center

Donaldson-Feilder, Emma J.; Bond, Frank W.

2004-01-01

Psychological acceptance (acceptance) and emotional intelligence (EI) are two relatively new individual characteristics that are hypothesised to affect well-being and performance at work. This study compares both of them, in terms of their ability to predict various well-being outcomes (i.e. general mental health, physical well-being, and job…

Location and Lifestyle: The Comparative Explanatory Ability of Urbanism and Rurality

ERIC Educational Resources Information Center

Lowe, George D.; Peek, Charles W.

1974-01-01

The article focuses on 2 questions pivotal to the issue of rural-urban differences: 1) "Do attitudinal differences remain among the rural and urban residents independent of differences generated by other potent variables?"; and 2) "Will any increase in the predictive utility of rurality be generated by use of a composite definition (residence plus…

Comparing techniques for estimating flame temperature of prescribed fires

Treesearch

Deborah K. Kennard; Kenneth W. Outcalt; David Jones; Joseph J. O' Brien

2005-01-01

A variety of techniques that estimate temperature and/or heat output during fires are available. We assessed the predictive ability of metal and tile pyrometers, calorimeters of different sizes, and fuel consumption to time-temperature metrics derived from thick and thin thermocouples at 140 points distributed over 9 management-scale burns in a longleaf pine forest in...

A Longitudinal Comparison of Systems Used to Identify Subgroups of Learning Disabled Children.

ERIC Educational Resources Information Center

Goldstein, David; Dundon, William D.

This paper addresses the problem of heterogeneity of samples of learning disabled (LD) children by comparing five different systems for identifying homogeneous subgroups in terms of their ability to predict longitudinal reading and mathematics scores. One hundred and sixty LD children served as subjects. Three of the five subgrouping systems were…

Academic Self-Concept, Achievement Goals, and Achievement: Is Their Relation the Same for Academic Achievers and Underachievers?

ERIC Educational Resources Information Center

Preckel, Franzis; Brunner, Martin

2015-01-01

This longitudinal study investigated the contribution of achievement goals and academic self-concept for the prediction of unexpected academic achievement (i.e., achievement that is higher or lower than expected with respect to students' cognitive ability) in general and when comparing groups of extreme over- and underachievers. Our sample…

Dimensionality of brain networks linked to life-long individual differences in self-control.

PubMed

Berman, Marc G; Yourganov, Grigori; Askren, Mary K; Ayduk, Ozlem; Casey, B J; Gotlib, Ian H; Kross, Ethan; McIntosh, Anthony R; Strother, Stephen; Wilson, Nicole L; Zayas, Vivian; Mischel, Walter; Shoda, Yuichi; Jonides, John

2013-01-01

The ability to delay gratification in childhood has been linked to positive outcomes in adolescence and adulthood. Here we examine a subsample of participants from a seminal longitudinal study of self-control throughout a subject's life span. Self-control, first studied in children at age 4 years, is now re-examined 40 years later, on a task that required control over the contents of working memory. We examine whether patterns of brain activation on this task can reliably distinguish participants with consistently low and high self-control abilities (low versus high delayers). We find that low delayers recruit significantly higher-dimensional neural networks when performing the task compared with high delayers. High delayers are also more homogeneous as a group in their neural patterns compared with low delayers. From these brain patterns, we can predict with 71% accuracy, whether a participant is a high or low delayer. The present results suggest that dimensionality of neural networks is a biological predictor of self-control abilities.

Using an Informative Missing Data Model to Predict the Ability to Assess Recovery of Balance Control after Spaceflight

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Wood, Scott J.; Jain, Varsha

2008-01-01

Astronauts show degraded balance control immediately after spaceflight. To assess this change, astronauts' ability to maintain a fixed stance under several challenging stimuli on a movable platform is quantified by "equilibrium" scores (EQs) on a scale of 0 to 100, where 100 represents perfect control (sway angle of 0) and 0 represents data loss where no sway angle is observed because the subject has to be restrained from falling. By comparing post- to pre-flight EQs for actual astronauts vs. controls, we built a classifier for deciding when an astronaut has recovered. Future diagnostic performance depends both on the sampling distribution of the classifier as well as the distribution of its input data. Taking this into consideration, we constructed a predictive ROC by simulation after modeling P(EQ = 0) in terms of a latent EQ-like beta-distributed random variable with random effects.

The effects of Wechsler Intelligence Scale for Children-Fourth Edition cognitive abilities on math achievement.

PubMed

Parkin, Jason R; Beaujean, A Alexander

2012-02-01

This study used structural equation modeling to examine the effect of Stratum III (i.e., general intelligence) and Stratum II (i.e., Comprehension-Knowledge, Fluid Reasoning, Short-Term Memory, Processing Speed, and Visual Processing) factors of the Cattell-Horn-Carroll (CHC) cognitive abilities, as operationalized by the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003a) subtests, on Quantitative Knowledge, as operationalized by the Wechsler Individual Achievement Test, Second Edition (WIAT-II; Wechsler, 2002) subtests. Participants came from the WISC-IV/WIAT-II linking sample (n=550). We compared models that predicted Quantitative Knowledge using only Stratum III factors, only Stratum II factors, and both Stratum III and Stratum II factors. Results indicated that the model with only the Stratum III factor predicting Quantitative Knowledge best fit the data. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Genomic prediction using an iterative conditional expectation algorithm for a fast BayesC-like model.

PubMed

Dong, Linsong; Wang, Zhiyong

2018-06-11

Genomic prediction is feasible for estimating genomic breeding values because of dense genome-wide markers and credible statistical methods, such as Genomic Best Linear Unbiased Prediction (GBLUP) and various Bayesian methods. Compared with GBLUP, Bayesian methods propose more flexible assumptions for the distributions of SNP effects. However, most Bayesian methods are performed based on Markov chain Monte Carlo (MCMC) algorithms, leading to computational efficiency challenges. Hence, some fast Bayesian approaches, such as fast BayesB (fBayesB), were proposed to speed up the calculation. This study proposed another fast Bayesian method termed fast BayesC (fBayesC). The prior distribution of fBayesC assumes that a SNP with probability γ has a non-zero effect which comes from a normal density with a common variance. The simulated data from QTLMAS XII workshop and actual data on large yellow croaker were used to compare the predictive results of fBayesB, fBayesC and (MCMC-based) BayesC. The results showed that when γ was set as a small value, such as 0.01 in the simulated data or 0.001 in the actual data, fBayesB and fBayesC yielded lower prediction accuracies (abilities) than BayesC. In the actual data, fBayesC could yield very similar predictive abilities as BayesC when γ ≥ 0.01. When γ = 0.01, fBayesB could also yield similar results as fBayesC and BayesC. However, fBayesB could not yield an explicit result when γ ≥ 0.1, but a similar situation was not observed for fBayesC. Moreover, the computational speed of fBayesC was significantly faster than that of BayesC, making fBayesC a promising method for genomic prediction.

Video gaming enhances psychomotor skills but not visuospatial and perceptual abilities in surgical trainees.

PubMed

Kennedy, A M; Boyle, E M; Traynor, O; Walsh, T; Hill, A D K

2011-01-01

There is considerable interest in the identification and assessment of underlying aptitudes or innate abilities that could potentially predict excellence in the technical aspects of operating. However, before the assessment of innate abilities is introduced for high-stakes assessment (such as competitive selection into surgical training programs), it is essential to determine that these abilities are stable and unchanging and are not influenced by other factors, such as the use of video games. The aim of this study was to investigate whether experience playing video games will predict psychomotor performance on a laparoscopic simulator or scores on tests of visuospatial and perceptual abilities, and to examine the correlation, if any, between these innate abilities. Institutional ethical approval was obtained. Thirty-eight undergraduate medical students with no previous surgical experience were recruited. All participants completed a self-reported questionnaire that asked them to detail their video game experience. They then underwent assessment of their psychomotor, visuospatial, and perceptual abilities using previously validated tests. The results were analyzed using independent samples t tests to compare means and linear regression curves for subsequent analysis. Students who played video games for at least 7 hours per week demonstrated significantly better psychomotor skills than students who did not play video games regularly. However, there was no difference on measures of visuospatial and perceptual abilities. There was no correlation between psychomotor tests and visuospatial or perceptual tests. Regular video gaming correlates positively with psychomotor ability, but it does not seem to influence visuospatial or perceptual ability. This study suggests that video game experience might be beneficial to a future career in surgery. It also suggests that relevant surgical skills may be gained usefully outside the operating room in activities that are not related to surgery. Copyright © 2011 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Development of a Melanoma Risk Prediction Model Incorporating MC1R Genotype and Indoor Tanning Exposure: Impact of Mole Phenotype on Model Performance

PubMed Central

Penn, Lauren A.; Qian, Meng; Zhang, Enhan; Ng, Elise; Shao, Yongzhao; Berwick, Marianne; Lazovich, DeAnn; Polsky, David

2014-01-01

Background Identifying individuals at increased risk for melanoma could potentially improve public health through targeted surveillance and early detection. Studies have separately demonstrated significant associations between melanoma risk, melanocortin receptor (MC1R) polymorphisms, and indoor ultraviolet light (UV) exposure. Existing melanoma risk prediction models do not include these factors; therefore, we investigated their potential to improve the performance of a risk model. Methods Using 875 melanoma cases and 765 controls from the population-based Minnesota Skin Health Study we compared the predictive ability of a clinical melanoma risk model (Model A) to an enhanced model (Model F) using receiver operating characteristic (ROC) curves. Model A used self-reported conventional risk factors including mole phenotype categorized as “none”, “few”, “some” or “many” moles. Model F added MC1R genotype and measures of indoor and outdoor UV exposure to Model A. We also assessed the predictive ability of these models in subgroups stratified by mole phenotype (e.g. nevus-resistant (“none” and “few” moles) and nevus-prone (“some” and “many” moles)). Results Model A (the reference model) yielded an area under the ROC curve (AUC) of 0.72 (95% CI = 0.69, 0.74). Model F was improved with an AUC = 0.74 (95% CI = 0.71–0.76, p<0.01). We also observed substantial variations in the AUCs of Models A & F when examined in the nevus-prone and nevus-resistant subgroups. Conclusions These results demonstrate that adding genotypic information and environmental exposure data can increase the predictive ability of a clinical melanoma risk model, especially among nevus-prone individuals. PMID:25003831

Using Anisotropic 3D Minkowski Functionals for Trabecular Bone Characterization and Biomechanical Strength Prediction in Proximal Femur Specimens

PubMed Central

Nagarajan, Mahesh B.; De, Titas; Lochmüller, Eva-Maria; Eckstein, Felix; Wismüller, Axel

2017-01-01

The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk. PMID:29170581

External validity of two nomograms for predicting distant brain failure after radiosurgery for brain metastases in a bi-institutional independent patient cohort.

PubMed

Prabhu, Roshan S; Press, Robert H; Boselli, Danielle M; Miller, Katherine R; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Burri, Stuart H

2018-03-01

Patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) are at increased risk of distant brain failure (DBF). Two nomograms have been recently published to predict individualized risk of DBF after SRS. The goal of this study was to assess the external validity of these nomograms in an independent patient cohort. The records of consecutive patients with BM treated with SRS at Levine Cancer Institute and Emory University between 2005 and 2013 were reviewed. Three validation cohorts were generated based on the specific nomogram or recursive partitioning analysis (RPA) entry criteria: Wake Forest nomogram (n = 281), Canadian nomogram (n = 282), and Canadian RPA (n = 303) validation cohorts. Freedom from DBF at 1-year in the Wake Forest study was 30% compared with 50% in the validation cohort. The validation c-index for both the 6-month and 9-month freedom from DBF Wake Forest nomograms was 0.55, indicating poor discrimination ability, and the goodness-of-fit test for both nomograms was highly significant (p < 0.001), indicating poor calibration. The 1-year actuarial DBF in the Canadian nomogram study was 43.9% compared with 50.9% in the validation cohort. The validation c-index for the Canadian 1-year DBF nomogram was 0.56, and the goodness-of-fit test was also highly significant (p < 0.001). The validation accuracy and c-index of the Canadian RPA classification was 53% and 0.61, respectively. The Wake Forest and Canadian nomograms for predicting risk of DBF after SRS were found to have limited predictive ability in an independent bi-institutional validation cohort. These results reinforce the importance of validating predictive models in independent patient cohorts.

Do cravings predict smoking cessation in smokers calling a national quit line: secondary analyses from a randomised trial for the utility of 'urges to smoke' measures.

PubMed

Taggar, Jaspal S; Lewis, Sarah; Docherty, Graeme; Bauld, Linda; McEwen, Andy; Coleman, Tim

2015-04-14

Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28-50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation.

Measuring body composition in dogs using multifrequency bioelectrical impedance analysis and dual energy X-ray absorptiometry.

PubMed

Rae, L S; Vankan, D M; Rand, J S; Flickinger, E A; Ward, L C

2016-06-01

Thirty-five healthy, neutered, mixed breed dogs were used to determine the ability of multifrequency bioelectrical impedance analysis (MFBIA) to predict accurately fat-free mass (FFM) in dogs using dual energy X-ray absorptiometry (DXA)-measured FFM as reference. A second aim was to compare MFBIA predictions with morphometric predictions. MFBIA-based predictors provided an accurate measure of FFM, within 1.5% when compared to DXA-derived FFM, in normal weight dogs. FFM estimates were most highly correlated with DXA-measured FFM when the prediction equation included resistance quotient, bodyweight, and body condition score. At the population level, the inclusion of impedance as a predictor variable did not add substantially to the predictive power achieved with morphometric variables alone; in individual dogs, impedance predictors were more valuable than morphometric predictors. These results indicate that, following further validation, MFBIA could provide a useful tool in clinical practice to objectively measure FFM in canine patients and help improve compliance with prevention and treatment programs for obesity in dogs. Copyright © 2016. Published by Elsevier Ltd.

A comparison of life prediction methodologies for titanium matrix composites subjected to thermomechanical fatigue

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

Calcaterra, J.R.; Johnson, W.S.; Neu, R.W.

1997-12-31

Several methodologies have been developed to predict the lives of titanium matrix composites (TMCs) subjected to thermomechanical fatigue (TMF). This paper reviews and compares five life prediction models developed at NASA-LaRC. Wright Laboratories, based on a dingle parameter, the fiber stress in the load-carrying, or 0{degree}, direction. The two other models, both developed at Wright Labs. are multi-parameter models. These can account for long-term damage, which is beyond the scope of the single-parameter models, but this benefit is offset by the additional complexity of the methodologies. Each of the methodologies was used to model data generated at NASA-LeRC. Wright Labs.more » and Georgia Tech for the SCS-6/Timetal 21-S material system. VISCOPLY, a micromechanical stress analysis code, was used to determine the constituent stress state for each test and was used for each model to maintain consistency. The predictive capabilities of the models are compared, and the ability of each model to accurately predict the responses of tests dominated by differing damage mechanisms is addressed.« less

Effect of shaping sensor data on pilot response

NASA Technical Reports Server (NTRS)

Bailey, Roger M.

1990-01-01

The pilot of a modern jet aircraft is subjected to varying workloads while being responsible for multiple, ongoing tasks. The ability to associate the pilot's responses with the task/situation, by modifying the way information is presented relative to the task, could provide a means of reducing workload. To examine the feasibility of this concept, a real time simulation study was undertaken to determine whether preprocessing of sensor data would affect pilot response. Results indicated that preprocessing could be an effective way to tailor the pilot's response to displayed data. The effects of three transformations or shaping functions were evaluated with respect to the pilot's ability to predict and detect out-of-tolerance conditions while monitoring an electronic engine display. Two nonlinear transformations, on being the inverse of the other, were compared to a linear transformation. Results indicate that a nonlinear transformation that increases the rate-or-change of output relative to input tends to advance the prediction response and improve the detection response, while a nonlinear transformation that decreases the rate-of-change of output relative to input tends to lengthen the prediction response and make detection more difficult.

A Quantile Regression Approach to Understanding the Relations Between Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2015-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773

Predicting absenteeism: screening for work ability or burnout.

PubMed

Schouteten, R

2017-01-01

In determining the predictors of occupational health problems, two factors can be distinguished: personal (work ability) factors and work-related factors (burnout, job characteristics). However, these risk factors are hardly ever combined and it is not clear whether burnout or work ability best predicts absenteeism. To relate measures of work ability, burnout and job characteristics to absenteeism as the indicators of occupational health problems. Survey data on work ability, burnout and job characteristics from a Dutch university were related to the absenteeism data from the university's occupational health and safety database in the year following the survey study. The survey contained the Work Ability Index (WAI), Utrecht Burnout Scale (UBOS) and seven job characteristics from the Questionnaire on Experience and Evaluation of Work (QEEW). There were 242 employees in the study group. Logistic regression analyses revealed that job characteristics did not predict absenteeism. Exceptional absenteeism was most consistently predicted by the WAI dimensions 'employees' own prognosis of work ability in two years from now' and 'mental resources/vitality' and the burnout dimension 'emotional exhaustion'. Other significant predictors of exceptional absenteeism frequency included estimated work impairment due to diseases (WAI) and feelings of depersonalization or emotional distance from the work (burnout). Absenteeism among university personnel was best predicted by a combination of work ability and burnout. As a result, measures to prevent absenteeism and health problems may best be aimed at improving an individual's work ability and/or preventing the occurrence of burnout. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

USGS Publications Warehouse

Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

2015-08-24

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Individual differences in the benefits of feedback for learning.

PubMed

Kelley, Christopher M; McLaughlin, Anne Collins

2012-02-01

Research on learning from feedback has produced ambiguous guidelines for feedback design--some have advocated minimal feedback, whereas others have recommended more extensive feedback that highly supported performance. The objective of the current study was to investigate how individual differences in cognitive resources may predict feedback requirements and resolve previous conflicted findings. Cognitive resources were controlled for by comparing samples from populations with known differences, older and younger adults.To control for task demands, a simple rule-based learning task was created in which participants learned to identify fake Windows pop-ups. Pop-ups were divided into two categories--those that required fluid ability to identify and those that could be identified using crystallized intelligence. In general, results showed participants given higher feedback learned more. However, when analyzed by type of task demand, younger adults performed comparably with both levels of feedback for both cues whereas older adults benefited from increased feedbackfor fluid ability cues but from decreased feedback for crystallized ability cues. One explanation for the current findings is feedback requirements are connected to the cognitive abilities of the learner-those with higher abilities for the type of demands imposed by the task are likely to benefit from reduced feedback. We suggest the following considerations for feedback design: Incorporate learner characteristics and task demands when designing learning support via feedback.

The predictive performance of a path-dependent exotic-option credit risk model in the emerging market

NASA Astrophysics Data System (ADS)

Chen, Dar-Hsin; Chou, Heng-Chih; Wang, David; Zaabar, Rim

2011-06-01

Most empirical research of the path-dependent, exotic-option credit risk model focuses on developed markets. Taking Taiwan as an example, this study investigates the bankruptcy prediction performance of the path-dependent, barrier option model in the emerging market. We adopt Duan's (1994) [11], (2000) [12] transformed-data maximum likelihood estimation (MLE) method to directly estimate the unobserved model parameters, and compare the predictive ability of the barrier option model to the commonly adopted credit risk model, Merton's model. Our empirical findings show that the barrier option model is more powerful than Merton's model in predicting bankruptcy in the emerging market. Moreover, we find that the barrier option model predicts bankruptcy much better for highly-leveraged firms. Finally, our findings indicate that the prediction accuracy of the credit risk model can be improved by higher asset liquidity and greater financial transparency.

Cognitive capitalism: the effect of cognitive ability on wealth, as mediated through scientific achievement and economic freedom.

PubMed

Rindermann, Heiner; Thompson, James

2011-06-01

Traditional economic theories stress the relevance of political, institutional, geographic, and historical factors for economic growth. In contrast, human-capital theories suggest that peoples' competences, mediated by technological progress, are the deciding factor in a nation's wealth. Using three large-scale assessments, we calculated cognitive-competence sums for the mean and for upper- and lower-level groups for 90 countries and compared the influence of each group's intellectual ability on gross domestic product. In our cross-national analyses, we applied different statistical methods (path analyses, bootstrapping) and measures developed by different research groups to various country samples and historical periods. Our results underscore the decisive relevance of cognitive ability--particularly of an intellectual class with high cognitive ability and accomplishments in science, technology, engineering, and math--for national wealth. Furthermore, this group's cognitive ability predicts the quality of economic and political institutions, which further determines the economic affluence of the nation. Cognitive resources enable the evolution of capitalism and the rise of wealth.

Language Ability Predicts the Development of Behavior Problems in Children

PubMed Central

Petersen, Isaac T.; Bates, John E.; D’Onofrio, Brian M.; Coyne, Claire A.; Lansford, Jennifer E.; Dodge, Kenneth A.; Pettit, Gregory S.; Van Hulle, Carol A.

2013-01-01

Prior studies have suggested, but not fully established, that language ability is important for regulating attention and behavior. Language ability may have implications for understanding attention-deficit hyperactivity disorder (ADHD) and conduct disorders, as well as subclinical problems. This article reports findings from two longitudinal studies to test (a) whether language ability has an independent effect on behavior problems, and (b) the direction of effect between language ability and behavior problems. In Study 1 (N = 585), language ability was measured annually from ages 7 to 13 years by language subtests of standardized academic achievement tests administered at the children’s schools. Inattentive-hyperactive (I-H) and externalizing (EXT) problems were reported annually by teachers and mothers. In Study 2 (N = 11,506), language ability (receptive vocabulary) and mother-rated I-H and EXT problems were measured biannually from ages 4 to 12 years. Analyses in both studies showed that language ability predicted within-individual variability in the development of I-H and EXT problems over and above the effects of sex, ethnicity, socioeconomic status (SES), and performance in other academic and intellectual domains (e.g., math, reading comprehension, reading recognition, and short-term memory [STM]). Even after controls for prior levels of behavior problems, language ability predicted later behavior problems more strongly than behavior problems predicted later language ability, suggesting that the direction of effect may be from language ability to behavior problems. The findings suggest that language ability may be a useful target for the prevention or even treatment of attention deficits and EXT problems in children. PMID:23713507

External validation of preexisting first trimester preeclampsia prediction models.

PubMed

Allen, Rebecca E; Zamora, Javier; Arroyo-Manzano, David; Velauthar, Luxmilar; Allotey, John; Thangaratinam, Shakila; Aquilina, Joseph

2017-10-01

To validate the increasing number of prognostic models being developed for preeclampsia using our own prospective study. A systematic review of literature that assessed biomarkers, uterine artery Doppler and maternal characteristics in the first trimester for the prediction of preeclampsia was performed and models selected based on predefined criteria. Validation was performed by applying the regression coefficients that were published in the different derivation studies to our cohort. We assessed the models discrimination ability and calibration. Twenty models were identified for validation. The discrimination ability observed in derivation studies (Area Under the Curves) ranged from 0.70 to 0.96 when these models were validated against the validation cohort, these AUC varied importantly, ranging from 0.504 to 0.833. Comparing Area Under the Curves obtained in the derivation study to those in the validation cohort we found statistically significant differences in several studies. There currently isn't a definitive prediction model with adequate ability to discriminate for preeclampsia, which performs as well when applied to a different population and can differentiate well between the highest and lowest risk groups within the tested population. The pre-existing large number of models limits the value of further model development and future research should be focussed on further attempts to validate existing models and assessing whether implementation of these improves patient care. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Work-related stress, education and work ability among hospital nurses.

PubMed

Golubic, Rajna; Milosevic, Milan; Knezevic, Bojana; Mustajbegovic, Jadranka

2009-10-01

This paper is a report of a study conducted to determine which occupational stressors are present in nurses' working environment; to describe and compare occupational stress between two educational groups of nurses; to estimate which stressors and to what extent predict nurses' work ability; and to determine if educational level predicts nurses' work ability. Nurses' occupational stress adversely affects their health and nursing quality. Higher educational level has been shown to have positive effects on the preservation of good work ability. A cross-sectional study was conducted in 2006-2007. Questionnaires were distributed to a convenience sample of 1392 (59%) nurses employed at four university hospitals in Croatia (n = 2364). The response rate was 78% (n = 1086). Data were collected using the Occupational Stress Assessment Questionnaire and Work Ability Index Questionnaire. We identified six major groups of occupational stressors: 'Organization of work and financial issues', 'public criticism', 'hazards at workplace', 'interpersonal conflicts at workplace', 'shift work' and 'professional and intellectual demands'. Nurses with secondary school qualifications perceived Hazards at workplace and Shift work as statistically significantly more stressful than nurses a with college degree. Predictors statistically significantly related with low work ability were: Organization of work and financial issues (odds ratio = 1.69, 95% confidence interval 122-236), lower educational level (odds ratio = 1.69, 95% confidence interval 122-236) and older age (odds ratio = 1.07, 95% confidence interval 1.05-1.09). Hospital managers should develop strategies to address and improve the quality of working conditions for nurses in Croatian hospitals. Providing educational and career prospects can contribute to decreasing nurses' occupational stress levels, thus maintaining their work ability.

No difference in the competitive ability of introduced and native Trifolium provenances when grown with soil biota from their introduced and native ranges

PubMed Central

Shelby, Natasha; Hulme, Philip E.; van der Putten, Wim H.; McGinn, Kevin J.; Weser, Carolin; Duncan, Richard P.

2016-01-01

The evolution of increased competitive ability (EICA) hypothesis could explain why some introduced plant species perform better outside their native ranges. The EICA hypothesis proposes that introduced plants escape specialist pathogens or herbivores leading to selection for resources to be reallocated away from defence and towards greater competitive ability. We tested the hypothesis that escape from soil-borne enemies has led to increased competitive ability in three non-agricultural Trifolium (Fabaceae) species native to Europe that were introduced to New Zealand in the 19th century. Trifolium performance is intimately tied to rhizosphere biota. Thus, we grew plants from one introduced (New Zealand) and two native (Spain and the UK) provenances for each of three species in pots inoculated with soil microbiota collected from the rhizosphere beneath conspecifics in the introduced and native ranges. Plants were grown singly and in competition with conspecifics from a different provenance in order to compare competitive ability in the presence of different microbial communities. In contrast to the predictions of the EICA hypothesis, we found no difference in the competitive ability of introduced and native provenances when grown with soil microbiota from either the native or introduced range. Although plants from introduced provenances of two species grew more slowly than native provenances in native-range soils, as predicted by the EICA hypothesis, plants from the introduced provenance were no less competitive than native conspecifics. Overall, the growth rate of plants grown singly was a poor predictor of their competitive ability, highlighting the importance of directly quantifying plant performance in competitive scenarios, rather than relying on surrogate measures such as growth rate. PMID:26969431

Osteogenesis imperfecta in childhood: prognosis for walking.

PubMed

Engelbert, R H; Uiterwaal, C S; Gulmans, V A; Pruijs, H; Helders, P J

2000-09-01

We studied the predicted value of disease-related characteristics for the ability of children with osteogenesis imperfecta (OI) to walk. The severity of OI was classified according to Sillence. The parents were asked to report the age at which the child achieved motor milestones, the fracture incidence, and the age and localization of the first surgical intervention. The present main means of mobility was classified according to Bleck. There were 76 replies to the 98 questionnaires, of which 70 were included (type I, 41; type III, 11; type IV, 18). The type of OI was strongly associated with current walking ability, as was the presence of dentinogenesis imperfecta. Patients with type III and IV had a lower chance of ultimately walking compared with those with type I. Children with more than 2 intramedullary rods in the lower extremities had a reduced chance of walking than patients without rods. Rolling over before 8 months, unsupported sitting before 9 months, the ability to get in sitting position without support before 12 months, and the ability to get in a standing position without support before 12 months showed positive odds ratios. In Bleck > or = 4, multivariate analysis revealed that only the presence of rodding (yes/no) in the lower extremities had additional predictive value to the type of OI. The presence of dentinogenesis imperfecta and rodding (yes/no) had additional value in Bleck > or = 5. The type of OI is the single most important clinical indicator of the ultimate ability to walk. Information about motor development adds little. The early achievement of motor milestones contributes to the ability of independent walking when the type of OI is uncertain. Intramedullary rodding of the lower extremities is primarily related to the severity of the disease and in this way provides consequences for the ability to walk.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Forecast cooling of the Atlantic subpolar gyre and associated impacts.

PubMed

Hermanson, Leon; Eade, Rosie; Robinson, Niall H; Dunstone, Nick J; Andrews, Martin B; Knight, Jeff R; Scaife, Adam A; Smith, Doug M

2014-07-28

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate.

Linear genetic programming application for successive-station monthly streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

Empirical comparison between different methods for genomic prediction of number of piglets born alive in moderate sized breeding populations.

PubMed

Fangmann, A; Sharifi, R A; Heinkel, J; Danowski, K; Schrade, H; Erbe, M; Simianer, H

2017-04-01

Currently used multi-step methods to incorporate genomic information in the prediction of breeding values (BV) implicitly involve many assumptions which, if violated, may result in loss of information, inaccuracies and bias. To overcome this, single-step genomic best linear unbiased prediction (ssGBLUP) was proposed combining pedigree, phenotype and genotype of all individuals for genetic evaluation. Our objective was to implement ssGBLUP for genomic predictions in pigs and to compare the accuracy of ssGBLUP with that of multi-step methods with empirical data of moderately sized pig breeding populations. Different predictions were performed: conventional parent average (PA), direct genomic value (DGV) calculated with genomic BLUP (GBLUP), a GEBV obtained by blending the DGV with PA, and ssGBLUP. Data comprised individuals from a German Landrace (LR) and Large White (LW) population. The trait 'number of piglets born alive' (NBA) was available for 182,054 litters of 41,090 LR sows and 15,750 litters from 4534 LW sows. The pedigree contained 174,021 animals, of which 147,461 (26,560) animals were LR (LW) animals. In total, 526 LR and 455 LW animals were genotyped with the Illumina PorcineSNP60 BeadChip. After quality control and imputation, 495 LR (424 LW) animals with 44,368 (43,678) SNP on 18 autosomes remained for the analysis. Predictive abilities, i.e., correlations between de-regressed proofs and genomic BV, were calculated with a five-fold cross validation and with a forward prediction for young genotyped validation animals born after 2011. Generally, predictive abilities for LR were rather small (0.08 for GBLUP, 0.19 for GEBV and 0.18 for ssGBLUP). For LW, ssGBLUP had the greatest predictive ability (0.45). For both breeds, assessment of reliabilities for young genotyped animals indicated that genomic prediction outperforms PA with ssGBLUP providing greater reliabilities (0.40 for LR and 0.32 for LW) than GEBV (0.35 for LR and 0.29 for LW). Grouping of animals according to information sources revealed that genomic prediction had the highest potential benefit for genotyped animals without their own phenotype. Although, ssGBLUP did not generally outperform GBLUP or GEBV, the results suggest that ssGBLUP can be a useful and conceptually convincing approach for practical genomic prediction of NBA in moderately sized LR and LW populations.

Models for short term malaria prediction in Sri Lanka

PubMed Central

Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

2008-01-01

Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Improving Genomic Prediction in Cassava Field Experiments by Accounting for Interplot Competition

PubMed Central

Elias, Ani A.; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2018-01-01

Plants competing for available resources is an unavoidable phenomenon in a field. We conducted studies in cassava (Manihot esculenta Crantz) in order to understand the pattern of this competition. Taking into account the competitive ability of genotypes while selecting parents for breeding advancement or commercialization can be very useful. We assumed that competition could occur at two levels: (i) the genotypic level, which we call interclonal, and (ii) the plot level irrespective of the type of genotype, which we call interplot competition or competition error. Modification in incidence matrices was applied in order to relate neighboring genotype/plot to the performance of a target genotype/plot with respect to its competitive ability. This was added into a genomic selection (GS) model to simultaneously predict the direct and competitive ability of a genotype. Predictability of the models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error (pRMSE) compared to that of the base model having no competitive component. Results from our real data studies indicated that <10% increase in accuracy was achieved with GS-interclonal competition model, but this value reached up to 25% with a GS-competition error model. We also found that the competitive influence of a cassava clone is not just limited to the adjacent neighbors but spreads beyond them. Through simulations, we found that a 26% increase of accuracy in estimating trait genotypic effect can be achieved even in the presence of high competitive variance. PMID:29358232

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

PubMed

Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

2013-12-01

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Improving Genomic Prediction in Cassava Field Experiments by Accounting for Interplot Competition.

PubMed

Elias, Ani A; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2018-03-02

Plants competing for available resources is an unavoidable phenomenon in a field. We conducted studies in cassava ( Manihot esculenta Crantz) in order to understand the pattern of this competition. Taking into account the competitive ability of genotypes while selecting parents for breeding advancement or commercialization can be very useful. We assumed that competition could occur at two levels: (i) the genotypic level, which we call interclonal, and (ii) the plot level irrespective of the type of genotype, which we call interplot competition or competition error. Modification in incidence matrices was applied in order to relate neighboring genotype/plot to the performance of a target genotype/plot with respect to its competitive ability. This was added into a genomic selection (GS) model to simultaneously predict the direct and competitive ability of a genotype. Predictability of the models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error (pRMSE) compared to that of the base model having no competitive component. Results from our real data studies indicated that <10% increase in accuracy was achieved with GS-interclonal competition model, but this value reached up to 25% with a GS-competition error model. We also found that the competitive influence of a cassava clone is not just limited to the adjacent neighbors but spreads beyond them. Through simulations, we found that a 26% increase of accuracy in estimating trait genotypic effect can be achieved even in the presence of high competitive variance. Copyright © 2018 Elias et al.

Simulation of 2D Granular Hopper Flow

NASA Astrophysics Data System (ADS)

Li, Zhusong; Shattuck, Mark

2012-02-01

Jamming and intermittent granular flow are big problems in industry, and the vertical hopper is a canonical example of these difficulties. We simulate gravity driven flow and jamming of 2D disks in a vertical hopper and compare with identical companion experiments presented in this session. We measure and compare the flow rate and probability for jamming as a function of particle properties and geometry. We evaluate the ability of standard Hertz-Mindlin contact mode to quantitatively predict the experimental flow.

Bilateral versus unilateral cochlear implants in children: a study of spoken language outcomes.

PubMed

Sarant, Julia; Harris, David; Bennet, Lisa; Bant, Sharyn

2014-01-01

Although it has been established that bilateral cochlear implants (CIs) offer additional speech perception and localization benefits to many children with severe to profound hearing loss, whether these improved perceptual abilities facilitate significantly better language development has not yet been clearly established. The aims of this study were to compare language abilities of children having unilateral and bilateral CIs to quantify the rate of any improvement in language attributable to bilateral CIs and to document other predictors of language development in children with CIs. The receptive vocabulary and language development of 91 children was assessed when they were aged either 5 or 8 years old by using the Peabody Picture Vocabulary Test (fourth edition), and either the Preschool Language Scales (fourth edition) or the Clinical Evaluation of Language Fundamentals (fourth edition), respectively. Cognitive ability, parent involvement in children's intervention or education programs, and family reading habits were also evaluated. Language outcomes were examined by using linear regression analyses. The influence of elements of parenting style, child characteristics, and family background as predictors of outcomes were examined. Children using bilateral CIs achieved significantly better vocabulary outcomes and significantly higher scores on the Core and Expressive Language subscales of the Clinical Evaluation of Language Fundamentals (fourth edition) than did comparable children with unilateral CIs. Scores on the Preschool Language Scales (fourth edition) did not differ significantly between children with unilateral and bilateral CIs. Bilateral CI use was found to predict significantly faster rates of vocabulary and language development than unilateral CI use; the magnitude of this effect was moderated by child age at activation of the bilateral CI. In terms of parenting style, high levels of parental involvement, low amounts of screen time, and more time spent by adults reading to children facilitated significantly better vocabulary and language outcomes. In terms of child characteristics, higher cognitive ability and female sex were predictive of significantly better language outcomes. When family background factors were examined, having tertiary-educated primary caregivers and a family history of hearing loss were significantly predictive of better outcomes. Birth order was also found to have a significant negative effect on both vocabulary and language outcomes, with each older sibling predicting a 5 to 10% decrease in scores. Children with bilateral CIs achieved significantly better vocabulary outcomes, and 8-year-old children with bilateral CIs had significantly better language outcomes than did children with unilateral CIs. These improvements were moderated by children's ages at both first and second CIs. The outcomes were also significantly predicted by a number of factors related to parenting, child characteristics, and family background. Fifty-one percent of the variance in vocabulary outcomes and between 59 to 69% of the variance in language outcomes was predicted by the regression models.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

The Association of CHA2DS2-VASc Score and Blood Biomarkers with Ischemic Stroke Outcomes: The Belgrade Stroke Study

PubMed Central

Potpara, Tatjana S.; Polovina, Marija M.; Djikic, Dijana; Marinkovic, Jelena M.; Kocev, Nikola; Lip, Gregory Y. H.

2014-01-01

Background Many blood biomarkers have a positive association with stroke outcome, but adding blood biomarkers to the National Institutes of Health Stroke Scale (NIHSS) did not significantly improve its discriminatory ability. We investigated the association of the CHA2DS2-VASc score with unfavourable functional outcome (defined as a 30-day modified Rankin Scale [mRS] ≥3) in patients presenting with acute ischemic stroke (AIS), and examined whether the addition of blood biomarkers (troponin I [TnI], fibrinogen, C-reactive protein [CRP]) affects the model discriminatory ability. Methods We conducted an observational single-centre study of consecutive patients with AIS. All patients were admitted to hospital within 24 hours from the neurological symptoms onset. Results Of 240 patients (mean age 70.0±8.9 years), unfavourable 30-day outcome occurred in 92 (38.3%). Patients with mRS≥3 were older and more likely to have atrial fibrillation or other comorbidities (all p<0.001). They had higher levels of CRP, fibrinogen, TnI and higher CHA2DS2-VASc and CHADS2 scores (all p<0.05). The adjusted CHA2DS2-VASc score had excellent predictive ability for poor stroke outcome (c-statistic 0.982;95%CI,0.964–1.000, p<0.001). Whilst CRP had the highest sensitivity (83.7%), cardiac TnI was the most specific (97.3%) for prediction of poor stroke outcome (cut-off: >0.09µg/L). Compared with each of these biomarkers, CHA2DS2-VASc score had significantly better predictive ability for poor stroke outcome (c-statistic for CRP, Fibrinogen and TnI was 0.853;95%CI,0.802–0.895, 0.848;95%CI,0.796–0.891, and 0.792;95%CI,0.736–0.842, all p<0.001, respectively, versus 0.932;95%CI,0.892–0.960, p<0.001 for the CHA2DS2-VASc, all p for the comparisons<0.01). There was no significant difference in the predictive ability of the CHA2DS2-VASc score vs. combinations of the CHA2DS2-VASc and TnI or TnI, fibrinogen and CRP (z statistic 0.369, p = 0.7119; integrated discrimination index 0.00801 and 0.00172, respectively, both p>0.05). Conclusions The CHA2DS2-VASc score alone reliably predicts 30-day unfavourable outcome of stroke. Adding blood biomarkers to the CHA2DS2-VASc score did not significantly increase the predictive ability of the model. PMID:25184809

Process fault detection and nonlinear time series analysis for anomaly detection in safeguards

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

Burr, T.L.; Mullen, M.F.; Wangen, L.E.

In this paper we discuss two advanced techniques, process fault detection and nonlinear time series analysis, and apply them to the analysis of vector-valued and single-valued time-series data. We investigate model-based process fault detection methods for analyzing simulated, multivariate, time-series data from a three-tank system. The model-predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). We evaluate two methods, testing all individual residuals with a univariate z-score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect lossmore » of material from two different leak scenarios from the three-tank system: a leak without and with replacement of the lost volume. Nonlinear time-series analysis tools were compared with the linear methods popularized by Box and Jenkins. We compare prediction results using three nonlinear and two linear modeling methods on each of six simulated time series: two nonlinear and four linear. The nonlinear methods performed better at predicting the nonlinear time series and did as well as the linear methods at predicting the linear values.« less

Avoidance of Emotionally Arousing Stimuli Predicts Social-Perceptual Impairment in Asperger's Syndrome

ERIC Educational Resources Information Center

Corden, Ben; Chilvers, Rebecca; Skuse, David

2008-01-01

We combined eye-tracking technology with a test of facial affect recognition and a measure of self-reported social anxiety in order to explore the aetiology of social-perceptual deficits in Asperger's syndrome (AS). Compared to controls matched for age, IQ and visual-perceptual ability, we found a group of AS adults was impaired in their…

Can Medical Students Accurately Predict Their Learning? A Study Comparing Perceived and Actual Performance in Neuroanatomy

ERIC Educational Resources Information Center

Hall, Samuel R.; Stephens, Jonny R.; Seaby, Eleanor G.; Andrade, Matheus Gesteira; Lowry, Andrew F.; Parton, Will J. C.; Smith, Claire F.; Border, Scott

2016-01-01

It is important that clinicians are able to adequately assess their level of knowledge and competence in order to be safe practitioners of medicine. The medical literature contains numerous examples of poor self-assessment accuracy amongst medical students over a range of subjects however this ability in neuroanatomy has yet to be observed. Second…

Brief Report: Inhibition of Return in Young People with Autism and Asperger's Disorder

ERIC Educational Resources Information Center

Rinehart, Nicole J.; Bradshaw, John L.; Moss, Simon A.; Brereton, Avril V.; Tonge, Bruce J.

2008-01-01

The aim of this study was to investigate whether the superior search abilities observed in autism/Asperger's disorder may in part be a consequence of a more pronounced inhibition of return (IOR). Contrary to our prediction, IOR in individuals with autism was comparable to the matched comparison group. However, the autism group committed more false…

Models of vegetation change for landscape planning: a comparison of FETM, LANDSUM, SIMPPLLE, and VDDT

Treesearch

T. M. Barrett

2001-01-01

Landscape assessment and planning often depend on the ability to predict change of vegetation. This report compares four modeling systems (FETM, LANDSUM, SIMPPLLE, and VDDT) that can be used to understand changes resulting from succession, natural disturbance, and management activities. The four models may be useful for regional or local assessments in National Forest...

The Role of RAN and Reading Rate in Predicting Reading Self-Concept

ERIC Educational Resources Information Center

Kasperski, Ronen; Shany, Michal; Katzir, Tami

2016-01-01

Social identity theory states that a person's self-concept is created from comparison with others (Walsh & Gordon, 2008). In the case of reading, oral reading is a salient feature young children have to compare themselves on to their classroom peer group. The current study was set to explore the ability of oral reading tasks such as rapid…

Longitudinal Trajectories of Gestural and Linguistic Abilities in Very Preterm Infants in the Second Year of Life

ERIC Educational Resources Information Center

Sansavini, Alessandra; Guarini, Annalisa; Savini, Silvia; Broccoli, Serena; Justice, Laura; Alessandroni, Rosina; Faldella, Giacomo

2011-01-01

The present study involved a systematic longitudinal analysis, with three points of assessment in the second year of life, of gestures/actions, word comprehension, and word production in a sample of very preterm infants compared to a sample of full-term infants. The relationships among these competencies as well as their predictive value on…

Simulated effects of forest management alternatives on landscape structure and habitat suitability in the Midwestern United States

Treesearch

Stephen R. Shifley; Frank R., III Thompson; William D. Dijak; Michael A. Larson; Joshua J. Millspaugh

2006-01-01

Understanding the cumulative effects and resource trade-offs associated with forest management requires the ability to predict, analyze, and communicate information about how forest landscapes (1000s to > 100,000 ha in extent) respond to silviculture and other disturbances. We applied a spatially explicit landscape simulation model, LANDIS, and compared the outcomes...

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.

The evolution of intelligence in mammalian carnivores.

PubMed

Holekamp, Kay E; Benson-Amram, Sarah

2017-06-06

Although intelligence should theoretically evolve to help animals solve specific types of problems posed by the environment, it is unclear which environmental challenges favour enhanced cognition, or how general intelligence evolves along with domain-specific cognitive abilities. The social intelligence hypothesis posits that big brains and great intelligence have evolved to cope with the labile behaviour of group mates. We have exploited the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas to test predictions of the social intelligence hypothesis in regard to both cognition and brain size. Behavioural data indicate that there has been considerable convergence between primates and hyaenas with respect to their social cognitive abilities. Moreover, compared with other hyaena species, spotted hyaenas have larger brains and expanded frontal cortex, as predicted by the social intelligence hypothesis. However, broader comparative study suggests that domain-general intelligence in carnivores probably did not evolve in response to selection pressures imposed specifically in the social domain. The cognitive buffer hypothesis, which suggests that general intelligence evolves to help animals cope with novel or changing environments, appears to offer a more robust explanation for general intelligence in carnivores than any hypothesis invoking selection pressures imposed strictly by sociality or foraging demands.

The evolution of intelligence in mammalian carnivores

PubMed Central

Benson-Amram, Sarah

2017-01-01

Although intelligence should theoretically evolve to help animals solve specific types of problems posed by the environment, it is unclear which environmental challenges favour enhanced cognition, or how general intelligence evolves along with domain-specific cognitive abilities. The social intelligence hypothesis posits that big brains and great intelligence have evolved to cope with the labile behaviour of group mates. We have exploited the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas to test predictions of the social intelligence hypothesis in regard to both cognition and brain size. Behavioural data indicate that there has been considerable convergence between primates and hyaenas with respect to their social cognitive abilities. Moreover, compared with other hyaena species, spotted hyaenas have larger brains and expanded frontal cortex, as predicted by the social intelligence hypothesis. However, broader comparative study suggests that domain-general intelligence in carnivores probably did not evolve in response to selection pressures imposed specifically in the social domain. The cognitive buffer hypothesis, which suggests that general intelligence evolves to help animals cope with novel or changing environments, appears to offer a more robust explanation for general intelligence in carnivores than any hypothesis invoking selection pressures imposed strictly by sociality or foraging demands. PMID:28479979

Masking ability of bi- and tri- laminate all-ceramic veneers on tooth-colored ceramic discs.

PubMed

Farhan, Daniel; Sukumar, Smitha; von Stein-Lausnitz, Axel; Aarabi, Ghazal; Alawneh, Ahmad; Reissmann, Daniel R

2014-01-01

A predictable esthetic outcome is imperative when placing ceramic veneers. Discolored teeth pose a major challenge as sufficient material thickness is required to achieve a good esthetic result. There is limited evidence in the literature that compares the masking ability of multi-laminate veneers. The aim of this in-vitro study was to compare the masking ability of bi-laminate (BL) and tri-laminate (TL) all-ceramic veneers cemented on tooth-colored ceramic discs. A total of 40 veneers (shade A1, 10-mm diameter, 0.8-mm thick) were manufactured-20 BL veneers (0.4-mm pressable ceramic coping veneered with 0.4-mm thick enamel layer) and 20 TL veneers (0.4-mm coping veneered with 0.2-mm thick opaque interlayer and 0.2-mm thick enamel layer). A bonding apparatus was utilized to adhesively cement all veneers on the ceramic discs (shade A1), simulating teeth of light and dark color. The resulting groups (N = 10 each) were the reference groups (shade A1 ceramic base) BL-1 and TL-1 veneers, and the test groups (shade A4 ceramic base) BL-4 and TL-4 veneers. The color of the cemented veneers was measured using a spectrophotometer. The data were converted to CIE L*a*b* coordinates, and ΔE* were calculated to allow for statistical analysis. The color differences between the samples with the A1 and A4 ceramic bases were significantly lower when covered with TL veneers (mean ΔE*: 3.2 units) than with BL veneers (mean ΔE*: 4.0 units: p < 0.001), indicating a better masking ability of the TL veneers. The 0.8-mm thick TL veneer was able to mask darker tooth-colored ceramic disc within clinically acceptable limits. Increased understanding of the masking ability of ceramics and of color science is necessary in these esthetically aware times. Providing tri-laminate veneers for darker colored teeth seems to result in more predictable esthetical results than when using bi-laminate veneers. Patients with discolored/darker teeth may benefit from a more predictable esthetic result when teeth restored with tri-laminate rather than bi-laminate veneers. © 2014 Wiley Periodicals, Inc.

Musical Competence is Predicted by Music Training, Cognitive Abilities, and Personality.

PubMed

Swaminathan, Swathi; Schellenberg, E Glenn

2018-06-15

Individuals differ in musical competence, which we defined as the ability to perceive, remember, and discriminate sequences of tones or beats. We asked whether such differences could be explained by variables other than music training, including socioeconomic status (SES), short-term memory, general cognitive ability, and personality. In a sample of undergraduates, musical competence had positive simple associations with duration of music training, SES, short-term memory, general cognitive ability, and openness-to-experience. When these predictors were considered jointly, musical competence had positive partial associations with music training, general cognitive ability, and openness. Nevertheless, moderation analyses revealed that the partial association between musical competence and music training was evident only among participants who scored below the mean on our measure of general cognitive ability. Moreover, general cognitive ability and openness had indirect associations with musical competence by predicting music training, which in turn predicted musical competence. Musical competence appears to be the result of multiple factors, including but not limited to music training.

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection.

PubMed

Mwanza, Jean-Claude; Warren, Joshua L; Hochberg, Jessica T; Budenz, Donald L; Chang, Robert T; Ramulu, Pradeep Y

2015-01-01

To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. One hundred ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike's information criterion (AIC), and prediction confidence interval lengths. For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDx-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT×NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single-variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAP-FDT, and interaction GDx-TSNIT×NAP-FDT consistently provided better discriminating abilities for detecting early, moderate, and severe glaucoma than the best single-variable models. The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDx-TSNIT×NAP-FDT provides the best glaucoma prediction compared with all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared with using GDx or FDT alone.

GuiTope: an application for mapping random-sequence peptides to protein sequences.

PubMed

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to changes in the environment's statistics. We provide evidence for an alternate route for learning complex temporal statistics: extracting the most probable outcome in a given context is implemented by interactions between executive and motor corticostriatal mechanisms compared with visual corticostriatal circuits (including hippocampal cortex) that support learning of the exact temporal statistics. Copyright © 2017 Wang et al.

Using growth velocity to predict child mortality.

PubMed

Schwinger, Catherine; Fadnes, Lars T; Van den Broeck, Jan

2016-03-01

Growth assessment based on the WHO child growth velocity standards can potentially be used to predict adverse health outcomes. Nevertheless, there are very few studies on growth velocity to predict mortality. We aimed to determine the ability of various growth velocity measures to predict child death within 3 mo and to compare it with those of attained growth measures. Data from 5657 children <5 y old who were enrolled in a cohort study in the Democratic Republic of Congo were used. Children were measured up to 6 times in 3-mo intervals, and 246 (4.3%) children died during the study period. Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for weight and length velocity z scores and 3-mo changes in midupper arm circumference (MUAC). We used receiver operating characteristic (ROC) curves to present balance in sensitivity and specificity to predict child death. GEE models showed that children had an exponential increase in the risk of dying with decreasing growth velocity in all 4 indexes (1.2- to 2.4-fold for every unit decrease). A length and weight velocity z score of <-3 was associated with an 11.8- and a 7.9-fold increase, respectively, in the RR of death in the subsequent 3-mo period (95% CIs: 3.9, 35.5, and 3.9, 16.2, respectively). Weight and length velocity z scores had better predictive abilities [area under the ROC curves (AUCs) of 0.67 and 0.69] than did weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score <-2), the AUC of weight velocity z scores was 0.87. Absolute MUAC performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value. Although repeated growth measures are slightly more complex to implement, their superiority in mortality-predictive abilities suggests that these could be used more for identifying children at increased risk of death.

Two-hour post-challenge glucose is a better predictor of adverse outcome after myocardial infarction than fasting or admission glucose in patients without diabetes.

PubMed

Chattopadhyay, Sudipta; George, Anish; John, Joseph; Sathyapalan, Thozhukat

2018-05-01

We evaluate prevalence of new abnormal glucose tolerance (AGT) in post-MI survivors without known diabetes (DM) if guidelines are followed and compare the ability of admission (APG), fasting (FPG) and 2-h post-load plasma glucose (2h-PG) to predict prognosis. A total of 674 patients were followed up for 4 years for incidence of major adverse cardiovascular events (MACE) of cardiovascular death, non-fatal re-infarction or non-haemorrhagic stroke. Ability of models including APG, FPG and 2h-PG to predict MACE was compared. Of the total, 93-96% of impaired glucose tolerance and 64-75% of DM would be missed with current guidelines. MACE was higher in the upper quartiles of 2h-PG. When 2h-PG and FPG were included simultaneously in models, only 2h-PG predicted MACE (HR 1.12, CI 1.04-1.20, p = 0.0012), all cause mortality (HR 1.17, CI 1.05-1.30, p = 0.0039), cardiovascular mortality (HR 1.17, CI 1.02-1.33, p = 0.0205) and non-fatal MI (HR 1.10, CI 1.01-1.20, p = 0.0291). Adding 2h-PG significantly improved ability of models including FPG (χ 2  = 16.01, df = 1, p = 0.0001) or FPG and APG (χ 2  = 17.36, df = 1, p = 0.000) to predict MACE. Model including 2h-PG only had the lowest Akaike's information criteria and highest Akaike weights suggesting that this was the best in predicting events. Adding 2h-PG to models including FPG or APG with other co-variates yielded continuous net reclassification improvement (NRI) of 0.22 (p = 0.026) and 0.27 (p = 0.005) and categorical NRI of 0.09 (p = 0.032) and 0.12 (p = 0.014), respectively. Adding 2 h-PG to models including only FPG, only APG and both yielded integrated discrimination improvement of 0.012 (p = 0.015), 0.022 (p = 0.001) and 0.013 (p = 0.014), respectively. AGT is under-diagnosed on current guidelines. 2h-PG is a better predictor of prognosis compared to APG and FPG.

Automated Assessment of Existing Patient's Revised Cardiac Risk Index Using Algorithmic Software.

PubMed

Hofer, Ira S; Cheng, Drew; Grogan, Tristan; Fujimoto, Yohei; Yamada, Takashige; Beck, Lauren; Cannesson, Maxime; Mahajan, Aman

2018-05-25

Previous work in the field of medical informatics has shown that rules-based algorithms can be created to identify patients with various medical conditions; however, these techniques have not been compared to actual clinician notes nor has the ability to predict complications been tested. We hypothesize that a rules-based algorithm can successfully identify patients with the diseases in the Revised Cardiac Risk Index (RCRI). Patients undergoing surgery at the University of California, Los Angeles Health System between April 1, 2013 and July 1, 2016 and who had at least 2 previous office visits were included. For each disease in the RCRI except renal failure-congestive heart failure, ischemic heart disease, cerebrovascular disease, and diabetes mellitus-diagnosis algorithms were created based on diagnostic and standard clinical treatment criteria. For each disease state, the prevalence of the disease as determined by the algorithm, International Classification of Disease (ICD) code, and anesthesiologist's preoperative note were determined. Additionally, 400 American Society of Anesthesiologists classes III and IV cases were randomly chosen for manual review by an anesthesiologist. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve were determined using the manual review as a gold standard. Last, the ability of the RCRI as calculated by each of the methods to predict in-hospital mortality was determined, and the time necessary to run the algorithms was calculated. A total of 64,151 patients met inclusion criteria for the study. In general, the incidence of definite or likely disease determined by the algorithms was higher than that detected by the anesthesiologist. Additionally, in all disease states, the prevalence of disease was always lowest for the ICD codes, followed by the preoperative note, followed by the algorithms. In the subset of patients for whom the records were manually reviewed, the algorithms were generally the most sensitive and the ICD codes the most specific. When computing the modified RCRI using each of the methods, the modified RCRI from the algorithms predicted in-hospital mortality with an area under the receiver operating characteristic curve of 0.70 (0.67-0.73), which compared to 0.70 (0.67-0.72) for ICD codes and 0.64 (0.61-0.67) for the preoperative note. On average, the algorithms took 12.64 ± 1.20 minutes to run on 1.4 million patients. Rules-based algorithms for disease in the RCRI can be created that perform with a similar discriminative ability as compared to physician notes and ICD codes but with significantly increased economies of scale.

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

Do Statistical Segmentation Abilities Predict Lexical-Phonological and Lexical-Semantic Abilities in Children with and without SLI?

ERIC Educational Resources Information Center

Mainela-Arnold, Elina; Evans, Julia L.

2014-01-01

This study tested the predictions of the procedural deficit hypothesis by investigating the relationship between sequential statistical learning and two aspects of lexical ability, lexical-phonological and lexical-semantic, in children with and without specific language impairment (SLI). Participants included forty children (ages 8;5-12;3), twenty…

Non-"g" Residuals of the SAT and ACT Predict Specific Abilities

ERIC Educational Resources Information Center

Coyle, Thomas R.; Purcell, Jason M.; Snyder, Anissa C.; Kochunov, Peter

2013-01-01

This research examined whether non-"g" residuals of the SAT and ACT subtests, obtained after removing g, predicted specific abilities. Non-"g" residuals of the verbal and math subtests of the SAT and ACT were correlated with academic (verbal and math) and non-academic abilities (speed and shop), both based on the Armed Services…

Comparison of RISK-PCI, GRACE, TIMI risk scores for prediction of major adverse cardiac events in patients with acute coronary syndrome.

PubMed

Jakimov, Tamara; Mrdović, Igor; Filipović, Branka; Zdravković, Marija; Djoković, Aleksandra; Hinić, Saša; Milić, Nataša; Filipović, Branislav

2017-12-31

To compare the prognostic performance of three major risk scoring systems including global registry for acute coronary events (GRACE), thrombolysis in myocardial infarction (TIMI), and prediction of 30-day major adverse cardiovascular events after primary percutaneous coronary intervention (RISK-PCI). This single-center retrospective study involved 200 patients with acute coronary syndrome (ACS) who underwent invasive diagnostic approach, ie, coronary angiography and myocardial revascularization if appropriate, in the period from January 2014 to July 2014. The GRACE, TIMI, and RISK-PCI risk scores were compared for their predictive ability. The primary endpoint was a composite 30-day major adverse cardiovascular event (MACE), which included death, urgent target-vessel revascularization (TVR), stroke, and non-fatal recurrent myocardial infarction (REMI). The c-statistics of the tested scores for 30-day MACE or area under the receiver operating characteristic curve (AUC) with confidence intervals (CI) were as follows: RISK-PCI (AUC=0.94; 95% CI 1.790-4.353), the GRACE score on admission (AUC=0.73; 95% CI 1.013-1.045), the GRACE score on discharge (AUC=0.65; 95% CI 0.999-1.033). The RISK-PCI score was the only score that could predict TVR (AUC=0.91; 95% CI 1.392-2.882). The RISK-PCI scoring system showed an excellent discriminative potential for 30-day death (AUC=0.96; 95% CI 1.339-3.548) in comparison with the GRACE scores on admission (AUC=0.88; 95% CI 1.018-1.072) and on discharge (AUC=0.78; 95% CI 1.000-1.058). In comparison with the GRACE and TIMI scores, RISK-PCI score showed a non-inferior ability to predict 30-day MACE and death in ACS patients. Moreover, RISK-PCI was the only scoring system that could predict recurrent ischemia requiring TVR.

Comparison of RISK-PCI, GRACE, TIMI risk scores for prediction of major adverse cardiac events in patients with acute coronary syndrome

PubMed Central

Jakimov, Tamara; Mrdović, Igor; Filipović, Branka; Zdravković, Marija; Djoković, Aleksandra; Hinić, Saša; Milić, Nataša; Filipović, Branislav

2017-01-01

Aim To compare the prognostic performance of three major risk scoring systems including global registry for acute coronary events (GRACE), thrombolysis in myocardial infarction (TIMI), and prediction of 30-day major adverse cardiovascular events after primary percutaneous coronary intervention (RISK-PCI). Methods This single-center retrospective study involved 200 patients with acute coronary syndrome (ACS) who underwent invasive diagnostic approach, ie, coronary angiography and myocardial revascularization if appropriate, in the period from January 2014 to July 2014. The GRACE, TIMI, and RISK-PCI risk scores were compared for their predictive ability. The primary endpoint was a composite 30-day major adverse cardiovascular event (MACE), which included death, urgent target-vessel revascularization (TVR), stroke, and non-fatal recurrent myocardial infarction (REMI). Results The c-statistics of the tested scores for 30-day MACE or area under the receiver operating characteristic curve (AUC) with confidence intervals (CI) were as follows: RISK-PCI (AUC = 0.94; 95% CI 1.790-4.353), the GRACE score on admission (AUC = 0.73; 95% CI 1.013-1.045), the GRACE score on discharge (AUC = 0.65; 95% CI 0.999-1.033). The RISK-PCI score was the only score that could predict TVR (AUC = 0.91; 95% CI 1.392-2.882). The RISK-PCI scoring system showed an excellent discriminative potential for 30-day death (AUC = 0.96; 95% CI 1.339-3.548) in comparison with the GRACE scores on admission (AUC = 0.88; 95% CI 1.018-1.072) and on discharge (AUC = 0.78; 95% CI 1.000-1.058). Conclusions In comparison with the GRACE and TIMI scores, RISK-PCI score showed a non-inferior ability to predict 30-day MACE and death in ACS patients. Moreover, RISK-PCI was the only scoring system that could predict recurrent ischemia requiring TVR. PMID:29308832

Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.

PubMed

Chirico, Nicola; Gramatica, Paola

2011-09-26

The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.

Lactate clearance cut off for early mortality prediction in adult sepsis and septic shock patients

NASA Astrophysics Data System (ADS)

Sinto, R.; Widodo, D.; Pohan, H. T.

2018-03-01

Previous lactate clearance cut off for early mortality prediction in sepsis and septic shock patient was determined by consensus from small sample size-study. We investigated the best lactate clearance cut off and its ability to predict early mortality in sepsis and septic shock patients. This cohort study was conducted in Intensive Care Unit of CiptoMangunkusumo Hospital in 2013. Patients’ lactate clearance and eight other resuscitationendpoints were recorded, and theoutcome was observed during the first 120 hours. The clearance cut off was determined using receiver operating characteristic (ROC) analysis, and its ability was investigated with Cox’s proportional hazard regression analysis using other resuscitation endpoints as confounders. Total of 268 subjects was included, of whom 70 (26.11%) subjects died within the first 120 hours. The area under ROC of lactate clearance to predict early mortality was 0.78 (95% % confidence interval [CI] 0.71-0.84) with best cut off was <7.5% (sensitivity and specificity 88.99% and 81.4% respectively). Compared with group achieving lactate clearance target, group not achieving lactate clearance target had to increase early mortality risk (adjusted hazard ratio 13.42; 95%CI 7.19-25.07). In conclusion, the best lactate clearance cut off as anearly mortality predictor in sepsis and septic shock patients is 7.5%.

Comparison of calculated and measured velocities near the tip of a model rotor blade at transonic speeds

NASA Technical Reports Server (NTRS)

Tauber, M. E.; Owen, F. K.; Langhi, R. G.; Palmer, G. E.

1985-01-01

The ability of the ROT22 code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high speed rotor blade was assessed. The computations were compared with extensive laser velocimetry measurements made at zero advance ratio and tip Mach numbers of 0.85, 0.88, 0.90, and 0.95. The comparison between theory and experiment was made using 300 scans for the three orthogonal velocity components covering a volume having a height of over one blade chord, a width of nearly two chords, and a length ranging from about 1 to 1.6 chords, depending on the tip speeds. The good agreement between the calculated and measured velocities established the ability of the code to predict the off blade flow field at high tip speeds. This supplements previous comparisons where surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuth blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip region flow field including the occurrence, strength, and location of shock waves causing high drag and noise.

Numerical and Qualitative Contrasts of Two Statistical Models ...

EPA Pesticide Factsheets

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and products. This study provided an empirical and qualitative comparison of both models using 29 years of data for two discrete time series of chlorophyll-a (chl-a) in the Patuxent River estuary. Empirical descriptions of each model were based on predictive performance against the observed data, ability to reproduce flow-normalized trends with simulated data, and comparisons of performance with validation datasets. Between-model differences were apparent but minor and both models had comparable abilities to remove flow effects from simulated time series. Both models similarly predicted observations for missing data with different characteristics. Trends from each model revealed distinct mainstem influences of the Chesapeake Bay with both models predicting a roughly 65% increase in chl-a over time in the lower estuary, whereas flow-normalized predictions for the upper estuary showed a more dynamic pattern, with a nearly 100% increase in chl-a in the last 10 years. Qualitative comparisons highlighted important differences in the statistical structure, available products, and characteristics of the data and desired analysis. This manuscript describes a quantitative comparison of two recently-

Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

PubMed

Lorenz, Alyson; Dhingra, Radhika; Chang, Howard H; Bisanzio, Donal; Liu, Yang; Remais, Justin V

2014-01-01

Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

A Video-Based Measure of Preservice Teachers' Abilities to Predict Elementary Students' Scientific Reasoning

ERIC Educational Resources Information Center

Akerson, Valarie L.; Carter, Ingrid S.; Park Rogers, Meredith A.; Pongsanon, Khemmawadee

2018-01-01

In this mixed methods study, the researchers developed a video-based measure called a "Prediction Assessment" to determine preservice elementary teachers' abilities to predict students' scientific reasoning. The instrument is based on teachers' need to develop pedagogical content knowledge for teaching science. Developing a knowledge…

Humor Ability Reveals Intelligence, Predicts Mating Success, and Is Higher in Males

ERIC Educational Resources Information Center

Greengross, Gil; Miller, Geoffrey

2011-01-01

A good sense of humor is sexually attractive, perhaps because it reveals intelligence, creativity, and other "good genes" or "good parent" traits. If so, intelligence should predict humor production ability, which in turn should predict mating success. In this study, 400 university students (200 men and 200 women) completed…

Challenges in Quantifying Pliocene Terrestrial Warming Revealed by Data-Model Discord

NASA Technical Reports Server (NTRS)

Salzmann, Ulrich; Dolan, Aisling M.; Haywood, Alan M.; Chan, Wing-Le; Voss, Jochen; Hill, Daniel J.; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Bragg, Frances J.; Chandler, Mark A.;

Differential neural contributions to native- and foreign-language talker identification

PubMed Central

Perrachione, Tyler K.; Pierrehumbert, Janet B.; Wong, Patrick C.M.

2009-01-01

Humans are remarkably adept at identifying individuals by the sound of their voice, a behavior supported by the nervous system’s ability to integrate information from voice and speech perception. Talker-identification abilities are significantly impaired when listeners are unfamiliar with the language being spoken. Recent behavioral studies describing the language-familiarity effect implicate functionally integrated neural systems for speech and voice perception, yet specific neuroscientific evidence demonstrating the basis for such integration has not yet been shown. Listeners in the present study learned to identify voices speaking a familiar (native) or unfamiliar (foreign) language. The talker-identification performance of neural circuitry in each cerebral hemisphere was assessed using dichotic listening. To determine the relative contribution of circuitry in each hemisphere to ecological (binaural) talker identification abilities, we compared the predictive capacity of dichotic performance on binaural performance across languages. We found listeners’ right-ear (left hemisphere) performance to be a better predictor of overall accuracy in their native language than a foreign one. The enhanced predictive capacity of the classically language-dominant left-hemisphere on overall talker-identification accuracy demonstrates functionally integrated neural systems for speech and voice perception during natural talker identification. PMID:19968445

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Introduction to the IWA task group on biofilm modeling.

PubMed

Noguera, D R; Morgenroth, E

2004-01-01

An International Water Association (IWA) Task Group on Biofilm Modeling was created with the purpose of comparatively evaluating different biofilm modeling approaches. The task group developed three benchmark problems for this comparison, and used a diversity of modeling techniques that included analytical, pseudo-analytical, and numerical solutions to the biofilm problems. Models in one, two, and three dimensional domains were also compared. The first benchmark problem (BM1) described a monospecies biofilm growing in a completely mixed reactor environment and had the purpose of comparing the ability of the models to predict substrate fluxes and concentrations for a biofilm system of fixed total biomass and fixed biomass density. The second problem (BM2) represented a situation in which substrate mass transport by convection was influenced by the hydrodynamic conditions of the liquid in contact with the biofilm. The third problem (BM3) was designed to compare the ability of the models to simulate multispecies and multisubstrate biofilms. These three benchmark problems allowed identification of the specific advantages and disadvantages of each modeling approach. A detailed presentation of the comparative analyses for each problem is provided elsewhere in these proceedings.

Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities.

PubMed

Evans, Tanya M; Kochalka, John; Ngoon, Tricia J; Wu, Sarah S; Qin, Shaozheng; Battista, Christian; Menon, Vinod

2015-08-19

Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today's technological society. Identification of cognitive and brain markers associated with long-term growth of children's basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children's gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties. Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children's math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions. Copyright © 2015 the authors 0270-6474/15/3511743-08$15.00/0.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

The association of children's mathematic abilities with both adults' cognitive abilities and intrinsic fronto-parietal networks is altered in preterm-born individuals.

PubMed

Bäuml, J G; Meng, C; Daamen, M; Baumann, N; Busch, B; Bartmann, P; Wolke, D; Boecker, H; Wohlschläger, A; Sorg, C; Jaekel, Julia

2017-03-01

Mathematic abilities in childhood are highly predictive for long-term neurocognitive outcomes. Preterm-born individuals have an increased risk for both persistent cognitive impairments and long-term changes in macroscopic brain organization. We hypothesized that the association of childhood mathematic abilities with both adulthood general cognitive abilities and associated fronto-parietal intrinsic networks is altered after preterm delivery. 72 preterm- and 71 term-born individuals underwent standardized mathematic and IQ testing at 8 years and resting-state fMRI and full-scale IQ testing at 26 years of age. Outcome measure for intrinsic networks was intrinsic functional connectivity (iFC). Controlling for IQ at age eight, mathematic abilities in childhood were significantly stronger positively associated with adults' IQ in preterm compared with term-born individuals. In preterm-born individuals, the association of children's mathematic abilities and adults' fronto-parietal iFC was altered. Likewise, fronto-parietal iFC was distinctively linked with preterm- and term-born adults' IQ. Results provide evidence that preterm birth alters the link of mathematic abilities in childhood and general cognitive abilities and fronto-parietal intrinsic networks in adulthood. Data suggest a distinct functional role of intrinsic fronto-parietal networks for preterm individuals with respect to mathematic abilities and that these networks together with associated children's mathematic abilities may represent potential neurocognitive targets for early intervention.

The importance of subjective facial appearance on the ability of anesthesiologists to predict difficult intubation.

PubMed

Connor, Christopher W; Segal, Scott

2014-02-01

Previously we demonstrated that a computer algorithm based on bedside airway examinations and facial photographs accurately classified easy and difficult airways. The extent of the ability of anesthesiologists to perform the same task is unknown. We hypothesized that providing photographs would add to the predictive ability of anesthesiologists over that achieved when provided only with the Mallampati (MP) score and the thyromental distance (TMD). We further hypothesized that human observers would implicitly bias their predictions toward more sensitive determination of difficult airways, rather than more specific determination of easy airways. Residents, fellows, and attending anesthesiologists with varying levels of experience (N = 160) were presented with MP and TMD information from 80 Caucasian men subjects. The same subjects' data, accompanied by 3 facial photographs in head-on and right and left profiles, were also presented. Anesthesiologists classified the airways as easy or difficult according to specified criteria ("easy" defined as a single attempt with a Macintosh 3 blade resulting in a grade 1 laryngoscopic view; "difficult" defined as >1 attempt by an operator with at least 12 months anesthesia experience, grade 3 or 4 laryngoscopic view, need for a second operator, or nonelective use of an alternative airway device). Accuracy, sensitivity, and specificity were calculated for each anesthesiologist. We further developed a cost function to quantify a relative bias toward avoiding an unexpectedly difficult intubation versus overpreparing for an easy intubation. One hundred sixty respondents completed the study. Presenting photographs improved respondents' sensitivity and accuracy in classifying airways, though specificity decreased slightly. Overall accuracy when given photographs was 61.6% (95% confidence interval, 60.8%-62.4%), which was significantly lower than the computer's performance of 87.5% (t test, P < 0.0001). Presentation of photographs, compared with MP and TMD alone, caused anesthesiologists to change their prediction from easy to difficult more frequently if the patients were obese (weight or body mass index), despite not having data on weight or height available. The cost function demonstrated that anesthesiologists strongly preferred to enhance sensitivity (detecting difficult airways) as compared with specificity (detecting easy airways), with a ratio of 6.5:1 (95% confidence interval, 4.9:1-8.4:1). Anesthesiologists can derive useful information from facial appearance that enhances the prediction of a difficult airway over that achieved when presented with MP and TMD data alone. Anesthesiologists implicitly bias their predictions toward detection of difficult airways, compared with the true incidence of difficult airways, at the expense of accuracy and specificity. This behavior may be rational for cognitive tasks in which the costs of failure are strongly asymmetric.

Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

PubMed

Petersen, Laura A; Pietz, Kenneth; Woodard, LeChauncy D; Byrne, Margaret

2005-01-01

Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.

Derivation and validation of in-hospital mortality prediction models in ischaemic stroke patients using administrative data.

PubMed

Lee, Jason; Morishima, Toshitaka; Kunisawa, Susumu; Sasaki, Noriko; Otsubo, Tetsuya; Ikai, Hiroshi; Imanaka, Yuichi

2013-01-01

Stroke and other cerebrovascular diseases are a major cause of death and disability. Predicting in-hospital mortality in ischaemic stroke patients can help to identify high-risk patients and guide treatment approaches. Chart reviews provide important clinical information for mortality prediction, but are laborious and limiting in sample sizes. Administrative data allow for large-scale multi-institutional analyses but lack the necessary clinical information for outcome research. However, administrative claims data in Japan has seen the recent inclusion of patient consciousness and disability information, which may allow more accurate mortality prediction using administrative data alone. The aim of this study was to derive and validate models to predict in-hospital mortality in patients admitted for ischaemic stroke using administrative data. The sample consisted of 21,445 patients from 176 Japanese hospitals, who were randomly divided into derivation and validation subgroups. Multivariable logistic regression models were developed using 7- and 30-day and overall in-hospital mortality as dependent variables. Independent variables included patient age, sex, comorbidities upon admission, Japan Coma Scale (JCS) score, Barthel Index score, modified Rankin Scale (mRS) score, and admissions after hours and on weekends/public holidays. Models were developed in the derivation subgroup, and coefficients from these models were applied to the validation subgroup. Predictive ability was analysed using C-statistics; calibration was evaluated with Hosmer-Lemeshow χ(2) tests. All three models showed predictive abilities similar or surpassing that of chart review-based models. The C-statistics were highest in the 7-day in-hospital mortality prediction model, at 0.906 and 0.901 in the derivation and validation subgroups, respectively. For the 30-day in-hospital mortality prediction models, the C-statistics for the derivation and validation subgroups were 0.893 and 0.872, respectively; in overall in-hospital mortality prediction these values were 0.883 and 0.876. In this study, we have derived and validated in-hospital mortality prediction models for three different time spans using a large population of ischaemic stroke patients in a multi-institutional analysis. The recent inclusion of JCS, Barthel Index, and mRS scores in Japanese administrative data has allowed the prediction of in-hospital mortality with accuracy comparable to that of chart review analyses. The models developed using administrative data had consistently high predictive abilities for all models in both the derivation and validation subgroups. These results have implications in the role of administrative data in future mortality prediction analyses. Copyright © 2013 S. Karger AG, Basel.

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Raspberry, not a car: context predictability and a phonological advantage in early and late learners’ processing of speech in noise

PubMed Central

Gor, Kira

2014-01-01

Second language learners perform worse than native speakers under adverse listening conditions, such as speech in noise (SPIN). No data are available on heritage language speakers’ (early naturalistic interrupted learners’) ability to perceive SPIN. The current study fills this gap and investigates the perception of Russian speech in multi-talker babble noise by the matched groups of high- and low-proficiency heritage speakers (HSs) and late second language learners of Russian who were native speakers of English. The study includes a control group of Russian native speakers. It manipulates the noise level (high and low), and context cloze probability (high and low). The results of the SPIN task are compared to the tasks testing the control of phonology, AXB discrimination and picture-word discrimination, and lexical knowledge, a word translation task, in the same participants. The increased phonological sensitivity of HSs interacted with their ability to rely on top–down processing in sentence integration, use contextual cues, and build expectancies in the high-noise/high-context condition in a bootstrapping fashion. HSs outperformed oral proficiency-matched late second language learners on SPIN task and two tests of phonological sensitivity. The outcomes of the SPIN experiment support both the early naturalistic advantage and the role of proficiency in HSs. HSs’ ability to take advantage of the high-predictability context in the high-noise condition was mitigated by their level of proficiency. Only high-proficiency HSs, but not any other non-native group, took advantage of the high-predictability context that became available with better phonological processing skills in high-noise. The study thus confirms high-proficiency (but not low-proficiency) HSs’ nativelike ability to combine bottom–up and top–down cues in processing SPIN. PMID:25566130

Development of an Itemwise Efficiency Scoring Method: Concurrent, Convergent, Discriminant, and Neuroimaging-Based Predictive Validity Assessed in a Large Community Sample

PubMed Central

Moore, Tyler M.; Reise, Steven P.; Roalf, David R.; Satterthwaite, Theodore D.; Davatzikos, Christos; Bilker, Warren B.; Port, Allison M.; Jackson, Chad T.; Ruparel, Kosha; Savitt, Adam P.; Baron, Robert B.; Gur, Raquel E.; Gur, Ruben C.

2016-01-01

Traditional “paper-and-pencil” testing is imprecise in measuring speed and hence limited in assessing performance efficiency, but computerized testing permits precision in measuring itemwise response time. We present a method of scoring performance efficiency (combining information from accuracy and speed) at the item level. Using a community sample of 9,498 youths age 8-21, we calculated item-level efficiency scores on four neurocognitive tests, and compared the concurrent, convergent, discriminant, and predictive validity of these scores to simple averaging of standardized speed and accuracy-summed scores. Concurrent validity was measured by the scores' abilities to distinguish men from women and their correlations with age; convergent and discriminant validity were measured by correlations with other scores inside and outside of their neurocognitive domains; predictive validity was measured by correlations with brain volume in regions associated with the specific neurocognitive abilities. Results provide support for the ability of itemwise efficiency scoring to detect signals as strong as those detected by standard efficiency scoring methods. We find no evidence of superior validity of the itemwise scores over traditional scores, but point out several advantages of the former. The itemwise efficiency scoring method shows promise as an alternative to standard efficiency scoring methods, with overall moderate support from tests of four different types of validity. This method allows the use of existing item analysis methods and provides the convenient ability to adjust the overall emphasis of accuracy versus speed in the efficiency score, thus adjusting the scoring to the real-world demands the test is aiming to fulfill. PMID:26866796

Iterative weighting of multiblock data in the orthogonal partial least squares framework.

PubMed

Boccard, Julien; Rutledge, Douglas N

2014-02-27

The integration of multiple data sources has emerged as a pivotal aspect to assess complex systems comprehensively. This new paradigm requires the ability to separate common and redundant from specific and complementary information during the joint analysis of several data blocks. However, inherent problems encountered when analysing single tables are amplified with the generation of multiblock datasets. Finding the relationships between data layers of increasing complexity constitutes therefore a challenging task. In the present work, an algorithm is proposed for the supervised analysis of multiblock data structures. It associates the advantages of interpretability from the orthogonal partial least squares (OPLS) framework and the ability of common component and specific weights analysis (CCSWA) to weight each data table individually in order to grasp its specificities and handle efficiently the different sources of Y-orthogonal variation. Three applications are proposed for illustration purposes. A first example refers to a quantitative structure-activity relationship study aiming to predict the binding affinity of flavonoids toward the P-glycoprotein based on physicochemical properties. A second application concerns the integration of several groups of sensory attributes for overall quality assessment of a series of red wines. A third case study highlights the ability of the method to combine very large heterogeneous data blocks from Omics experiments in systems biology. Results were compared to the reference multiblock partial least squares (MBPLS) method to assess the performance of the proposed algorithm in terms of predictive ability and model interpretability. In all cases, ComDim-OPLS was demonstrated as a relevant data mining strategy for the simultaneous analysis of multiblock structures by accounting for specific variation sources in each dataset and providing a balance between predictive and descriptive purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Raspberry, not a car: context predictability and a phonological advantage in early and late learners' processing of speech in noise.

PubMed

Gor, Kira

2014-01-01

Second language learners perform worse than native speakers under adverse listening conditions, such as speech in noise (SPIN). No data are available on heritage language speakers' (early naturalistic interrupted learners') ability to perceive SPIN. The current study fills this gap and investigates the perception of Russian speech in multi-talker babble noise by the matched groups of high- and low-proficiency heritage speakers (HSs) and late second language learners of Russian who were native speakers of English. The study includes a control group of Russian native speakers. It manipulates the noise level (high and low), and context cloze probability (high and low). The results of the SPIN task are compared to the tasks testing the control of phonology, AXB discrimination and picture-word discrimination, and lexical knowledge, a word translation task, in the same participants. The increased phonological sensitivity of HSs interacted with their ability to rely on top-down processing in sentence integration, use contextual cues, and build expectancies in the high-noise/high-context condition in a bootstrapping fashion. HSs outperformed oral proficiency-matched late second language learners on SPIN task and two tests of phonological sensitivity. The outcomes of the SPIN experiment support both the early naturalistic advantage and the role of proficiency in HSs. HSs' ability to take advantage of the high-predictability context in the high-noise condition was mitigated by their level of proficiency. Only high-proficiency HSs, but not any other non-native group, took advantage of the high-predictability context that became available with better phonological processing skills in high-noise. The study thus confirms high-proficiency (but not low-proficiency) HSs' nativelike ability to combine bottom-up and top-down cues in processing SPIN.

How could Theory of Mind contribute to the differentiation of social adjustment profiles of children with externalizing behavior disorders and children with intellectual disabilities?

PubMed

Nader-Grosbois, Nathalie; Houssa, Marine; Mazzone, Stéphanie

2013-09-01

This study compared Theory of Mind (ToM) emotion and belief abilities in 43 children with externalized behavior (EB) disorders presenting low intelligence, 40 children with intellectual disabilities (ID) and 33 typically developing (TD) preschoolers (as a control group), matched for developmental age. The links between their ToM abilities, their level in seven self-regulation strategies as displayed in social problem-solving tasks and their social adjustment profiles (assessed by the Social Competence and Behavior Evaluation, completed by their teachers) were examined. Children with EB presented lower comprehension of causes of emotions and lower self-regulation of joint attention and of attention than children with ID and TD children. In comparison with TD children, lower social adjustment was observed in nearly all dimensions of profiles in both atypical groups. Specifically, children with EB were significantly angrier than children with ID. Although variable patterns of positive correlations were obtained in atypical groups between self-regulation strategies and ToM abilities, the most numerous positive links were obtained in the group with EB. Regression analyses showed that developmental age predicted ToM abilities and certain dimensions of social adjustment profiles in atypical groups. In the ID group, ToM emotions predicted general adaptation, affective adaptation, interactions with peers and with adults and low internalizing problems. In the EB group, general adaptation was predicted by ToM emotions and self-regulation, interactions with peers by ToM beliefs, and a low level of externalizing problems by ToM emotions. Some implications for intervention and perspectives for research are suggested. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives.

PubMed

Johannesdottir, Fjola; Allaire, Brett; Bouxsein, Mary L

2018-05-30

This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures. CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment. CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test

PubMed Central

Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

2016-01-01

This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants’ (ii), men’s (iii), and women’s (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women’s predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one’s ability relative to same and opposite sex peers. PMID:27847487

Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test.

PubMed

Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

2016-01-01

This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants' (ii), men's (iii), and women's (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women's predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one's ability relative to same and opposite sex peers.

The Role of the AMOC in Forecast Cooling of the Atlantic Subpolar Gyre and Its Associated Impacts

NASA Astrophysics Data System (ADS)

Eade, R.; Hermanson, L.; Robinson, N.; Dunstone, N.; Andrews, M.; Knight, J.; Scaife, A. A.; Smith, D.

2014-12-01

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate.

Forecast cooling of the Atlantic subpolar gyre and associated impacts

PubMed Central

Hermanson, Leon; Eade, Rosie; Robinson, Niall H; Dunstone, Nick J; Andrews, Martin B; Knight, Jeff R; Scaife, Adam A; Smith, Doug M

2014-01-01

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate. PMID:25821269

Predicting temporal trends in total absenteeism rates for civil service employees of a federal public health agency.

PubMed

Spears, D Ross; McNeil, Carrie; Warnock, Eli; Trapp, Jonathan; Oyinloye, Oluremi; Whitehurst, Vanessa; Decker, K C; Chapman, Sandy; Campbell, Morris; Meechan, Paul

2014-06-01

This study evaluates the predictability in temporal absences trends due to all causes (total absenteeism) among employees at a federal agency. The objective is to determine how leave trends vary within the year, and determine whether trends are predictable. Ten years of absenteeism data from an attendance system were analyzed for rates of total absence. Trends over a 10-year period followed predictable and regular patterns during a given year that correspond to major holiday periods. Temporal trends in leave among small, medium, and large facilities compared favorably with the agency as a whole. Temporal trends in total absenteeism rates for an organization can be determined using its attendance system. The ability to predict employee absenteeism rates can be extremely helpful for management in optimizing business performance and ensuring that an organization meets its mission.

Predictive Compensator Optimization for Head Tracking Lag in Virtual Environments

NASA Technical Reports Server (NTRS)

Adelstein, Barnard D.; Jung, Jae Y.; Ellis, Stephen R.

2001-01-01

We examined the perceptual impact of plant noise parameterization for Kalman Filter predictive compensation of time delays intrinsic to head tracked virtual environments (VEs). Subjects were tested in their ability to discriminate between the VE system's minimum latency and conditions in which artificially added latency was then predictively compensated back to the system minimum. Two head tracking predictors were parameterized off-line according to cost functions that minimized prediction errors in (1) rotation, and (2) rotation projected into translational displacement with emphasis on higher frequency human operator noise. These predictors were compared with a parameterization obtained from the VE literature for cost function (1). Results from 12 subjects showed that both parameterization type and amount of compensated latency affected discrimination. Analysis of the head motion used in the parameterizations and the subsequent discriminability results suggest that higher frequency predictor artifacts are contributory cues for discriminating the presence of predictive compensation.

The real-time prediction and inhibition of linguistic outcomes: Effects of language and literacy skill.

PubMed

Kukona, Anuenue; Braze, David; Johns, Clinton L; Mencl, W Einar; Van Dyke, Julie A; Magnuson, James S; Pugh, Kenneth R; Shankweiler, Donald P; Tabor, Whitney

2016-11-01

Recent studies have found considerable individual variation in language comprehenders' predictive behaviors, as revealed by their anticipatory eye movements during language comprehension. The current study investigated the relationship between these predictive behaviors and the language and literacy skills of a diverse, community-based sample of young adults. We found that rapid automatized naming (RAN) was a key determinant of comprehenders' prediction ability (e.g., as reflected in predictive eye movements to a white cake on hearing "The boy will eat the white…"). Simultaneously, comprehension-based measures predicted participants' ability to inhibit eye movements to objects that shared features with predictable referents but were implausible completions (e.g., as reflected in eye movements to a white but inedible white car). These findings suggest that the excitatory and inhibitory mechanisms that support prediction during language processing are closely linked with specific cognitive abilities that support literacy. We show that a self-organizing cognitive architecture captures this pattern of results. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients.

PubMed

Kusy, Maciej; Obrzut, Bogdan; Kluska, Jacek

2013-12-01

The aim of this article was to compare gene expression programming (GEP) method with three types of neural networks in the prediction of adverse events of radical hysterectomy in cervical cancer patients. One-hundred and seven patients treated by radical hysterectomy were analyzed. Each record representing a single patient consisted of 10 parameters. The occurrence and lack of perioperative complications imposed a two-class classification problem. In the simulations, GEP algorithm was compared to a multilayer perceptron (MLP), a radial basis function network neural, and a probabilistic neural network. The generalization ability of the models was assessed on the basis of their accuracy, the sensitivity, the specificity, and the area under the receiver operating characteristic curve (AUROC). The GEP classifier provided best results in the prediction of the adverse events with the accuracy of 71.96 %. Comparable but slightly worse outcomes were obtained using MLP, i.e., 71.87 %. For each of measured indices: accuracy, sensitivity, specificity, and the AUROC, the standard deviation was the smallest for the models generated by GEP classifier.

Use of the Short Physical Performance Battery Score to predict loss of ability to walk 400 meters: analysis from the InCHIANTI study.

PubMed

Vasunilashorn, Sarinnapha; Coppin, Antonia K; Patel, Kushang V; Lauretani, Fulvio; Ferrucci, Luigi; Bandinelli, Stefania; Guralnik, Jack M

2009-02-01

Early detection of mobility limitations remains an important goal for preventing mobility disability. The purpose of this study was to examine the association between the Short Physical Performance Battery (SPPB) and the loss of ability to walk 400 m, an objectively assessed mobility outcome increasingly used in clinical trials. The study sample consisted of 542 adults from the InCHIANTI study aged 65 and older, who completed the 400 m walk at baseline and had evaluations on the SPPB and 400 m walk at baseline and 3-year follow-up. Multiple logistic regression models were used to determine whether SPPB scores predict the loss of ability to walk 400 m at follow-up among persons able to walk 400 m at baseline. The 3-year incidence of failing the 400 m walk was 15.5%. After adjusting for age, sex, education, body mass index, Mini-Mental State Examination, number of medical conditions, and 400 m walk gait speed at baseline, SPPB score was significantly associated with loss of ability to walk 400 m after 3 years. Participants with SPPB scores of 10 or lower at baseline had significantly higher odds of mobility disability at follow-up (odds ratio [OR] = 3.38, 95% confidence interval [CI]: 1.32-8.65) compared with those who scored 12, with a graded response across the range of SPPB scores (OR = 26.93, 95% CI: 7.51-96.50; OR = 7.67, 95% CI: 2.26-26.04; OR = 8.28, 95% CI: 3.32-20.67 for SPPB < or = 7, SPPB 8, and SPPB 9, respectively). The SPPB strongly predicts loss of ability to walk 400 m. Thus, using the SPPB to identify older persons at high risk of lower body functional limitations seems a valid means of recognizing individuals who would benefit most from preventive interventions.

Use of the Short Physical Performance Battery Score to Predict Loss of Ability to Walk 400 Meters: Analysis From the InCHIANTI Study

PubMed Central

Coppin, Antonia K.; Patel, Kushang V.; Lauretani, Fulvio; Ferrucci, Luigi; Bandinelli, Stefania; Guralnik, Jack M.

2009-01-01

Background Early detection of mobility limitations remains an important goal for preventing mobility disability. The purpose of this study was to examine the association between the Short Physical Performance Battery (SPPB) and the loss of ability to walk 400 m, an objectively assessed mobility outcome increasingly used in clinical trials. Methods The study sample consisted of 542 adults from the InCHIANTI study aged 65 and older, who completed the 400 m walk at baseline and had evaluations on the SPPB and 400 m walk at baseline and 3-year follow-up. Multiple logistic regression models were used to determine whether SPPB scores predict the loss of ability to walk 400 m at follow-up among persons able to walk 400 m at baseline. Results The 3-year incidence of failing the 400 m walk was 15.5%. After adjusting for age, sex, education, body mass index, Mini-Mental State Examination, number of medical conditions, and 400 m walk gait speed at baseline, SPPB score was significantly associated with loss of ability to walk 400 m after 3 years. Participants with SPPB scores of 10 or lower at baseline had significantly higher odds of mobility disability at follow-up (odds ratio [OR] = 3.38, 95% confidence interval [CI]: 1.32–8.65) compared with those who scored 12, with a graded response across the range of SPPB scores (OR = 26.93, 95% CI: 7.51–96.50; OR = 7.67, 95% CI: 2.26–26.04; OR = 8.28, 95% CI: 3.32–20.67 for SPPB ≤ 7, SPPB 8, and SPPB 9, respectively). Conclusions The SPPB strongly predicts loss of ability to walk 400 m. Thus, using the SPPB to identify older persons at high risk of lower body functional limitations seems a valid means of recognizing individuals who would benefit most from preventive interventions. PMID:19182232

The discriminative ability of waist circumference, body mass index and waist-to-hip ratio in identifying metabolic syndrome: Variations by age, sex and race.

PubMed

Cheong, Kee C; Ghazali, Sumarni M; Hock, Lim K; Subenthiran, Soobitha; Huey, Teh C; Kuay, Lim K; Mustapha, Feisul I; Yusoff, Ahmad F; Mustafa, Amal N

2015-01-01

Many studies have suggested that there is variation in the capabilities of BMI, WC and WHR in predicting cardiometabolic risk and that it might be confounded by gender, ethnicity and age group. The objective of this study is to examine the discriminative abilities of body mass index (BMI), waist circumference (WC) and waist-hip ratio (WHR) to predict two or more non-adipose components of the metabolic syndrome (high blood pressure, hypertriglyceridemia, low high density lipoprotein-cholesterol and high fasting plasma glucose) among the adult Malaysian population by gender, age group and ethnicity. Data from 2572 respondents (1044 men and 1528 women) aged 25-64 years who participated in the Non Communicable Disease Surveillance 2005/2006, a population-based cross sectional study, were analysed. Participants' socio-demographic details, anthropometric indices (BMI, WC and WHR), blood pressure, fasting lipid profile and fasting glucose level were assessed. Receiver operating characteristics curves analysis was used to evaluate the ability of each anthropometric index to discriminate MetS cases from non-MetS cases based on the area under the curve. Overall, WC had better discriminative ability than WHR for women but did not perform significantly better than BMI in both sexes, whereas BMI was better than WHR in women only. Waist circumference was a better discriminator of MetS compared to WHR in Malay men and women. Waist circumference and BMI performed better than WHR in Chinese women, men aged 25-34 years and women aged 35-44 years. The discriminative ability of BMI and WC is better than WHR for predicting two or more non-adipose components of MetS. Therefore, either BMI or WC measurements are recommended in screening for metabolic syndrome in routine clinical practice in the effort to combat cardiovascular disease and type II diabetes mellitus. Copyright © 2015 Diabetes India. Published by Elsevier Ltd. All rights reserved.

The Predictive Validity of the Assessment of Basic Learning Abilities versus Parents' Predictions with Children with Autism

ERIC Educational Resources Information Center

Murphy, Colleen; Martin, Garry L.; Yu, C. T.

2014-01-01

The Assessment of Basic Learning Abilities (ABLA) is an empirically validated clinical tool for assessing the learning ability of persons with intellectual disabilities and children with autism. An ABLA tester uses standardized prompting and reinforcement procedures to attempt to teach, individually, each of six tasks, called levels, to a testee,…

Expectancy Theory as a Predictor of Grade-Point Averages, Satisfaction, and Participation in the College Environment. ASHE 1983 Annual Meeting Paper.

ERIC Educational Resources Information Center

Lincoln, Yvonna S.; And Others

The ability of Vroom's expectancy motivation theory to predict student satisfaction with the college environment, student participation at school, and student academic performance was studied. Specific objectives of the study were as follows: to test the ability of Vroom's valence model to predict student satisfaction, to test the ability of…

Consumer Decision-Making Abilities and Long-Term Care Insurance Purchase.

PubMed

McGarry, Brian E; Tempkin-Greener, Helena; Grabowski, David C; Chapman, Benjamin P; Li, Yue

2018-04-16

To determine the impact of consumer decision-making abilities on making a long-term care insurance (LTCi) purchasing decision that is consistent with normative economic predictions regarding policy ownership. Using data from the Health and Retirement Study, multivariate analyses are implemented to estimate the effect of decision-making ability factors on owning LTCi. Stratified multivariate analyses are used to examine the effect of decision-making abilities on the likelihood of adhering to economic predictions of LTCi ownership. In the full sample, better cognitive capacity was found to significantly increase the odds of ownership. When the sample was stratified based on expected LTCi ownership status, cognitive capacity was positively associated with ownership among those predicted to own and negatively associated with ownership among those predicted not to own who could likely afford a policy. Consumer decision-making abilities, specifically cognitive capacity, are an important determinant of LTCi decision outcomes. Deficits in this ability may prevent individuals from successfully preparing for future long-term care expenses. Policy makers should consider changes that reduce the cognitive burden of this choice, including the standardization of the LTCi market, the provision of consumer decision aids, and alternatives to voluntary and private insuring mechanisms.

Utility of the MMPI Pain Assessment Index in Predicting Outcome After Lumbar Surgery.

ERIC Educational Resources Information Center

Turner, Judith; And Others

1986-01-01

Examined the ability of the Pain Assesment Index, determined from presurgery Minnesota Multiphasic Personality Inventory scores, to predict outcome subsequent to lumbar laminectomy and discectomy. The PAI was found to have good ability to identify patients who were doing well after surgery, but low power in predicting which patients would have…

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.

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

ERIC Educational Resources Information Center

Kayri, Murat

2015-01-01

The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

Report on High School Characteristic Index Study at John Marshall High School - 1970.

ERIC Educational Resources Information Center

Newman, Wilfred

The High School Characteristic Index (H.S.C.I.) was employed at a high school in Rochester to measure students' perceptions, as well as teachers' ability to predict students' perceptions, after black-white violence occurred in May, 1970. The 1970 results were compared with 1966 results of the H.S.C.I. at the same high school when a different…

A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant.

PubMed

Chun, Ting Sie; Malek, M A; Ismail, Amelia Ritahani

2015-01-01

The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a well-established method - namely the least-square support vector machine (LS-SVM) as a baseline model. The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. The CSA approach shows that fewer control and training parameters are required for model simulation as compared with the LS-SVM approach. The ability of a CSA approach in resolving limited data samples, non-linear sample function and multidimensional pattern recognition makes it a powerful tool in modelling the prediction of effluent removals in an SSTP.

Accuracy of percutaneous transhepatic cholangiography in predicting the location and nature of major bile duct injuries.

PubMed

Fidelman, Nicholas; Kerlan, Robert K; Laberge, Jeanne M; Gordon, Roy L

2011-06-01

To determine the ability of percutaneous transhepatic cholangiography (PTC) to predict accurately the anatomic location and nature of major bile duct injuries, to examine the contribution of endoscopic retrograde cholangiopancreatography (ERCP) and PTC to the diagnosis of injuries to the low-inserting right posterior segmental ducts, and to compare the ability of radiologists and gastroenterologists to detect injuries to the low-inserting right posterior segmental duct. PTC images and operative reports of 78 consecutive patients who underwent surgical repair of major bile duct injuries at the authors' institution were retrospectively reviewed. The location of injury was assessed according to the Bismuth classification. Images were also evaluated for the presence of a biliary stricture, biliary leak, or both. Imaging observations were compared with findings obtained during surgical biliary reconstruction. PTC correctly predicted the anatomic location of injuries in 85% of patients. Incorrect Bismuth type was assigned in 12 patients. Seven of the errors (58%) originated from the inability to distinguish injuries at the confluence of the lobar ducts from injuries involving the cephalad 2 cm of the common hepatic duct. Injuries to the right posterior segmental duct were detected more often on ERCP images by gastroenterologists than by diagnostic radiologists. In four patients (5%), biliary strictures were masked on PTC by the presence of a concomitant leak. PTC accurately depicts the location and nature of major bile duct injuries in most patients. Copyright © 2011 SIR. Published by Elsevier Inc. All rights reserved.

Performance on verbal and low-verbal false belief tasks: evidence from children with Williams syndrome.

PubMed

Van Herwegen, Jo; Dimitriou, Dagmara; Rundblad, Gabriella

2013-01-01

Previous studies that have investigated the relationship between performance on theory of mind (ToM) tasks and verbal abilities in individuals with Williams syndrome (WS) have reported contradictory findings with some showing that language abilities aid performance on ToM tasks while others have found that participants with WS fail these tasks because of their verbal demands. The current study investigated this relationship again comparing performance on a classical change-location task to two newly developed low-verbal tasks, one change-location task and one unexpected content task. Thirty children with WS (aged 5-17;01 years) and 30 typically developing (TD) children (aged between 2;10 years and 9;09 years), who were matched for vocabulary comprehension scores were included in the study. Although performance in the WS group was significantly poorer compared to the TD group on all three tasks, performance was not predicted by their receptive vocabulary or grammatical ability scores. In addition, ToM abilities in both groups depended on the cognitive demands of the task at hand. This finding shows that performance on ToM tasks in WS is not necessarily hindered by their delayed language abilities but rather by the task administered. This could potentially affect the diagnosis of developmental disorders, such as Autism Spectrum Disorders, and comparison of ToM abilities across developmental disorders. Readers of this article should be able to (1) describe the current state of theory of mind research in Williams syndrome, (2) identify which cognitive abilities might explain performance on theory of mind tasks in both typically developing children and in children with Williams syndrome, and (3) interpret the importance of task demands when assessing children's theory of mind abilities. Copyright © 2013 Elsevier Inc. All rights reserved.

High Strain Rate Deformation Modeling of a Polymer Matrix Composite. Part 2; Composite Micromechanical Model

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Stouffer, Donald C.

1998-01-01

Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this second paper of a two part report, a three-dimensional composite micromechanical model is described which allows for the analysis of the rate dependent, nonlinear deformation response of a polymer matrix composite. Strain rate dependent inelastic constitutive equations utilized to model the deformation response of a polymer are implemented within the micromechanics method. The deformation response of two representative laminated carbon fiber reinforced composite materials with varying fiber orientation has been predicted using the described technique. The predicted results compare favorably to both experimental values and the response predicted by the Generalized Method of Cells, a well-established micromechanics analysis method.

Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis.

PubMed

Uzun, Harun; Yıldız, Zeynep; Goldfarb, Jillian L; Ceylan, Selim

2017-06-01

As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel artificial neural network model with a 3-3-1 tangent sigmoid architecture to predict biomasses' higher heating values from only their proximate analyses, requiring minimal specificity as compared to models based on elemental composition. The model presented has a considerably higher correlation coefficient (0.963) and lower root mean square (0.375), mean absolute (0.328), and mean bias errors (0.010) than other models presented in the literature which, at least when applied to the present data set, tend to under-predict the combustion enthalpy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inference of beliefs and emotions in patients with Alzheimer's disease.

PubMed

Zaitchik, Deborah; Koff, Elissa; Brownell, Hiram; Winner, Ellen; Albert, Marilyn

2006-01-01

The present study compared 20 patients with mild to moderate Alzheimer's disease with 20 older controls (ages 69-94 years) on their ability to make inferences about emotions and beliefs in others. Six tasks tested their ability to make 1st-order and 2nd-order inferences as well as to offer explanations and moral evaluations of human action by appeal to emotions and beliefs. Results showed that the ability to infer emotions and beliefs in 1st-order tasks remains largely intact in patients with mild to moderate Alzheimer's. Patients were able to use mental states in the prediction, explanation, and moral evaluation of behavior. Impairment on 2nd-order tasks involving inference of mental states was equivalent to impairment on control tasks, suggesting that patients' difficulty is secondary to their cognitive impairments. ((c) 2006 APA, all rights reserved).

Self-assessment in schizophrenia: Accuracy of evaluation of cognition and everyday functioning.

PubMed

Gould, Felicia; McGuire, Laura Stone; Durand, Dante; Sabbag, Samir; Larrauri, Carlos; Patterson, Thomas L; Twamley, Elizabeth W; Harvey, Philip D

2015-09-01

Self-assessment deficits, often referred to as impaired insight or unawareness of illness, are well established in people with schizophrenia. There are multiple levels of awareness, including awareness of symptoms, functional deficits, cognitive impairments, and the ability to monitor cognitive and functional performance in an ongoing manner. The present study aimed to evaluate the comparative predictive value of each aspect of awareness on the levels of everyday functioning in people with schizophrenia. We examined multiple aspects of self-assessment of functioning in 214 people with schizophrenia. We also collected information on everyday functioning rated by high contact clinicians and examined the importance of self-assessment for the prediction of real-world functional outcomes. The relative impact of performance-based measures of cognition, functional capacity, and metacognitive performance on everyday functioning was also examined. Misestimation of ability emerged as the strongest predictor of real-world functioning and exceeded the influences of cognitive performance, functional capacity performance, and performance-based assessment of metacognitive monitoring. The relative contribution of the factors other than self-assessment varied according to which domain of everyday functioning was being examined, but, in all cases, accounted for less predictive variance. These results underscore the functional impact of misestimating one's current functioning and relative level of ability. These findings are consistent with the use of insight-focused treatments and compensatory strategies designed to increase self-awareness in multiple functional domains. (c) 2015 APA, all rights reserved).

Self Assessment in Schizophrenia: Accuracy of Evaluation of Cognition and Everyday Functioning

PubMed Central

Gould, Felicia; McGuire, Laura Stone; Durand, Dante; Sabbag, Samir; Larrauri, Carlos; Patterson, Thomas L.; Twamley, Elizabeth W.; Harvey, Philip D.

2015-01-01

Objective Self-assessment deficits, often referred to as impaired insight or unawareness of illness, are well established in people with schizophrenia. There are multiple levels of awareness, including awareness of symptoms, functional deficits, cognitive impairments, and the ability to monitor cognitive and functional performance in an ongoing manner. The present study aimed to evaluate the comparative predictive value of each aspect of awareness on the levels of everyday functioning in people with schizophrenia. Method We examined multiple aspects of self-assessment of functioning in 214 people with schizophrenia. We also collected information on everyday functioning rated by high contact clinicians and examined the importance of self-assessment for the prediction of real world functional outcomes. The relative impact of performance based measures of cognition, functional capacity, and metacognitive performance on everyday functioning was also examined. Results Misestimation of ability emerged as the strongest predictor of real world functioning and exceeded the influences of cognitive performance, functional capacity performance, and performance-based assessment of metacognitive monitoring. The relative contribution of the factors other than self-assessment varied according to which domain of everyday functioning was being examined, but in all cases, accounted for less predictive variance. Conclusions These results underscore the functional impact of misestimating one’s current functioning and relative level of ability. These findings are consistent with the use of insight-focused treatments and compensatory strategies designed to increase self-awareness in multiple functional domains. PMID:25643212

Low verbal ability predicts later violence in adolescent boys with serious conduct problems.

PubMed

Manninen, Marko; Lindgren, Maija; Huttunen, Matti; Ebeling, Hanna; Moilanen, Irma; Kalska, Hely; Suvisaari, Jaana; Therman, Sebastian

2013-10-01

Delinquent adolescents are a known high-risk group for later criminality. Cognitive deficits correlate with adult criminality, and specific cognitive deficits might predict later criminality in the high-risk adolescents. This study aimed to explore the neuropsychological performance and predictors of adult criminal offending in adolescents with severe behavioural problems. Fifty-three adolescents (33 boys and 20 girls), aged 15-18 years, residing in a reform school due to serious conduct problems, were examined for neuropsychological profile and psychiatric symptoms. Results were compared with a same-age general population control sample, and used for predicting criminality 5 years after the baseline testing. The reform school adolescents' neuropsychological performance was weak on many tasks, and especially on the verbal domain. Five years after the baseline testing, half of the reform school adolescents had obtained a criminal record. Males were overrepresented in both any criminality (75% vs. 10%) and in violent crime (50% vs. 5%). When cognitive variables, psychiatric symptoms and background factors were used as predictors for later offending, low verbal intellectual ability turned out to be the most significant predictor of a criminal record and especially a record of violent crime. Neurocognitive deficits, especially in the verbal and attention domains, are common among delinquent adolescents. Among males, verbal deficits are the best predictors for later criminal offending and violence. Assessing verbal abilities among adolescent population with conduct problems might prove useful as a screening method for inclusion in specific therapies for aggression management.

Can pre-season fitness measures predict time to injury in varsity athletes?: a retrospective case control study

PubMed Central

2012-01-01

Background The ability to determine athletic performance in varsity athletes using preseason measures has been established. The ability of pre-season performance measures and athlete’s exposure to predict the incidence of injuries is unclear. Thus our purpose was to determine the ability of pre-season measures of athletic performance to predict time to injury in varsity athletes. Methods Male and female varsity athletes competing in basketball, volleyball and ice hockey participated in this study. The main outcome measures were injury prevalence, time to injury (based on calculated exposure) and pre-season fitness measures as predictors of time to injury. Fitness measures were Apley’s range of motion, push-up, curl-ups, vertical jump, modified Illinois agility, and sit-and-reach. Cox regression models were used to identify which baseline fitness measures were predictors of time to injury. Results Seventy-six percent of the athletes reported 1 or more injuries. Mean times to initial injury were significantly different for females and males (40.6% and 66.1% of the total season (p < 0.05), respectively). A significant univariate correlation was observed between push-up performance and time to injury (Pearson’s r = 0.332, p < 0.01). No preseason fitness measure impacted the hazard of injury. Regardless of sport, female athletes had significantly shorter time to injury than males (Hazard Ratio = 2.2, p < 0.01). Athletes playing volleyball had significantly shorter time to injury (Hazard Ratio = 4.2, p < 0.01) compared to those playing hockey or basketball. Conclusions When accounting for exposure, gender, sport and fitness measures, prediction of time to injury was influenced most heavily by gender and sport. PMID:22824555

Cognitive Abilities Underlying Reading Accuracy, Fluency and Spelling Acquisition in Korean Hangul Learners from Grades 1 to 4: A Cross-Sectional Study.

PubMed

Park, Hyun-Rin; Uno, Akira

2015-08-01

The purpose of this cross-sectional study was to examine the cognitive abilities that predict reading and spelling performance in Korean children in Grades 1 to 4, depending on expertise and reading experience. As a result, visual cognition, phonological awareness, naming speed and receptive vocabulary significantly predicted reading accuracy in children in Grades 1 and 2, whereas visual cognition, phonological awareness and rapid naming speed did not predict reading accuracy in children in higher grades. For reading, fluency, phonological awareness, rapid naming speed and receptive vocabulary were crucial abilities in children in Grades 1 to 3, whereas phonological awareness was not a significant predictor in children in Grade 4. In spelling, reading ability and receptive vocabulary were the most important abilities for accurate Hangul spelling. The results suggested that the degree of cognitive abilities required for reading and spelling changed depending on expertise and reading experience. Copyright © 2015 John Wiley & Sons, Ltd.

Executive function predicts the development of play skills for verbal preschoolers with autism spectrum disorders.

PubMed

Faja, Susan; Dawson, Geraldine; Sullivan, Katherine; Meltzoff, Andrew N; Estes, Annette; Bernier, Raphael

2016-12-01

Executive function and play skills develop in early childhood and are linked to cognitive and language ability. The present study examined these abilities longitudinally in two groups with autism spectrum disorder-a group with higher initial language (n = 30) and a group with lower initial language ability (n = 36). Among the lower language group, concurrent nonverbal cognitive ability contributed most to individual differences in executive function and play skills. For the higher language group, executive function during preschool significantly predicted play ability at age 6 over and above intelligence, but early play did not predict later executive function. These results suggested that factors related to the development of play and executive function differ for subgroups of children with different language abilities and that early executive function skills may be critical in order for verbal children with autism to develop play. Autism Res 2016, 9: 1274-1284. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Predicting Language Outcome and Recovery After Stroke (PLORAS)

PubMed Central

Price, CJ; Seghier, ML; Leff, AP

2013-01-01

The ability of comprehend and produce speech after stroke depends on whether the areas of the brain that support language have been damaged. Here we review two different ways to predict language outcome after stroke. The first depends on understanding the neural circuits that support language. This model-based approach is a challenging endeavor because language is a complex cognitive function that involves the interaction of many different brain areas. The second approach does not require an understanding of why a lesion impairs language, instead, predictions are made on the basis of how previous patients with the same lesion recovered. This requires a database storing the speech and language abilities of a large population of patients who have, between them, incurred a comprehensive range of focal brain damage. In addition it requires a system that converts an MRI scan from a new patient into a 3D description of the lesion and then compares this lesion to all others on the database. The outputs of this system are the longitudinal language outcomes of corresponding patients in the database. This will provide a new patient, their carers and the clinician team managing them the range of likely recovery patterns over a variety of language measures. PMID:20212513

Application of principal component regression and artificial neural network in FT-NIR soluble solids content determination of intact pear fruit

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Fu, Xiaping; Lu, Huishan

2005-11-01

The artificial neural networks (ANNs) have been used successfully in applications such as pattern recognition, image processing, automation and control. However, majority of today's applications of ANNs is back-propagate feed-forward ANN (BP-ANN). In this paper, back-propagation artificial neural networks (BP-ANN) were applied for modeling soluble solid content (SSC) of intact pear from their Fourier transform near infrared (FT-NIR) spectra. One hundred and sixty-four pear samples were used to build the calibration models and evaluate the models predictive ability. The results are compared to the classical calibration approaches, i.e. principal component regression (PCR), partial least squares (PLS) and non-linear PLS (NPLS). The effects of the optimal methods of training parameters on the prediction model were also investigated. BP-ANN combine with principle component regression (PCR) resulted always better than the classical PCR, PLS and Weight-PLS methods, from the point of view of the predictive ability. Based on the results, it can be concluded that FT-NIR spectroscopy and BP-ANN models can be properly employed for rapid and nondestructive determination of fruit internal quality.

A Quantile Regression Approach to Understanding the Relations Among Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students.

PubMed

Tighe, Elizabeth L; Schatschneider, Christopher

2016-07-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.

Writing Abilities Longitudinally Predict Academic Outcomes of Adolescents with ADHD

PubMed Central

Molitor, Stephen J.; Langberg, Joshuah M.; Bourchtein, Elizaveta; Eddy, Laura D.; Dvorsky, Melissa R.; Evans, Steven W.

2016-01-01

Students with ADHD often experience a host of negative academic outcomes and deficits in reading and mathematics abilities contribute to these academic impairments. Students with ADHD may also have difficulties with written expression but there has been minimal research in this area and it is not clear whether written expression abilities uniquely contribute to the academic functioning of students with ADHD. The current study included a sample of 104 middle school students diagnosed with ADHD (grades 6–8). Participants were followed longitudinally to evaluate whether written expression abilities at baseline predicted student GPA and parent ratings of academic impairment 18 months later, after controlling for reading ability and additional relevant covariates. Written expression abilities longitudinally predicted both academic outcomes above and beyond ADHD and ODD symptoms, medication use, reading ability, and baseline values of GPA and parent-rated academic impairment. Follow-up analyses revealed that no single aspect of written expression was demonstrably more impactful on academic outcomes than the others, suggesting that writing as an entire process should be the focus of intervention. PMID:26783650

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

PubMed

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

An improved null model for assessing the net effects of multiple stressors on communities.

PubMed

Thompson, Patrick L; MacLennan, Megan M; Vinebrooke, Rolf D

2018-01-01

Ecological stressors (i.e., environmental factors outside their normal range of variation) can mediate each other through their interactions, leading to unexpected combined effects on communities. Determining whether the net effect of stressors is ecologically surprising requires comparing their cumulative impact to a null model that represents the linear combination of their individual effects (i.e., an additive expectation). However, we show that standard additive and multiplicative null models that base their predictions on the effects of single stressors on community properties (e.g., species richness or biomass) do not provide this linear expectation, leading to incorrect interpretations of antagonistic and synergistic responses by communities. We present an alternative, the compositional null model, which instead bases its predictions on the effects of stressors on individual species, and then aggregates them to the community level. Simulations demonstrate the improved ability of the compositional null model to accurately provide a linear expectation of the net effect of stressors. We simulate the response of communities to paired stressors that affect species in a purely additive fashion and compare the relative abilities of the compositional null model and two standard community property null models (additive and multiplicative) to predict these linear changes in species richness and community biomass across different combinations (both positive, negative, or opposite) and intensities of stressors. The compositional model predicts the linear effects of multiple stressors under almost all scenarios, allowing for proper classification of net effects, whereas the standard null models do not. Our findings suggest that current estimates of the prevalence of ecological surprises on communities based on community property null models are unreliable, and should be improved by integrating the responses of individual species to the community level as does our compositional null model. © 2017 John Wiley & Sons Ltd.

An assessment of predictive value of the biophysical profile in women with preeclampsia using data from the fullPIERS database.

PubMed

Payne, Beth A; Kyle, Phillipa M; Lim, Kenneth; Lisonkova, Sarka; Magee, Laura A; Pullar, Barbra; Qu, Ziguang; von Dadelszen, Peter

2013-07-01

Pre-eclampsia is associated with increased risk to both the mother and fetus. Effective monitoring of the fetal condition is essential to the management of women with pre-eclampsia. The biophysical profile (BPP) is one monitoring tool available to clinicians. To compare the BPP test with cardiotocography/non-stress test (CTG/NST) alone for their ability to predict fetal acidemia at birth or a composite adverse perinatal outcome among women with preeclampsia and to estimate the effect of BPP assessment on mode of delivery and birth outcome. Secondary analysis of a prospective cohort of women with preeclampsia. The predictive ability of the tests was assessed based on sensitivity, specificity, positive and negative likelihood ratios (LR+, LR-). Women assessed with the BPP were compared with matched controls not assessed with the BPP to determine the odds of Cesarean delivery or adverse perinatal outcomes after adjustment for potential confounders. Five out of 89 women (5.6%) had an abnormal BPP; 18 out of 89 (20.2%) had an abnormal CTG/NST. Fetal acidemia was diagnosed in 13 fetuses (14.6%); composite adverse perinatal outcome in 68 fetuses/infants (76.4%). Both tests had relatively poor predictive performance for both outcomes (LR+ between 2.50 and 3.90 and LR- between 0.64 and 0.93). Assessment with the BPP was positively associated with fetal acidemia (adjusted OR 4.84; 95% CI 1.33-17.66). The BPP and CTG/NST alone were poor predictors of perinatal outcome in this cohort; multiple tests should be considered when assessing fetal risk in women with preeclampsia. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Self-concept and quality of object relations as predictors of outcome in short- and long-term psychotherapy.

PubMed

Lindfors, Olavi; Knekt, Paul; Heinonen, Erkki; Virtala, Esa

2014-01-01

Quality of object relations and self-concept reflect clinically relevant aspects of personality functioning, but their prediction as suitability factors for psychotherapies of different lengths has not been compared. This study compared their prediction on psychiatric symptoms and work ability in short- and long-term psychotherapy. Altogether 326 patients, 20-46 years of age, with mood and/or anxiety disorder, were randomized to short-term (solution-focused or short-term psychodynamic) psychotherapy and long-term psychodynamic psychotherapy. The Quality of Object Relations Scale (QORS) and the Structural Analysis of Social Behavior (SASB) self-concept questionnaire were measured at baseline, and their prediction on outcome during the 3-year follow-up was assessed by the Symptom Check List Global Severity Index and the Anxiety Scale, the Beck Depression Inventory and by the Work Ability Index, Social Adjustment Scale work subscale and the Perceived Psychological Functioning scale. Negative self-concept strongly and self-controlling characteristics modestly predicted better 3-year outcomes in long-term therapy, after faster early gains in short-term therapy. Patients with a more positive or self-emancipating self-concept, or more mature object relations, experienced more extensive benefits after long-term psychotherapy. The importance of length vs. long-term therapy technique on the differences found is not known. Patients with mild to moderate personality pathology, indicated by poor self-concept, seem to benefit more from long-term than short-term psychotherapy, in reducing risk of depression. Long-term therapy may also be indicated for patients with relatively good psychological functioning. More research is needed on the relative importance of these characteristics in comparison with other patient-related factors. © 2013 Published by Elsevier B.V.

Your Brain on the Movies: A Computational Approach for Predicting Box-office Performance from Viewer’s Brain Responses to Movie Trailers

PubMed Central

Christoforou, Christoforos; Papadopoulos, Timothy C.; Constantinidou, Fofi; Theodorou, Maria

2017-01-01

The ability to anticipate the population-wide response of a target audience to a new movie or TV series, before its release, is critical to the film industry. Equally important is the ability to understand the underlying factors that drive or characterize viewer’s decision to watch a movie. Traditional approaches (which involve pilot test-screenings, questionnaires, and focus groups) have reached a plateau in their ability to predict the population-wide responses to new movies. In this study, we develop a novel computational approach for extracting neurophysiological electroencephalography (EEG) and eye-gaze based metrics to predict the population-wide behavior of movie goers. We further, explore the connection of the derived metrics to the underlying cognitive processes that might drive moviegoers’ decision to watch a movie. Towards that, we recorded neural activity—through the use of EEG—and eye-gaze activity from a group of naive individuals while watching movie trailers of pre-selected movies for which the population-wide preference is captured by the movie’s market performance (i.e., box-office ticket sales in the US). Our findings show that the neural based metrics, derived using the proposed methodology, carry predictive information about the broader audience decisions to watch a movie, above and beyond traditional methods. In particular, neural metrics are shown to predict up to 72% of the variance of the films’ performance at their premiere and up to 67% of the variance at following weekends; which corresponds to a 23-fold increase in prediction accuracy compared to current neurophysiological or traditional methods. We discuss our findings in the context of existing literature and hypothesize on the possible connection of the derived neurophysiological metrics to cognitive states of focused attention, the encoding of long-term memory, and the synchronization of different components of the brain’s rewards network. Beyond the practical implication in predicting and understanding the behavior of moviegoers, the proposed approach can facilitate the use of video stimuli in neuroscience research; such as the study of individual differences in attention-deficit disorders, and the study of desensitization to media violence. PMID:29311885

Your Brain on the Movies: A Computational Approach for Predicting Box-office Performance from Viewer's Brain Responses to Movie Trailers.

PubMed

Christoforou, Christoforos; Papadopoulos, Timothy C; Constantinidou, Fofi; Theodorou, Maria

2017-01-01

The ability to anticipate the population-wide response of a target audience to a new movie or TV series, before its release, is critical to the film industry. Equally important is the ability to understand the underlying factors that drive or characterize viewer's decision to watch a movie. Traditional approaches (which involve pilot test-screenings, questionnaires, and focus groups) have reached a plateau in their ability to predict the population-wide responses to new movies. In this study, we develop a novel computational approach for extracting neurophysiological electroencephalography (EEG) and eye-gaze based metrics to predict the population-wide behavior of movie goers. We further, explore the connection of the derived metrics to the underlying cognitive processes that might drive moviegoers' decision to watch a movie. Towards that, we recorded neural activity-through the use of EEG-and eye-gaze activity from a group of naive individuals while watching movie trailers of pre-selected movies for which the population-wide preference is captured by the movie's market performance (i.e., box-office ticket sales in the US). Our findings show that the neural based metrics, derived using the proposed methodology, carry predictive information about the broader audience decisions to watch a movie, above and beyond traditional methods. In particular, neural metrics are shown to predict up to 72% of the variance of the films' performance at their premiere and up to 67% of the variance at following weekends; which corresponds to a 23-fold increase in prediction accuracy compared to current neurophysiological or traditional methods. We discuss our findings in the context of existing literature and hypothesize on the possible connection of the derived neurophysiological metrics to cognitive states of focused attention, the encoding of long-term memory, and the synchronization of different components of the brain's rewards network. Beyond the practical implication in predicting and understanding the behavior of moviegoers, the proposed approach can facilitate the use of video stimuli in neuroscience research; such as the study of individual differences in attention-deficit disorders, and the study of desensitization to media violence.

Emotion Perception Mediates the Predictive Relationship between Verbal Ability and Functional Outcome in High-Functioning Adults with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Otsuka, Sadao; Uono, Shota; Yoshimura, Sayaka; Zhao, Shuo; Toichi, Motomi

2017-01-01

The aim of this study was to identify specific cognitive abilities that predict functional outcome in high-functioning adults with autism spectrum disorder (ASD), and to clarify the contribution of those abilities and their relationships. In total, 41 adults with ASD performed cognitive tasks in a broad range of neuro- and social cognitive…

Predicting the Ability of Marine Mammal Populations to Compensate for Behavioral Disturbances

DTIC Science & Technology

2014-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Predicting the Ability of Marine Mammal Populations to...determine the ability of marine mammal populations to respond to behavioral disturbances. These tools are to be generic and applicable in a wide range...scale consequences. OBJECTIVES • Develop simple, generic measures that allow the estimation of marine mammal populations and individuals to

Self-Reported Work Ability Predicts Rehabilitation Measures, Disability Pensions, Other Welfare Benefits, and Work Participation: Longitudinal Findings from a Sample of German Employees.

PubMed

Bethge, Matthias; Spanier, Katja; Peters, Elke; Michel, Elliot; Radoschewski, Michael

2017-09-27

Purpose The study examined the performance of the Work Ability Index in predicting rehabilitation measures and disability pensions, sickness absence and unemployment benefits, and work participation among a sample of workers previously receiving sickness absence benefits. Methods Workers aged 40 to 54 years who received sickness absence benefits in 2012 completed the Work Ability Index in 2013. Outcomes were extracted from administrative data records. Results Data for 2149 participants were included (mean age: 47.8 years; 54.4% women). Mean follow-up was 19 months. Work Ability Index scores were poor (7-27 points) in 21% of the participants, and moderate (28-36 points) in 38.4%. In all, 224 rehabilitation measures and 35 disability pensions were approved. Fully adjusted analyses showed increased risk of rehabilitation measures in workers with poor (HR 4.55; 95% CI 3.14-6.60) and moderate scores (HR 2.08; 95% CI 1.43-3.01) compared to workers with good or excellent scores (37-49 points). The risk of a disability pension increased significantly for workers with poor scores (HR 7.78; 95% CI 2.59-23.35). In addition, poor scores were prospectively associated with a longer duration of sickness absence and employment benefits, and fewer employment days and less income from regular employment. Conclusions The Work Ability Index is a potential tool for following up workers who already have an increased risk of permanent work disability due to previous long-term sickness absence.

Predictors of fatigue and work ability in cancer survivors.

PubMed

van Muijen, P; Duijts, S F A; Bonefaas-Groenewoud, K; van der Beek, A J; Anema, J R

2017-12-30

Workers diagnosed with cancer are at risk for job loss or work disability. To determine predictors of fatigue and work ability at 36 months after diagnosis in a population of cancer survivors. Individuals diagnosed with cancer and who applied for work disability benefit at 24 months of sick leave were surveyed at the time of application and again 12 months later. Fatigue was measured using the Functional Assessment of Chronic Illness-Fatigue scale questionnaire and work ability was measured using the work ability index. Linear regression analyses were applied to identify predictors. There were 336 participants. Participants who were divorced or widowed had more physical limitations, more depressive symptoms and were more fatigued at baseline, and who worked in health care demonstrated higher levels of fatigue. Lower fatigue was predicted by having received chemotherapy. A higher level of work ability was predicted by having received chemotherapy, better global health and better work ability at baseline. Lower work ability was predicted by being principal wage earner, insecurity about being free of disease, having more physical limitations and having greater wage loss. Socio-demographic, health- and work-related factors were associated with fatigue and work ability in cancer survivors on long-term sick leave. As fatigue and poor work ability are important risk factors for work disability, addressing the identified predictive factors may assist in mitigation of work disability in cancer survivors. © The Author 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Naturalistic Assessment of Executive Function and Everyday Multitasking in Healthy Older Adults

PubMed Central

McAlister, Courtney; Schmitter-Edgecombe, Maureen

2013-01-01

Everyday multitasking and its cognitive correlates were investigated in an older adult population using a naturalistic task, the Day Out Task. Fifty older adults and 50 younger adults prioritized, organized, initiated and completed a number of subtasks in a campus apartment to prepare for a day out (e.g., gather ingredients for a recipe, collect change for a bus ride). Participants also completed tests assessing cognitive constructs important in multitasking. Compared to younger adults, the older adults took longer to complete the everyday tasks and more poorly sequenced the subtasks. Although they initiated, completed, and interweaved a similar number of subtasks, the older adults demonstrated poorer task quality and accuracy, completing more subtasks inefficiently. For the older adults, reduced prospective memory abilities were predictive of poorer task sequencing, while executive processes and prospective memory were predictive of inefficiently completed subtasks. The findings suggest that executive dysfunction and prospective memory difficulties may contribute to the age-related decline of everyday multitasking abilities in healthy older adults. PMID:23557096

Effect of body size and temperature on respiration of Galaxias maculatus (Pisces: Galaxiidae)

USGS Publications Warehouse

Milano, D.; Vigliano, P.H.; Beauchamp, David A.

2017-01-01

Body mass and temperature are primary determinants of metabolic rate in ectothermic animals. Oxygen consumption of post-larval Galaxias maculatus was measured in respirometry trials under different temperatures (5–21°C) and varying body masses (0.1–>1.5 g) spanning a relevant range of thermal conditions and sizes. Specific respiration rates (R in g O2 g−1 d−1) declined as a power function of body mass and increased exponentially with temperature and was expressed as: R = 0.0007 * W −0.31 * e 0.13 * T. The ability of this model to predict specific respiration rate was evaluated by comparing observed values with those predicted by the model. Our findings suggest that the respiration rate of G. maculatus is the result of multiple interactive processes (intrinsic and extrinsic factors) that modulate each other in ‘meta-mechanistic’ ways; this would help to explain the species’ ability to undergo the complex ontogenetic habitat shifts observed in the lakes of the Andean Patagonic range.

Computational discovery of small open reading frames in Bacillus lehensis

NASA Astrophysics Data System (ADS)

Zainuddin, Nurhafizhoh; Illias, Rosli Md.; Mahadi, Nor Muhammad; Firdaus-Raih, Mohd

2015-09-01

Bacillus lehensis is a Gram-positive and endospore-forming alkalitolerant bacterial strain. In recent years there has been increasing interest in alkaliphilic bacteria and their ability to grow under extreme conditions as well as their ability to serve various important functions in industrial biology especially enzyme production. Small open reading frames (sORFs) have emerged as important regulators in various biological roles such as tumor progression, hormone signalling and stress response. Over the past decade, many biocomputational tools have been developed to predict genes in bacterial genomes. In this study, three softwares were used to predict sORF (≤ 80 aa) in B. lehensis by using whole genome sequence. We used comparative analysis to identify the sORFs in B. lehensis that conserved across all other bacterial genomes. We extended the analysis by doing the homology analysis against protein database. This study established the sORFs in B. lehensis that are conserved across bacteria which might has important biological function which still remain elusive in biological field.

Coping with examinations: exploring relationships between students' coping strategies, implicit theories of ability, and perceived control.

PubMed

Doron, Julie; Stephan, Yannick; Boiché, Julie; Le Scanff, Christine

2009-09-01

Relatively little is known about the contribution of students' beliefs regarding the nature of academic ability (i.e. their implicit theories) on strategies used to deal with examinations. This study applied Dweck's socio-cognitive model of achievement motivation to better understand how students cope with examinations. It was expected that students' implicit theories of academic ability would be related to their use of particular coping strategies to deal with exam-related stress. Additionally, it was predicted that perceived control over exams acts as a mediator between implicit theories of ability and coping. Four hundred and ten undergraduate students (263 males, 147 females), aged from 17 to 26 years old (M=19.73, SD=1.46) were volunteers for the present study. Students completed measures of coping, implicit theories of academic ability, and perception of control over academic examinations during regular classes in the first term of the university year. Multiple regression analyses revealed that incremental beliefs of ability significantly and positively predicted active coping, planning, venting of emotions, seeking social support for emotional and instrumental reasons, whereas entity beliefs positively predicted behavioural disengagement and negatively predicted active coping and acceptance. In addition, analyses revealed that entity beliefs of ability were related to coping strategies through students' perception of control over academic examinations. These results confirm that exam-related coping varies as a function of students' beliefs about the nature of academic ability and their perceptions of control when approaching examinations.

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Computer-aided design of negative allosteric modulators of metabotropic glutamate receptor 5 (mGluR5): Comparative molecular field analysis of aryl ether derivatives.

PubMed

Selvam, Chelliah; Thilagavathi, Ramasamy; Narasimhan, Balasubramanian; Kumar, Pradeep; Jordan, Brian C; Ranganna, Kasturi

2016-02-15

The metabotropic glutamate receptors (mGlu receptors) have emerged as attractive targets for number of neurological and psychiatric disorders. Recently, mGluR5 negative allosteric modulators (NAMs) have gained considerable attention in pharmacological research. Comparative molecular field analysis (CoMFA) was performed on 73 analogs of aryl ether which were reported as mGluR5 NAMs. The study produced a statistically significant model with high correlation coefficient and good predictive abilities. Published by Elsevier Ltd.

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927

The Roles of Cognitive and Language Abilities in Predicting Decoding and Reading Comprehension: Comparisons of Dyslexia and Specific Language Impairment

ERIC Educational Resources Information Center

Lauterbach, Alexandra A.; Park, Yujeong; Lombardino, Linda J.

2017-01-01

This study aimed to (a) explore the roles of cognitive and language variables in predicting reading abilities of two groups of individuals with reading disabilities (i.e., dyslexia and specific language impairment) and (b) examine which variable(s) is the most predictive in differentiating two groups. Inclusion/exclusion criteria applied to…

For Whom the Mind Wanders, and When, Varies Across Laboratory and Daily-Life Settings.

PubMed

Kane, Michael J; Gross, Georgina M; Chun, Charlotte A; Smeekens, Bridget A; Meier, Matt E; Silvia, Paul J; Kwapil, Thomas R

2017-09-01

Undergraduates ( N = 274) participated in a weeklong daily-life experience-sampling study of mind wandering after being assessed in the lab for executive-control abilities (working memory capacity; attention-restraint ability; attention-constraint ability; and propensity for task-unrelated thoughts, or TUTs) and personality traits. Eight times a day, electronic devices prompted subjects to report on their current thoughts and context. Working memory capacity and attention abilities predicted subjects' TUT rates in the lab, but predicted the frequency of daily-life mind wandering only as a function of subjects' momentary attempts to concentrate. This pattern replicates prior daily-life findings but conflicts with laboratory findings. Results for personality factors also revealed different associations in the lab and daily life: Only neuroticism predicted TUT rate in the lab, but only openness predicted mind-wandering rate in daily life (both predicted the content of daily-life mind wandering). Cognitive and personality factors also predicted dimensions of everyday thought other than mind wandering, such as subjective judgments of controllability of thought. Mind wandering in people's daily environments and TUTs during controlled and artificial laboratory tasks have different correlates (and perhaps causes). Thus, mind-wandering theories based solely on lab phenomena may be incomplete.

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.

Formability prediction for AHSS materials using damage models

NASA Astrophysics Data System (ADS)

Amaral, R.; Santos, Abel D.; José, César de Sá; Miranda, Sara

2017-05-01

Advanced high strength steels (AHSS) are seeing an increased use, mostly due to lightweight design in automobile industry and strict regulations on safety and greenhouse gases emissions. However, the use of these materials, characterized by a high strength to weight ratio, stiffness and high work hardening at early stages of plastic deformation, have imposed many challenges in sheet metal industry, mainly their low formability and different behaviour, when compared to traditional steels, which may represent a defying task, both to obtain a successful component and also when using numerical simulation to predict material behaviour and its fracture limits. Although numerical prediction of critical strains in sheet metal forming processes is still very often based on the classic forming limit diagrams, alternative approaches can use damage models, which are based on stress states to predict failure during the forming process and they can be classified as empirical, physics based and phenomenological models. In the present paper a comparative analysis of different ductile damage models is carried out, in order numerically evaluate two isotropic coupled damage models proposed by Johnson-Cook and Gurson-Tvergaard-Needleman (GTN), each of them corresponding to the first two previous group classification. Finite element analysis is used considering these damage mechanics approaches and the obtained results are compared with experimental Nakajima tests, thus being possible to evaluate and validate the ability to predict damage and formability limits for previous defined approaches.

A simplified clinical prediction rule for prognosticating independent walking after spinal cord injury: a prospective study from a Canadian multicenter spinal cord injury registry.

PubMed

Hicks, Katharine E; Zhao, Yichen; Fallah, Nader; Rivers, Carly S; Noonan, Vanessa K; Plashkes, Tova; Wai, Eugene K; Roffey, Darren M; Tsai, Eve C; Paquet, Jerome; Attabib, Najmedden; Marion, Travis; Ahn, Henry; Phan, Philippe

2017-10-01

Traumatic spinal cord injury (SCI) is a debilitating condition with limited treatment options for neurologic or functional recovery. The ability to predict the prognosis of walking post injury with emerging prediction models could aid in rehabilitation strategies and reintegration into the community. To revalidate an existing clinical prediction model for independent ambulation (van Middendorp et al., 2011) using acute and long-term post-injury follow-up data, and to investigatethe accuracy of a simplified model using prospectively collected data from a Canadian multicenter SCI database, the Rick Hansen Spinal Cord Injury Registry (RHSCIR). Prospective cohort study. The analysis cohort consisted of 278 adult individuals with traumatic SCI enrolled in the RHSCIR for whom complete neurologic examination data and Functional Independence Measure (FIM) outcome data were available. The FIM locomotor score was used to assess independent walking ability (defined as modified or complete independence in walk or combined walk and wheelchair modality) at 1-year follow-up for each participant. A logistic regression (LR) model based on age and four neurologic variables was applied to our cohort of 278 RHSCIR participants. Additionally, a simplified LR model was created. The Hosmer-Lemeshow goodness of fit test was used to check if the predictive model is applicable to our data set. The performance of the model was verified by calculating the area under the receiver operating characteristic curve (AUC). The accuracy of the model was tested using a cross-validation technique. This study was supported by a grant from The Ottawa Hospital Academic Medical Organization ($50,000 over 2 years). The RHSCIR is sponsored by the Rick Hansen Institute and is supported by funding from Health Canada, Western Economic Diversification Canada, and the provincial governments of Alberta, British Columbia, Manitoba, and Ontario. ET and JP report receiving grants from the Rick Hansen Institute (approximately $60,000 and $30,000 per year, respectively). DMR reports receiving remuneration for consulting services provided to Palladian Health, LLC and Pacira Pharmaceuticals, Inc ($20,000-$30,000 annually), although neither relationship presents a potential conflict of interest with the submitted work. KEH received a grant for involvement in the present study from the Government of Canada as part of the Canada Summer Jobs Program ($3,000). JP reports receiving an educational grant from Medtronic Canada outside of the submitted work ($75,000 annually). TM reports receiving educational fellowship support from AO Spine, AO Trauma, and Medtronic; however, none of these relationships are financial in nature. All remaining authors have no conflicts of interest to disclose. The fitted prediction model generated 85% overall classification accuracy, 79% sensitivity, and 90% specificity. The prediction model was able to accurately classify independent walking ability (AUC 0.889, 95% confidence interval [CI] 0.846-0.933, p<.001) compared with the existing prediction model, despite the use of a different outcome measure (FIM vs. Spinal Cord Independence Measure) to qualify walking ability. A simplified, three-variable LR model based on age and two neurologic variables had an overall classification accuracy of 84%, with 76% sensitivity and 90% specificity, demonstrating comparable accuracy with its five-variable prediction model counterpart. The AUC was 0.866 (95% CI 0.816-0.916, p<.01), only marginally less than that of the existing prediction model. A simplified predictive model with similar accuracy to a more complex model for predicting independent walking was created, which improves utility in a clinical setting. Such models will allow clinicians to better predict the prognosis of ambulation in individuals who have sustained a traumatic SCI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species.

PubMed

Perumal, Deepak; Lim, Chu Sing; Chow, Vincent T K; Sakharkar, Kishore R; Sakharkar, Meena K

2008-09-10

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

A comparison between the clinical significance and growth mixture modelling early change methods at predicting negative outcomes.

PubMed

Flood, Nicola; Page, Andrew; Hooke, Geoff

2018-05-03

Routine outcome monitoring benefits treatment by identifying potential no change and deterioration. The present study compared two methods of identifying early change and their ability to predict negative outcomes on self-report symptom and wellbeing measures. 1467 voluntary day patients participated in a 10-day group Cognitive Behaviour Therapy (CBT) program and completed the symptom and wellbeing measures daily. Early change, as defined by (a) the clinical significance method and (b) longitudinal modelling, was compared on each measure. Early change, as defined by the simpler clinical significance method, was superior at predicting negative outcomes than longitudinal modelling. The longitudinal modelling method failed to detect a group of deteriorated patients, and agreement between the early change methods and the final unchanged outcome was higher for the clinical significance method. Therapists could use the clinical significance early change method during treatment to alert them of patients at risk for negative outcomes, which in turn could allow therapists to prevent those negative outcomes from occurring.

Structural and Optical Properties Studies Of Ar2+ Ion Implanted Mn Deposited GaAs

NASA Astrophysics Data System (ADS)

De Gennaro, Michele; Caridi, Domenico; de Nicola, Carlo

2010-09-01

In this paper we propose a numerical approach for noise prediction of high-speed propellers for Turboprop applications. It is based on a RANS approach for aerodynamic simulation coupled with Ffowcs Williams-Hawkings (FW-H) Acoustic Analogy for propeller noise prediction. The test-case geometry adopted for this study is the 8-bladed NASA SR2 transonic cruise propeller, and simulated Sound Pressure Levels (SPL) have been compared with experimental data available from Wind Tunnel and Flight Tests for different microphone locations in a range of Mach numbers between 0.78 and 0.85 and rotational velocities between 7000 and 9000 rpm. Results show the ability of this approach to predict noise to within a few dB of experimental data. Moreover corrections are provided to be applied to acoustic numerical results in order for them to be compared with Wind Tunnel and Flight Test experimental data, as well computational grid requirements and guidelines in order to perform complete aerodynamic and aeroacoustic calculations with highly competitive computational cost.

SEC proton prediction model: verification and analysis.

PubMed

Balch, C C

1999-06-01

This paper describes a model that has been used at the NOAA Space Environment Center since the early 1970s as a guide for the prediction of solar energetic particle events. The algorithms for proton event probability, peak flux, and rise time are described. The predictions are compared with observations. The current model shows some ability to distinguish between proton event associated flares and flares that are not associated with proton events. The comparisons of predicted and observed peak flux show considerable scatter, with an rms error of almost an order of magnitude. Rise time comparisons also show scatter, with an rms error of approximately 28 h. The model algorithms are analyzed using historical data and improvements are suggested. Implementation of the algorithm modifications reduces the rms error in the log10 of the flux prediction by 21%, and the rise time rms error by 31%. Improvements are also realized in the probability prediction by deriving the conditional climatology for proton event occurrence given flare characteristics.

How do individuals with Asperger syndrome respond to nonliteral language and inappropriate requests in computer-mediated communication?

PubMed

Rajendran, Gnanathusharan; Mitchell, Peter; Rickards, Hugh

2005-08-01

Computer-mediated communication in individuals with Asperger syndrome, Tourette syndrome and normal controls was explored with a program called Bubble Dialogue (Gray, Creighton, McMahon, and Cunninghamn (1991)) in which the users type text into speech bubbles. Two scenarios, based on Happé (1994) were adapted to investigate understanding of figure of speech and sarcasm, and a third, developed by ourselves, looked at responses to inappropriate requests (lending money and disclosing home address on a first meeting). Dialogue transcripts were assessed by 62 raters who were blind to the clinical diagnoses. Hierarchical linear modelling revealed that rated understanding of a figure of speech was predicted mainly by verbal ability and executive ability, as well as by clinical diagnosis, whereas handling inappropriate requests was predicted by age, verbal ability, executive ability and diagnosis. Notably, the Tourette comparison group showed better understanding than the Asperger group in interpreting a figure of speech and handling inappropriate requests, and differences between these groups were possibly attributable to individual differences in executive ability. In contrast, understanding sarcasm was predicted by age but not by either verbal ability, executive ability or clinical diagnosis. Evidently, there is a complicated relation between Asperger syndrome, verbal ability and executive abilities with respect to communicative performance.

The Influence of Spelling Ability on Vocabulary Choices When Writing for Children With Dyslexia.

PubMed

Sumner, Emma; Connelly, Vincent; Barnett, Anna L

2016-01-01

Spelling is a prerequisite to expressing vocabulary in writing. Research has shown that children with dyslexia are hesitant spellers when composing. This study aimed to determine whether the hesitant spelling of children with dyslexia, evidenced by frequent pausing, affects vocabulary choices when writing. A total of 31 children with dyslexia, mean age 9 years, were compared to typically developing groups of children: the first matched by age, the second by spelling ability. Oral vocabulary was measured and children completed a written and verbal compositional task. Lexical diversity comparisons were made across written and verbal compositions to highlight the constraint of having to select and spell words. A digital writing tablet recorded the writing. Children with dyslexia and the spelling-ability group made a high proportion of spelling errors and within-word pauses, and had a lower lexical diversity within their written compositions compared to their verbal compositions. The age-matched peers demonstrated the opposite pattern. Spelling ability and pausing predicted 53% of the variance in written lexical diversity of children with dyslexia, demonstrating the link between spelling and vocabulary when writing. Oral language skills had no effect. Lexical diversity correlated with written and verbal text quality for all groups. Practical implications are discussed and related to writing models. © Hammill Institute on Disabilities 2014.

A Comparative Study of Glasgow Coma Scale and Full Outline of Unresponsiveness Scores for Predicting Long-Term Outcome After Brain Injury.

PubMed

McNett, Molly M; Amato, Shelly; Philippbar, Sue Ann

2016-01-01

The aim of this study was to compare predictive ability of hospital Glasgow Coma Scale (GCS) scores and scores obtained using a novel coma scoring tool (the Full Outline of Unresponsiveness [FOUR] scale) on long-term outcomes among patients with traumatic brain injury. Preliminary research of the FOUR scale suggests that it is comparable with GCS for predicting mortality and functional outcome at hospital discharge. No research has investigated relationships between coma scores and outcome 12 months postinjury. This is a prospective cohort study. Data were gathered on adult patients with traumatic brain injury admitted to urban level I trauma center. GCS and FOUR scores were assigned at 24 and 72 hours and at hospital discharge. Glasgow Outcome Scale scores were assigned at 6 and 12 months. The sample size was n = 107. Mean age was 53.5 (SD = ±21, range = 18-91) years. Spearman correlations were comparable and strongest among discharge GCS and FOUR scores and 12-month outcome (r = .73, p < .000; r = .72, p < .000). Multivariate regression models indicate that age and discharge GCS were the strongest predictors of outcome. Areas under the curve were similar for GCS and FOUR scores, with discharge scores occupying the largest areas. GCS and FOUR scores were comparable in bivariate associations with long-term outcome. Discharge coma scores performed best for both tools, with GCS discharge scores predictive in multivariate models.

CFD code calibration and inlet-fairing effects on a 3D hypersonic powered-simulation model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure dam. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing-inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flowfield differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

CFD Code Calibration and Inlet-Fairing Effects On a 3D Hypersonic Powered-Simulation Model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure data. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing- inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flow- field differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

Modeling the growth of Lactobacillus viridescens under non-isothermal conditions in vacuum-packed sliced ham.

PubMed

Silva, Nathália Buss da; Longhi, Daniel Angelo; Martins, Wiaslan Figueiredo; Laurindo, João Borges; Aragão, Gláucia Maria Falcão de; Carciofi, Bruno Augusto Mattar

2017-01-02

Lactic acid bacteria (LAB) are responsible for spoiling vacuum-packed meat products, such as ham. Since the temperature is the main factor affecting the microbial dynamic, the use of mathematical models describing the microbial behavior into a non-isothermal environment can be very useful for predicting food shelf life. In this study, the growth of Lactobacillus viridescens was measured in vacuum-packed sliced ham under non-isothermal conditions, and the predictive ability of primary (Baranyi and Roberts, 1994) and secondary (Square Root) models were assessed using parameters estimated in MRS culture medium under isothermal conditions (between 4 and 30°C). Fresh ham piece was sterilized, sliced, inoculated, vacuum-packed, and stored in a temperature-controlled incubator at five different non-isothermal conditions (between 4 and 25°C) and one isothermal condition (8°C). The mathematical models obtained in MRS medium were assessed by comparing predicted values with L. viridescens growth data in vacuum-packed ham. Its predictive ability was assessed through statistical indexes, with good results (bias factor between 0.95 and 1.03; accuracy factor between 1.04 and 1.07, and RMSE between 0.76 and 1.33), especially in increasing temperature, which predictions were safe. The model parameters obtained from isothermal growth data in MRS medium enabled to estimate the shelf life of a commercial ham under non-isothermal conditions in the temperature range analyzed. Copyright © 2016 Elsevier B.V. All rights reserved.

Predictive ability of visit-to-visit variability in HbA1c and systolic blood pressure for the development of microalbuminuria and retinopathy in people with type 2 diabetes.

PubMed

Takao, Toshiko; Suka, Machi; Yanagisawa, Hiroyuki; Matsuyama, Yutaka; Iwamoto, Yasuhiko

2017-06-01

We explored whether visit-to-visit variability in both glycated hemoglobin (HbA1c) and systolic blood pressure (SBP) simultaneously predicted the development of microalbuminuria and retinopathy, and whether the predictive ability of these measurements changed according to mean HbA1c and SBP levels in people with type 2 diabetes. A retrospective observational cohort study was conducted on 243 type 2 diabetes patients with normoalbuminuria and 486 without retinopathy at the first visit and within 1year thereafter. The two cohorts were followed up from 1995 until 2012. Multivariate and stratified analyses were performed using Cox proportional hazard models. Microalbuminuria developed in 84 patients and retinopathy in 108. Hazard ratios (HRs) for the development of microalbuminuria associated with the coefficient of variation (CV) and variation independent of mean (VIM) of both HbA1c and SBP significantly increased. In participants with a mean SBP <130mmHg, the HRs for the development of retinopathy associated with CV and VIM of HbA1c were abruptly elevated and significant compared with those with a mean SBP ≥130mmHg. Visit-to-visit variability in both HbA1c and SBP simultaneously predict the development of microalbuminuria. HbA1c variability may predict the development of retinopathy when the mean SBP is normal (<130mmHg). Copyright © 2017 Elsevier B.V. All rights reserved.

The BPAQ: a bone-specific physical activity assessment instrument.

PubMed

Weeks, B K; Beck, B R

2008-11-01

A newly developed bone-specific physical activity questionnaire (BPAQ) was compared with other common measures of physical activity for its ability to predict parameters of bone strength in healthy, young adults. The BPAQ predicted indices of bone strength at clinically relevant sites in both men and women, while other measures did not. Only certain types of physical activity (PA) are notably osteogenic. Most methods to quantify levels of PA fail to account for bone relevant loading. Our aim was to examine the ability of several methods of PA assessment and a new bone-specific measure to predict parameters of bone strength in healthy adults. We recruited 40 men and women (mean age 24.5). Subjects completed the modifiable activity questionnaire, Bouchard 3-day activity record, a recently published bone loading history questionnaire (BLHQ), and wore a pedometer for 14 days. We also administered our bone-specific physical activity questionnaire (BPAQ). Calcaneal broadband ultrasound attenuation (BUA) (QUS-2, Quidel) and densitometric measures (XR-36, Norland) were examined. Multiple regression and correlation analyses were performed on the data. The current activity component of BPAQ was a significant predictor of variance in femoral neck bone mineral density (BMD), lumbar spine BMD, and whole body BMD (R(2) = 0.36-0.68, p < 0.01) for men, while the past activity component of BPAQ predicted calcaneal BUA (R(2) = 0.48, p = 0.001) for women. The BPAQ predicted indices of bone strength at skeletal sites at risk of osteoporotic fracture while other PA measurement tools did not.

Quantifying data worth toward reducing predictive uncertainty

USGS Publications Warehouse

Dausman, A.M.; Doherty, J.; Langevin, C.D.; Sukop, M.C.

2010-01-01

The present study demonstrates a methodology for optimization of environmental data acquisition. Based on the premise that the worth of data increases in proportion to its ability to reduce the uncertainty of key model predictions, the methodology can be used to compare the worth of different data types, gathered at different locations within study areas of arbitrary complexity. The method is applied to a hypothetical nonlinear, variable density numerical model of salt and heat transport. The relative utilities of temperature and concentration measurements at different locations within the model domain are assessed in terms of their ability to reduce the uncertainty associated with predictions of movement of the salt water interface in response to a decrease in fresh water recharge. In order to test the sensitivity of the method to nonlinear model behavior, analyses were repeated for multiple realizations of system properties. Rankings of observation worth were similar for all realizations, indicating robust performance of the methodology when employed in conjunction with a highly nonlinear model. The analysis showed that while concentration and temperature measurements can both aid in the prediction of interface movement, concentration measurements, especially when taken in proximity to the interface at locations where the interface is expected to move, are of greater worth than temperature measurements. Nevertheless, it was also demonstrated that pairs of temperature measurements, taken in strategic locations with respect to the interface, can also lead to more precise predictions of interface movement. Journal compilation ?? 2010 National Ground Water Association.

Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

PubMed

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

2017-12-12

Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

Bilateral Versus Unilateral Cochlear Implants in Children: A Study of Spoken Language Outcomes

PubMed Central

Harris, David; Bennet, Lisa; Bant, Sharyn

2014-01-01

Objectives: Although it has been established that bilateral cochlear implants (CIs) offer additional speech perception and localization benefits to many children with severe to profound hearing loss, whether these improved perceptual abilities facilitate significantly better language development has not yet been clearly established. The aims of this study were to compare language abilities of children having unilateral and bilateral CIs to quantify the rate of any improvement in language attributable to bilateral CIs and to document other predictors of language development in children with CIs. Design: The receptive vocabulary and language development of 91 children was assessed when they were aged either 5 or 8 years old by using the Peabody Picture Vocabulary Test (fourth edition), and either the Preschool Language Scales (fourth edition) or the Clinical Evaluation of Language Fundamentals (fourth edition), respectively. Cognitive ability, parent involvement in children’s intervention or education programs, and family reading habits were also evaluated. Language outcomes were examined by using linear regression analyses. The influence of elements of parenting style, child characteristics, and family background as predictors of outcomes were examined. Results: Children using bilateral CIs achieved significantly better vocabulary outcomes and significantly higher scores on the Core and Expressive Language subscales of the Clinical Evaluation of Language Fundamentals (fourth edition) than did comparable children with unilateral CIs. Scores on the Preschool Language Scales (fourth edition) did not differ significantly between children with unilateral and bilateral CIs. Bilateral CI use was found to predict significantly faster rates of vocabulary and language development than unilateral CI use; the magnitude of this effect was moderated by child age at activation of the bilateral CI. In terms of parenting style, high levels of parental involvement, low amounts of screen time, and more time spent by adults reading to children facilitated significantly better vocabulary and language outcomes. In terms of child characteristics, higher cognitive ability and female sex were predictive of significantly better language outcomes. When family background factors were examined, having tertiary-educated primary caregivers and a family history of hearing loss were significantly predictive of better outcomes. Birth order was also found to have a significant negative effect on both vocabulary and language outcomes, with each older sibling predicting a 5 to 10% decrease in scores. Conclusions: Children with bilateral CIs achieved significantly better vocabulary outcomes, and 8-year-old children with bilateral CIs had significantly better language outcomes than did children with unilateral CIs. These improvements were moderated by children’s ages at both first and second CIs. The outcomes were also significantly predicted by a number of factors related to parenting, child characteristics, and family background. Fifty-one percent of the variance in vocabulary outcomes and between 59 to 69% of the variance in language outcomes was predicted by the regression models. PMID:24557003

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection

PubMed Central

Mwanza, Jean-Claude; Warren, Joshua L.; Hochberg, Jessica T.; Budenz, Donald L.; Chang, Robert T.; Ramulu, Pradeep Y.

2014-01-01

Purpose To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. Methods One hundred and ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike’s information criterion (AIC), and prediction confidence interval lengths (PIL). Results For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDX-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT * NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAPFDT, and interaction GDx-TSNIT*NAP-FDT consistently provided better discriminating abilities for detecting early, moderate and severe glaucoma than the best single variable models. Conclusions The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDX-TSNIT * NAP-FDT provides the best glaucoma prediction compared to all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared to using GDx or FDT alone. PMID:24777046

Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.

PubMed

Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan

2017-08-28

The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical programming language and the Python program HeatMapWrapper [ https://doi.org/10.5281/zenodo.495163 ] for heat map generation.

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding

PubMed Central

2013-01-01

Background In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. Results The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. Conclusions The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least biased, the most precise, robust and stable estimates of predictive accuracy. These properties argue for routinely using Methods 5 and 7 to assess predictive accuracy in genomic selection studies. PMID:24314298

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding.

PubMed

Ould Estaghvirou, Sidi Boubacar; Ogutu, Joseph O; Schulz-Streeck, Torben; Knaak, Carsten; Ouzunova, Milena; Gordillo, Andres; Piepho, Hans-Peter

2013-12-06

In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least biased, the most precise, robust and stable estimates of predictive accuracy. These properties argue for routinely using Methods 5 and 7 to assess predictive accuracy in genomic selection studies.

Unchained Melody: Revisiting the Estimation of SF-6D Values

PubMed Central

Craig, Benjamin M.

2015-01-01

Purpose In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. Methods Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under 3 alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. Results Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9% more). Conclusions Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates. PMID:26359242

Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.

PubMed

Schrag, Tobias A; Westhues, Matthias; Schipprack, Wolfgang; Seifert, Felix; Thiemann, Alexander; Scholten, Stefan; Melchinger, Albrecht E

2018-04-01

The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates. Copyright © 2018 by the Genetics Society of America.

Preschool Executive Functioning Abilities Predict Early Mathematics Achievement

ERIC Educational Resources Information Center

Clark, Caron A. C.; Pritchard, Verena E.; Woodward, Lianne J.

2010-01-01

Impairments in executive function have been documented in school-age children with mathematical learning difficulties. However, the utility and specificity of preschool executive function abilities in predicting later mathematical achievement are poorly understood. This study examined linkages between children's developing executive function…

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…

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

PubMed

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

PubMed Central

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

[Non-invasive fibrosis indexes in predicting acute liver function deterioration after transcatheter arterial chemoembolization].

PubMed

Song, Y P; Zhao, Q Y; Li, S; Wang, H; Wu, P H

2016-03-08

To investigate the ability of two non-invasive fibrosis indexes-APRI, i. e. aspartate transaminase (AST) to platelet (PLT) ratio index, and fibrosis index based on the 4 factors (FIB-4)score in predicting ALFD in patients with unresectable primary HCC and underwent TACE. Clinical data of those patients treated with TACE in Department of Interventional Radiology of the Center from Jan 2010 to Aug 2014 were investigated retrospectively. A total of 366 cases were enrolled after randomized selection, 62 (18.5%) of which developed ALFD after TACE. Child-Pugh score, APRI and FIB-4 score in every case were calculated, receiver operating characteristic (ROC) curve of each model were performed and the predictive abilities of them were assessed by area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity. The AUC of Child-Pugh score, APRI and FIB-4 score were 0.783, 0.752 and 0.758 respectively, while the difference had no significance in statistics, indicating that predictive accuracies of them were similar. APRI≤1.15 and FIB-4≤3.08 had better NPV (90.6% and 93.6%) and sensitivity (65.6% and 80.0%) than Child-Pugh score>6 (NPV=85.8%, sensitivity=27.4%), PPV and specificity of them are 35.7%, 32.9%, 89.5% and 73.7%, 64.2%, 99.3% respectively. Comparing to Child-Pugh score, APRI and FIB-4 score have similar accuracy but better NPV and sensitivity in predicting post-TACE ALFD. Thereafter they are good for selection of low-risk patients for TACE treatment. Candidates with an APRI≤1.15 or a FIB-4≤3.08 or in Child-Pugh a stage are unlikely to develop ALFD thus could receive TACE safely.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

NASA Astrophysics Data System (ADS)

Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

Can multi-subpopulation reference sets improve the genomic predictive ability for pigs?

PubMed

Fangmann, A; Bergfelder-Drüing, S; Tholen, E; Simianer, H; Erbe, M

2015-12-01

In most countries and for most livestock species, genomic evaluations are obtained from within-breed analyses. To achieve reliable breeding values, however, a sufficient reference sample size is essential. To increase this size, the use of multibreed reference populations for small populations is considered a suitable option in other species. Over decades, the separate breeding work of different pig breeding organizations in Germany has led to stratified subpopulations in the breed German Large White. Due to this fact and the limited number of Large White animals available in each organization, there was a pressing need for ascertaining if multi-subpopulation genomic prediction is superior compared with within-subpopulation prediction in pigs. Direct genomic breeding values were estimated with genomic BLUP for the trait "number of piglets born alive" using genotype data (Illumina Porcine 60K SNP BeadChip) from 2,053 German Large White animals from five different commercial pig breeding companies. To assess the prediction accuracy of within- and multi-subpopulation reference sets, a random 5-fold cross-validation with 20 replications was performed. The five subpopulations considered were only slightly differentiated from each other. However, the prediction accuracy of the multi-subpopulations approach was not better than that of the within-subpopulation evaluation, for which the predictive ability was already high. Reference sets composed of closely related multi-subpopulation sets performed better than sets of distantly related subpopulations but not better than the within-subpopulation approach. Despite the low differentiation of the five subpopulations, the genetic connectedness between these different subpopulations seems to be too small to improve the prediction accuracy by applying multi-subpopulation reference sets. Consequently, resources should be used for enlarging the reference population within subpopulation, for example, by adding genotyped females.

The postoperative Model for End stage Liver Disease score as a predictor of short-term outcome after transplantation of extended criteria donor livers.

PubMed

Benko, Tamas; Gallinat, Anja; Minor, Thomas; Saner, Fuat H; Sotiropoulos, Georgios C; Paul, Andreas; Hoyer, Dieter P

2017-06-01

Recently, the postoperative Model for End stage Liver Disease score (POPMELD) was suggested as a definition of postoperative graft dysfunction and a predictor of outcome after liver transplantation (LT). The aim of the present study was to validate this concept in the context of extended criteria donor (ECD) organs. Single-center prospectively collected data (OPAL study/01/11-12/13) of 116 ECD LTs were utilized. For each recipient, the Model for End stage Liver Disease (MELD) score was calculated for 7 postoperative days (PODs). The ability of international normalized ratio, bilirubin, aspartate aminotransferase, Donor Risk Index, a recent definition of early allograft dysfunction, and the POPMELD was compared to predict 90-day graft loss. Predictive abilities were compared by receiver operating characteristic curves, sensitivity and specificity, and positive and negative predictive values. The median Donor Risk Index was 1.8. In all, 60.3% of recipients were men [median age of 54 (23-68) years]. The median POD1-7 peak-aspartate aminotransferase value was 1052 (194-17 577) U/l. The rate of early allograft dysfunction was 22.4%. The 90-day graft survival was 89.7%. Out of possible predictors of the 90-day graft loss MELD on POD5 was the best predictor of outcome (area under the curve=0.84). A MELD score of 16 or more on POD5 predicted the 90-day graft loss with a specificity of 80.8%, a sensitivity of 81.8%, and a positive and negative predictive value of 31 and 97.7%. A MELD score of 16 or more on POD5 is an excellent predictor of outcome in ECD donor LT. Routine evaluation of POPMELD scores might support clinical decision-making and should be reported routinely in clinical trials.

Violent Recidivism: A Long-Time Follow-Up Study of Mentally Disordered Offenders

PubMed Central

Nilsson, Thomas; Wallinius, Märta; Gustavson, Christina; Anckarsäter, Henrik; Kerekes, Nóra

2011-01-01

Background In this prospective study, mentally disordered perpetrators of severe violent and/or sexual crimes were followed through official registers for 59 (range 8 to 73) months. The relapse rate in criminality was assessed, compared between offenders sentenced to prison versus forensic psychiatric care, and the predictive ability of various risk factors (criminological, clinical, and of structured assessment instruments) was investigated. Method One hundred perpetrators were consecutively assessed between 1998 and 2001 by a clinical battery of established instruments covering DSM-IV diagnoses, psychosocial background factors, and structured assessment instruments (HCR-20, PCL-R, and life-time aggression (LHA)). Follow-up data was collected from official registers for: (i) recidivistic crimes, (ii) crimes during ongoing sanction. Results Twenty subjects relapsed in violent criminality during ongoing sanctions (n = 6) or after discharge/parole (n = 14). Individuals in forensic psychiatric care spent significantly more time at liberty after discharge compared to those in prison, but showed significantly fewer relapses. Criminological (age at first conviction), and clinical (conduct disorder and substance abuse/dependence) risk factors, as well as scores on structured assessment instruments, were moderately associated with violent recidivism. Logistic regression analyses showed that the predictive ability of criminological risk factors versus clinical risk factors combined with scores from assessment instruments was comparable, with each set of variables managing to correctly classify about 80% of all individuals, but the only predictors that remained significant in multiple models were criminological (age at first conviction, and a history of substance abuse among primary relatives). Conclusions Only one in five relapsed into serious criminality, with significantly more relapses among subjects sentenced to prison as compared to forensic psychiatric care. Criminological risk factors tended to be the best predictors of violent relapses, while few synergies were seen when the risk factors were combined. Overall, the predictive validity of common risk factors for violent criminality was rather weak. PMID:22022445

Estudio comparativo de los metodos analitico-sintetico y global en el aprendizaje de la lectura (Comparative Study of the Analytical-Synthetical (Phonics) and Global (Sight) Reading Methods).

ERIC Educational Resources Information Center

Carbonell de Grompone, Maria A.; And Others

An investigation into the phonics and sight methods of reading instruction being taught in Uruguay schools seeks valid predictions in support of each approach. The study, written in Spanish, examines the progressive reading habits and abilities of 12 first-grade classes. Teachers assigned to teach each method uniformly had equivalent training and…

The relationship between theory of mind and autobiographical memory in high-functioning autism and Asperger syndrome.

PubMed

Adler, Noga; Nadler, Benny; Eviatar, Zohar; Shamay-Tsoory, Simone G

2010-06-30

The relationship between theory of mind (ToM) and autobiographical memory (AM) in high-functioning autism (HFA) and Asperger syndrome (AS) has never been investigated. Here, we show that ToM abilities could be predicted by levels of AM in HFA and AS as compared to controls, suggesting that difficulties in AM are closely related to ToM impairments in HFA and AS.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Personalized Vehicle Energy Efficiency & Range Predictor/MyGreenCar

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

SAXENA, SAMVEG

MyGreenCar provides users with the ability to predict the range capabilities, fuel economy, and operating costs for any vehicle for their individual driving patterns. Users launce the MyGreeCar mobile app on their smartphones to collect their driving patterns over any duration (e.g. serval days, weeks, months, etc) using a phones's locational capabilities. Using vehicle powertrain models for any user-specified vehicle type, MyGreenCar, calculates the component-level energy and power interactions for the chosen vehicle to predict several important quantities, including: 1. For Evs: Alleviating range anxiety 2. Comparing fuel economy, operating costs, and payback time across models and types.

Predicting reading ability in teenagers who are deaf or hard of hearing: A longitudinal analysis of language and reading.

PubMed

Worsfold, Sarah; Mahon, Merle; Pimperton, Hannah; Stevenson, Jim; Kennedy, Colin

2018-06-01

Deaf and hard of hearing (D/HH) children and young people are known to show group-level deficits in spoken language and reading abilities relative to their hearing peers. However, there is little evidence on the longitudinal predictive relationships between language and reading in this population. To determine the extent to which differences in spoken language ability in childhood predict reading ability in D/HH adolescents. and procedures: Participants were drawn from a population-based cohort study and comprised 53 D/HH teenagers, who used spoken language, and a comparison group of 38 normally hearing teenagers. All had completed standardised measures of spoken language (expression and comprehension) and reading (accuracy and comprehension) at 6-10 and 13-19 years of age. and results: Forced entry stepwise regression showed that, after taking reading ability at age 8 years into account, language scores at age 8 years did not add significantly to the prediction of Reading Accuracy z-scores at age 17 years (change in R 2  = 0.01, p = .459) but did make a significant contribution to the prediction of Reading Comprehension z-scores at age 17 years (change in R 2  = 0.17, p < .001). and implications: In D/HH individuals who are spoken language users, expressive and receptive language skills in middle childhood predict reading comprehension ability in adolescence. Continued intervention to support language development beyond primary school has the potential to benefit reading comprehension and hence educational access for D/HH adolescents. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Visuospatial and Attentional Abilities Predict Driving Simulator Performance Among Older HIV-infected Adults

PubMed Central

Foley, J. M.; Gooding, A. L.; Thames, A. D.; Ettenhofer, M. L.; Kim, M. S.; Castellon, S. A.; Marcotte, T. D.; Sadek, J. R.; Heaton, R. K.; van Gorp, W. G.; Hinkin, C. H.

2013-01-01

Objectives To examine the effects of aging and neuropsychological (NP) impairment on driving simulator performance within a human immunodeficiency virus (HIV)-infected cohort. Methods Participants included 79 HIV-infected adults (n = 58 > age 50, n = 21 ≤ 40) who completed a NP battery and a personnel computer-based driving simulator task. Outcome variables included total completion time (time) and number of city blocks to complete the task (blocks). Results Compared to the younger group, the older group was less efficient in their route finding (blocks over optimum: 25.9 [20.1] vs 14.4 [16.9]; P = .02) and took longer to complete the task (time: 1297.6 [577.6] vs 804.4 [458.5] seconds; P = .001). Regression models within the older adult group indicated that visuospatial abilities (blocks: b = –0.40, P < .001; time: b = –0.40, P = .001) and attention (blocks: b = –0.49, P = .001; time: b = –0.42, P = .006) independently predicted simulator performance. The NP-impaired group performed more poorly on both time and blocks, compared to the NP normal group. Conclusions Older HIV-infected adults may be at risk of driving-related functional compromise secondary to HIV-associated neurocognitive decline. PMID:23314403

Generating highly accurate prediction hypotheses through collaborative ensemble learning

NASA Astrophysics Data System (ADS)

Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

2017-03-01

Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

Nonlinear autoregressive neural networks with external inputs for forecasting of typhoon inundation level.

PubMed

Ouyang, Huei-Tau

2017-08-01

Accurate inundation level forecasting during typhoon invasion is crucial for organizing response actions such as the evacuation of people from areas that could potentially flood. This paper explores the ability of nonlinear autoregressive neural networks with exogenous inputs (NARX) to predict inundation levels induced by typhoons. Two types of NARX architecture were employed: series-parallel (NARX-S) and parallel (NARX-P). Based on cross-correlation analysis of rainfall and water-level data from historical typhoon records, 10 NARX models (five of each architecture type) were constructed. The forecasting ability of each model was assessed by considering coefficient of efficiency (CE), relative time shift error (RTS), and peak water-level error (PE). The results revealed that high CE performance could be achieved by employing more model input variables. Comparisons of the two types of model demonstrated that the NARX-S models outperformed the NARX-P models in terms of CE and RTS, whereas both performed exceptionally in terms of PE and without significant difference. The NARX-S and NARX-P models with the highest overall performance were identified and their predictions were compared with those of traditional ARX-based models. The NARX-S model outperformed the ARX-based models in all three indexes, whereas the NARX-P model exhibited comparable CE performance and superior RTS and PE performance.

Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2010-03-01

Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

Assessing Risk Prediction Models Using Individual Participant Data From Multiple Studies

PubMed Central

Pennells, Lisa; Kaptoge, Stephen; White, Ian R.; Thompson, Simon G.; Wood, Angela M.; Tipping, Robert W.; Folsom, Aaron R.; Couper, David J.; Ballantyne, Christie M.; Coresh, Josef; Goya Wannamethee, S.; Morris, Richard W.; Kiechl, Stefan; Willeit, Johann; Willeit, Peter; Schett, Georg; Ebrahim, Shah; Lawlor, Debbie A.; Yarnell, John W.; Gallacher, John; Cushman, Mary; Psaty, Bruce M.; Tracy, Russ; Tybjærg-Hansen, Anne; Price, Jackie F.; Lee, Amanda J.; McLachlan, Stela; Khaw, Kay-Tee; Wareham, Nicholas J.; Brenner, Hermann; Schöttker, Ben; Müller, Heiko; Jansson, Jan-Håkan; Wennberg, Patrik; Salomaa, Veikko; Harald, Kennet; Jousilahti, Pekka; Vartiainen, Erkki; Woodward, Mark; D'Agostino, Ralph B.; Bladbjerg, Else-Marie; Jørgensen, Torben; Kiyohara, Yutaka; Arima, Hisatomi; Doi, Yasufumi; Ninomiya, Toshiharu; Dekker, Jacqueline M.; Nijpels, Giel; Stehouwer, Coen D. A.; Kauhanen, Jussi; Salonen, Jukka T.; Meade, Tom W.; Cooper, Jackie A.; Cushman, Mary; Folsom, Aaron R.; Psaty, Bruce M.; Shea, Steven; Döring, Angela; Kuller, Lewis H.; Grandits, Greg; Gillum, Richard F.; Mussolino, Michael; Rimm, Eric B.; Hankinson, Sue E.; Manson, JoAnn E.; Pai, Jennifer K.; Kirkland, Susan; Shaffer, Jonathan A.; Shimbo, Daichi; Bakker, Stephan J. L.; Gansevoort, Ron T.; Hillege, Hans L.; Amouyel, Philippe; Arveiler, Dominique; Evans, Alun; Ferrières, Jean; Sattar, Naveed; Westendorp, Rudi G.; Buckley, Brendan M.; Cantin, Bernard; Lamarche, Benoît; Barrett-Connor, Elizabeth; Wingard, Deborah L.; Bettencourt, Richele; Gudnason, Vilmundur; Aspelund, Thor; Sigurdsson, Gunnar; Thorsson, Bolli; Kavousi, Maryam; Witteman, Jacqueline C.; Hofman, Albert; Franco, Oscar H.; Howard, Barbara V.; Zhang, Ying; Best, Lyle; Umans, Jason G.; Onat, Altan; Sundström, Johan; Michael Gaziano, J.; Stampfer, Meir; Ridker, Paul M.; Michael Gaziano, J.; Ridker, Paul M.; Marmot, Michael; Clarke, Robert; Collins, Rory; Fletcher, Astrid; Brunner, Eric; Shipley, Martin; Kivimäki, Mika; Ridker, Paul M.; Buring, Julie; Cook, Nancy; Ford, Ian; Shepherd, James; Cobbe, Stuart M.; Robertson, Michele; Walker, Matthew; Watson, Sarah; Alexander, Myriam; Butterworth, Adam S.; Angelantonio, Emanuele Di; Gao, Pei; Haycock, Philip; Kaptoge, Stephen; Pennells, Lisa; Thompson, Simon G.; Walker, Matthew; Watson, Sarah; White, Ian R.; Wood, Angela M.; Wormser, David; Danesh, John

2014-01-01

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous. PMID:24366051

Assessing risk prediction models using individual participant data from multiple studies.

PubMed

Pennells, Lisa; Kaptoge, Stephen; White, Ian R; Thompson, Simon G; Wood, Angela M

2014-03-01

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

Distribution drivers and physiological responses in geothermal bryophyte communities.

PubMed

García, Estefanía Llaneza; Rosenstiel, Todd N; Graves, Camille; Shortlidge, Erin E; Eppley, Sarah M

2016-04-01

Our ability to explain community structure rests on our ability to define the importance of ecological niches, including realized ecological niches, in shaping communities, but few studies of plant distributions have combined predictive models with physiological measures. Using field surveys and statistical modeling, we predicted distribution drivers in geothermal bryophyte (moss) communities of Lassen Volcanic National Park (California, USA). In the laboratory, we used drying and rewetting experiments to test whether the strong species-specific effects of relative humidity on distributions predicted by the models were correlated with physiological characters. We found that the three most common bryophytes in geothermal communities were significantly affected by three distinct distribution drivers: temperature, light, and relative humidity. Aulacomnium palustre, whose distribution is significantly affected by relative humidity according to our model, and which occurs in high-humidity sites, showed extreme signs of stress after drying and never recovered optimal values of PSII efficiency after rewetting. Campylopus introflexus, whose distribution is not affected by humidity according to our model, was able to maintain optimal values of PSII efficiency for 48 hr at 50% water loss and recovered optimal values of PSII efficiency after rewetting. Our results suggest that species-specific environmental stressors tightly constrain the ecological niches of geothermal bryophytes. Tests of tolerance to drying in two bryophyte species corresponded with model predictions of the comparative importance of relative humidity as distribution drivers for these species. © 2016 Botanical Society of America.

The Facial Appearance of CEOs: Faces Signal Selection but Not Performance.

PubMed

Stoker, Janka I; Garretsen, Harry; Spreeuwers, Luuk J

2016-01-01

Research overwhelmingly shows that facial appearance predicts leader selection. However, the evidence on the relevance of faces for actual leader ability and consequently performance is inconclusive. By using a state-of-the-art, objective measure for face recognition, we test the predictive value of CEOs' faces for firm performance in a large sample of faces. We first compare the faces of Fortune500 CEOs with those of US citizens and professors. We find clear confirmation that CEOs do look different when compared to citizens or professors, replicating the finding that faces matter for selection. More importantly, we also find that faces of CEOs of top performing firms do not differ from other CEOs. Based on our advanced face recognition method, our results suggest that facial appearance matters for leader selection but that it does not do so for leader performance.

Why Do Spatial Abilities Predict Mathematical Performance?

ERIC Educational Resources Information Center

Tosto, Maria Grazia; Hanscombe, Ken B.; Haworth, Claire M. A.; Davis, Oliver S. P.; Petrill, Stephen A.; Dale, Philip S.; Malykh, Sergey; Plomin, Robert; Kovas, Yulia

2014-01-01

Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance.…

Learning to predict is spared in mild cognitive impairment due to Alzheimer's disease.

PubMed

Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-10-01

Learning the statistics of the environment is critical for predicting upcoming events. However, little is known about how we translate previous knowledge about scene regularities to sensory predictions. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are known to have spared implicit but impaired explicit recognition memory are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards oriented gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. Further, we show that executive cognitive control may account for individual variability in predictive learning. That is, we observed significant positive correlations of performance in attentional and working memory tasks with post-training performance in the prediction task. Taken together, these results suggest a mediating role of circuits involved in cognitive control (i.e. frontal circuits) that may support the ability for predictive learning in MCI-AD.

Prognostic factors for work ability in women with chronic low back pain consulting primary health care: a 2-year prospective longitudinal cohort study.

PubMed

Nordeman, Lena; Gunnarsson, Ronny; Mannerkorpi, Kaisa

2014-05-01

To investigate prognostic factors for future work ability in women with chronic low back pain (CLBP) consulting primary health care. A 2-year prospective longitudinal cohort study of female patients with CLBP within the primary health care was conducted. Patients were assessed at the first assessment and after 2 years. Prognostic factors for work ability (yes/no) were analyzed by multivariate regression. A total of 130 patients were included at first assessment. After 2 years, 123 patients (95%) were followed up. The 6-minute walk test, depression, and earlier work ability predicted work ability at the 2-year follow-up. A nomogram was constructed to assess the probability of future work ability. The 6-minute walk test, work ability, and depression predicted work ability for women with CLBP after 2 years.

Accurate Descriptions of Hot Flow Behaviors Across β Transus of Ti-6Al-4V Alloy by Intelligence Algorithm GA-SVR

NASA Astrophysics Data System (ADS)

Wang, Li-yong; Li, Le; Zhang, Zhi-hua

2016-09-01

Hot compression tests of Ti-6Al-4V alloy in a wide temperature range of 1023-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-3500 machine. In order to accurately and effectively characterize the highly nonlinear flow behaviors, support vector regression (SVR) which is a machine learning method was combined with genetic algorithm (GA) for characterizing the flow behaviors, namely, the GA-SVR. The prominent character of GA-SVR is that it with identical training parameters will keep training accuracy and prediction accuracy at a stable level in different attempts for a certain dataset. The learning abilities, generalization abilities, and modeling efficiencies of the mathematical regression model, ANN, and GA-SVR for Ti-6Al-4V alloy were detailedly compared. Comparison results show that the learning ability of the GA-SVR is stronger than the mathematical regression model. The generalization abilities and modeling efficiencies of these models were shown as follows in ascending order: the mathematical regression model < ANN < GA-SVR. The stress-strain data outside experimental conditions were predicted by the well-trained GA-SVR, which improved simulation accuracy of the load-stroke curve and can further improve the related research fields where stress-strain data play important roles, such as speculating work hardening and dynamic recovery, characterizing dynamic recrystallization evolution, and improving processing maps.

Stroboscopic Training Enhances Anticipatory Timing.

PubMed

Smith, Trevor Q; Mitroff, Stephen R

The dynamic aspects of sports often place heavy demands on visual processing. As such, an important goal for sports training should be to enhance visual abilities. Recent research has suggested that training in a stroboscopic environment, where visual experiences alternate between visible and obscured, may provide a means of improving attentional and visual abilities. The current study explored whether stroboscopic training could impact anticipatory timing - the ability to predict where a moving stimulus will be at a specific point in time. Anticipatory timing is a critical skill for both sports and non-sports activities, and thus finding training improvements could have broad impacts. Participants completed a pre-training assessment that used a Bassin Anticipation Timer to measure their abilities to accurately predict the timing of a moving visual stimulus. Immediately after this initial assessment, the participants completed training trials, but in one of two conditions. Those in the Control condition proceeded as before with no change. Those in the Strobe condition completed the training trials while wearing specialized eyewear that had lenses that alternated between transparent and opaque (rate of 100ms visible to 150ms opaque). Post-training assessments were administered immediately after training, 10-minutes after training, and 10-days after training. Compared to the Control group, the Strobe group was significantly more accurate immediately after training, was more likely to respond early than to respond late immediately after training and 10 minutes later, and was more consistent in their timing estimates immediately after training and 10 minutes later.

Theory of Mind Development in Adolescence and Early Adulthood: The Growing Complexity of Recursive Thinking Ability

PubMed Central

Valle, Annalisa; Massaro, Davide; Castelli, Ilaria; Marchetti, Antonella

2015-01-01

This study explores the development of theory of mind, operationalized as recursive thinking ability, from adolescence to early adulthood (N = 110; young adolescents = 47; adolescents = 43; young adults = 20). The construct of theory of mind has been operationalized in two different ways: as the ability to recognize the correct mental state of a character, and as the ability to attribute the correct mental state in order to predict the character’s behaviour. The Imposing Memory Task, with five recursive thinking levels, and a third-order false-belief task with three recursive thinking levels (devised for this study) have been used. The relationship among working memory, executive functions, and linguistic skills are also analysed. Results show that subjects exhibit less understanding of elevated recursive thinking levels (third, fourth, and fifth) compared to the first and second levels. Working memory is correlated with total recursive thinking, whereas performance on the linguistic comprehension task is related to third level recursive thinking in both theory of mind tasks. An effect of age on third-order false-belief task performance was also found. A key finding of the present study is that the third-order false-belief task shows significant age differences in the application of recursive thinking that involves the prediction of others’ behaviour. In contrast, such an age effect is not observed in the Imposing Memory Task. These results may support the extension of the investigation of the third order false belief after childhood. PMID:27247645

Investigation into the propagation of Omega very low frequency signals and techniques for improvement of navigation accuracy including differential and composite omega

NASA Technical Reports Server (NTRS)

1973-01-01

An analysis of Very Low Frequency propagation in the atmosphere in the 10-14 kHz range leads to a discussion of some of the more significant causes of phase perturbation. The method of generating sky-wave corrections to predict the Omega phase is discussed. Composite Omega is considered as a means of lane identification and of reducing Omega navigation error. A simple technique for generating trapezoidal model (T-model) phase prediction is presented and compared with the Navy predictions and actual phase measurements. The T-model prediction analysis illustrates the ability to account for the major phase shift created by the diurnal effects on the lower ionosphere. An analysis of the Navy sky-wave correction table is used to provide information about spatial and temporal correlation of phase correction relative to the differential mode of operation.

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

Gene and translation initiation site prediction in metagenomic sequences

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

Hyatt, Philip Douglas; LoCascio, Philip F; Hauser, Loren John

2012-01-01

Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translationmore » initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.« less

Multi-step rhodopsin inactivation schemes can account for the size variability of single photon responses in Limulus ventral photoreceptors

PubMed Central

1994-01-01

Limulus ventral photoreceptors generate highly variable responses to the absorption of single photons. We have obtained data on the size distribution of these responses, derived the distribution predicted from simple transduction cascade models and compared the theory and data. In the simplest of models, the active state of the visual pigment (defined by its ability to activate G protein) is turned off in a single reaction. The output of such a cascade is predicted to be highly variable, largely because of stochastic variation in the number of G proteins activated. The exact distribution predicted is exponential, but we find that an exponential does not adequately account for the data. The data agree much better with the predictions of a cascade model in which the active state of the visual pigment is turned off by a multi-step process. PMID:8057085

Cognition and mortality in older people: the Sydney Memory and Ageing Study.

PubMed

Connors, Michael H; Sachdev, Perminder S; Kochan, Nicole A; Xu, Jing; Draper, Brian; Brodaty, Henry

2015-11-01

Both cognitive ability and cognitive decline have been shown to predict mortality in older people. As dementia, a major form of cognitive decline, has an established association with shorter survival, it is unclear the extent to which cognitive ability and cognitive decline predict mortality in the absence of dementia. To determine whether cognitive ability and decline in cognitive ability predict mortality in older individuals without dementia. The Sydney Memory and Ageing Study is an observational population-based cohort study. Participants completed detailed neuropsychological assessments and medical examinations to assess for risk factors such as depression, obesity, hypertension, diabetes, hypercholesterolaemia, smoking and physical activity. Participants were regularly assessed at 2-year intervals over 8 years. A community sample in Sydney, Australia. One thousand and thirty-seven elderly people without dementia. Overall, 236 (22.8%) participants died within 8 years. Both cognitive ability at baseline and decline in cognitive ability over 2 years predicted mortality. Decline in cognitive ability, but not baseline cognitive ability, was a significant predictor of mortality when depression and other medical risk factors were controlled for. These relationships also held when excluding incident cases of dementia. The findings indicate that decline in cognition is a robust predictor of mortality in older people without dementia at a population level. This relationship is not accounted for by co-morbid depression or other established biomedical risk factors. © The Author 2015. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cognitive ability in young adulthood predicts risk of early-onset dementia in Finnish men.

PubMed

Rantalainen, Ville; Lahti, Jari; Henriksson, Markus; Kajantie, Eero; Eriksson, Johan G; Räikkönen, Katri

2018-06-06

To test if the Finnish Defence Forces Basic Intellectual Ability Test scores at 20.1 years predicted risk of organic dementia or Alzheimer disease (AD). Dementia was defined as inpatient or outpatient diagnosis of organic dementia or AD risk derived from Hospital Discharge or Causes of Death Registers in 2,785 men from the Helsinki Birth Cohort Study, divided based on age at first diagnosis into early onset (<65 years) or late onset (≥65 years). The Finnish Defence Forces Basic Intellectual Ability Test comprises verbal, arithmetic, and visuospatial subtests and a total score (scores transformed into a mean of 100 and SD of 15). We used Cox proportional hazard models and adjusted for age at testing, childhood socioeconomic status, mother's age at delivery, parity, participant's birthweight, education, and stroke or coronary heart disease diagnosis. Lower cognitive ability total and verbal ability (hazard ratio [HR] per 1 SD disadvantage >1.69, 95% confidence interval [CI] 1.01-2.63) scores predicted higher early-onset any dementia risk across the statistical models; arithmetic and visuospatial ability scores were similarly associated with early-onset any dementia risk, but these associations weakened after covariate adjustments (HR per 1 SD disadvantage >1.57, 95% CI 0.96-2.57). All associations were rendered nonsignificant when we adjusted for participant's education. Cognitive ability did not predict late-onset dementia risk. These findings reinforce previous suggestions that lower cognitive ability in early life is a risk factor for early-onset dementia. © 2018 American Academy of Neurology.

An assessment of the ability of routine restaurant inspections to predict food-borne outbreaks in Miami-Dade County, Florida.

PubMed Central

Cruz, M A; Katz, D J; Suarez, J A

2001-01-01

OBJECTIVES: This study sought to determine the usefulness of restaurant inspections in predicting food-borne outbreaks in Miami-Dade County, Fla. METHODS: Inspection reports of restaurants with outbreaks in 1995 (cases; n = 51) were compared with those of randomly selected restaurants that had no reported outbreaks (controls; n = 76). RESULTS: Cases and controls did not differ by overall inspection outcome or mean number of critical violations. Only 1 critical violation--evidence of vermin--was associated with outbreaks (odds ratio = 3.3; 95% confidence interval = 1.1, 13.1). CONCLUSIONS: Results of restaurant inspections in Miami-Dade County did not predict outbreaks. If these findings are representative of the situation in other jurisdictions, inspection practices may need to be updated. PMID:11344897

Validation of engineering methods for predicting hypersonic vehicle controls forces and moments

NASA Technical Reports Server (NTRS)

Maughmer, M.; Straussfogel, D.; Long, L.; Ozoroski, L.

1991-01-01

This work examines the ability of the aerodynamic analysis methods contained in an industry standard conceptual design code, the Aerodynamic Preliminary Analysis System (APAS II), to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds. Predicted control forces and moments generated by various control effectors are compared with previously published wind-tunnel and flight-test data for three vehicles: the North American X-15, a hypersonic research airplane concept, and the Space Shuttle Orbiter. Qualitative summaries of the results are given for each force and moment coefficient and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage.

Variable-order fractional MSD function to describe the evolution of protein lateral diffusion ability in cell membranes

NASA Astrophysics Data System (ADS)

Yin, Deshun; Qu, Pengfei

2018-02-01

Protein lateral diffusion is considered anomalous in the plasma membrane. And this diffusion is related to membrane microstructure. In order to better describe the property of protein lateral diffusion and find out the inner relationship between protein lateral diffusion and membrane microstructure, this article applies variable-order fractional mean square displacement (f-MSD) function for characterizing the anomalous diffusion. It is found that the variable order can reflect the evolution of diffusion ability. The results of numerical simulation demonstrate variable-order f-MSD function can predict the tendency of anomalous diffusion during the process of confined diffusion. It is also noted that protein lateral diffusion ability during the processes of confined and hop diffusion can be split into three parts. In addition, the comparative analyses reveal that the variable order is related to the confinement-domain size and microstructure of compartment boundary too.

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis

PubMed Central

Forss, Sofia I. F.; Willems, Erik; Call, Josep; van Schaik, Carel P.

2016-01-01

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning. PMID:27466052

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis.

PubMed

Forss, Sofia I F; Willems, Erik; Call, Josep; van Schaik, Carel P

2016-07-28

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning.

Writing abilities longitudinally predict academic outcomes of adolescents with ADHD.

PubMed

Molitor, Stephen J; Langberg, Joshua M; Bourchtein, Elizaveta; Eddy, Laura D; Dvorsky, Melissa R; Evans, Steven W

2016-09-01

Students with attention-deficit/hyperactivity disorder (ADHD) often experience a host of negative academic outcomes, and deficits in reading and mathematics abilities contribute to these academic impairments. Students with ADHD may also have difficulties with written expression, but there has been minimal research in this area and it is not clear whether written expression abilities uniquely contribute to the academic functioning of students with ADHD. The current study included a sample of 104 middle school students diagnosed with ADHD (Grades 6-8). Participants were followed longitudinally to evaluate whether written expression abilities at baseline predicted student grade point average (GPA) and parent ratings of academic impairment 18 months later, after controlling for reading ability and additional relevant covariates. Written expression abilities longitudinally predicted both academic outcomes above and beyond ADHD and oppositional defiant disorder symptoms, medication use, reading ability, and baseline values of GPA and parent-rated academic impairment. Follow-up analyses revealed that no single aspect of written expression was demonstrably more impactful on academic outcomes than the others, suggesting that writing as an entire process should be the focus of intervention. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types

PubMed Central

Austin, Peter C.; Tu, Jack V.; Ho, Jennifer E.; Levy, Daniel; Lee, Douglas S.

2014-01-01

Objective Physicians classify patients into those with or without a specific disease. Furthermore, there is often interest in classifying patients according to disease etiology or subtype. Classification trees are frequently used to classify patients according to the presence or absence of a disease. However, classification trees can suffer from limited accuracy. In the data-mining and machine learning literature, alternate classification schemes have been developed. These include bootstrap aggregation (bagging), boosting, random forests, and support vector machines. Study design and Setting We compared the performance of these classification methods with those of conventional classification trees to classify patients with heart failure according to the following sub-types: heart failure with preserved ejection fraction (HFPEF) vs. heart failure with reduced ejection fraction (HFREF). We also compared the ability of these methods to predict the probability of the presence of HFPEF with that of conventional logistic regression. Results We found that modern, flexible tree-based methods from the data mining literature offer substantial improvement in prediction and classification of heart failure sub-type compared to conventional classification and regression trees. However, conventional logistic regression had superior performance for predicting the probability of the presence of HFPEF compared to the methods proposed in the data mining literature. Conclusion The use of tree-based methods offers superior performance over conventional classification and regression trees for predicting and classifying heart failure subtypes in a population-based sample of patients from Ontario. However, these methods do not offer substantial improvements over logistic regression for predicting the presence of HFPEF. PMID:23384592

Comparison of the predictive performance of the BIG, TRISS, and PS09 score in an adult trauma population derived from multiple international trauma registries

PubMed Central

2013-01-01

Background The BIG score (Admission base deficit (B), International normalized ratio (I), and Glasgow Coma Scale (G)) has been shown to predict mortality on admission in pediatric trauma patients. The objective of this study was to assess its performance in predicting mortality in an adult trauma population, and to compare it with the existing Trauma and Injury Severity Score (TRISS) and probability of survival (PS09) score. Materials and methods A retrospective analysis using data collected between 2005 and 2010 from seven trauma centers and registries in Europe and the United States of America was performed. We compared the BIG score with TRISS and PS09 scores in a population of blunt and penetrating trauma patients. We then assessed the discrimination ability of all scores via receiver operating characteristic (ROC) curves and compared the expected mortality rate (precision) of all scores with the observed mortality rate. Results In total, 12,206 datasets were retrieved to validate the BIG score. The mean ISS was 15 ± 11, and the mean 30-day mortality rate was 4.8%. With an AUROC of 0.892 (95% confidence interval (CI): 0.879 to 0.906), the BIG score performed well in an adult population. TRISS had an area under ROC (AUROC) of 0.922 (0.913 to 0.932) and the PS09 score of 0.825 (0.915 to 0.934). On a penetrating-trauma population, the BIG score had an AUROC result of 0.920 (0.898 to 0.942) compared with the PS09 score (AUROC of 0.921; 0.902 to 0.939) and TRISS (0.929; 0.912 to 0.947). Conclusions The BIG score is a good predictor of mortality in the adult trauma population. It performed well compared with TRISS and the PS09 score, although it has significantly less discriminative ability. In a penetrating-trauma population, the BIG score performed better than in a population with blunt trauma. The BIG score has the advantage of being available shortly after admission and may be used to predict clinical prognosis or as a research tool to risk stratify trauma patients into clinical trials. PMID:23844754

Do different types of school mathematics development depend on different constellations of numerical versus general cognitive abilities?

PubMed

Fuchs, Lynn S; Geary, David C; Compton, Donald L; Fuchs, Douglas; Hamlett, Carol L; Seethaler, Pamela M; Bryant, Joan D; Schatschneider, Christopher

2010-11-01

The purpose of this study was to examine the interplay between basic numerical cognition and domain-general abilities (such as working memory) in explaining school mathematics learning. First graders (N = 280; mean age = 5.77 years) were assessed on 2 types of basic numerical cognition, 8 domain-general abilities, procedural calculations, and word problems in fall and then reassessed on procedural calculations and word problems in spring. Development was indexed by latent change scores, and the interplay between numerical and domain-general abilities was analyzed by multiple regression. Results suggest that the development of different types of formal school mathematics depends on different constellations of numerical versus general cognitive abilities. When controlling for 8 domain-general abilities, both aspects of basic numerical cognition were uniquely predictive of procedural calculations and word problems development. Yet, for procedural calculations development, the additional amount of variance explained by the set of domain-general abilities was not significant, and only counting span was uniquely predictive. By contrast, for word problems development, the set of domain-general abilities did provide additional explanatory value, accounting for about the same amount of variance as the basic numerical cognition variables. Language, attentive behavior, nonverbal problem solving, and listening span were uniquely predictive.

Do Different Types of School Mathematics Development Depend on Different Constellations of Numerical versus General Cognitive Abilities?

PubMed Central

Fuchs, Lynn S.; Geary, David C.; Compton, Donald L.; Fuchs, Douglas; Hamlett, Carol L.; Seethaler, Pamela M.; Bryant, Joan D.; Schatschneider, Christopher

2010-01-01

The purpose of this study was to examine the interplay between basic numerical cognition and domain-general abilities (such as working memory) in explaining school mathematics learning. First graders (n=280; 5.77 years) were assessed on 2 types of basic numerical cognition, 8 domain-general abilities, procedural calculations (PCs), and word problems (WPs) in fall and then reassessed on PCs and WPs in spring. Development was indexed via latent change scores, and the interplay between numerical and domain-general abilities was analyzed via multiple regression. Results suggest that the development of different types of formal school mathematics depends on different constellations of numerical versus general cognitive abilities. When controlling for 8 domain-general abilities, both aspects of basic numerical cognition were uniquely predictive of PC and WP development. Yet, for PC development, the additional amount of variance explained by the set of domain-general abilities was not significant, and only counting span was uniquely predictive. By contrast, for WP development, the set of domain- general abilities did provide additional explanatory value, accounting for about the same amount of variance as the basic numerical cognition variables. Language, attentive behavior, nonverbal problem solving, and listening span were uniquely predictive. PMID:20822213

Math anxiety, self-efficacy, and ability in British undergraduate nursing students.

PubMed

McMullan, Miriam; Jones, Ray; Lea, Susan

2012-04-01

Nurses need to be able to make drug calculations competently. In this study, involving 229 second year British nursing students, we explored the influence of mathematics anxiety, self-efficacy, and numerical ability on drug calculation ability and determined which factors would best predict this skill. Strong significant relationships (p < .001) existed between anxiety, self-efficacy, and ability. Students who failed the numerical and/or drug calculation ability tests were more anxious (p < .001) and less confident (p ≤ .002) in performing calculations than those who passed. Numerical ability made the strongest unique contribution in predicting drug calculation ability (beta = 0.50, p < .001) followed by drug calculation self-efficacy (beta = 0.16, p = .04). Early testing is recommended for basic numerical skills. Faculty are advised to refresh students' numerical skills before introducing drug calculations. Copyright © 2012 Wiley Periodicals, Inc.

Growth trajectories and intellectual abilities in young adulthood: The Helsinki Birth Cohort study.

PubMed

Räikkönen, Katri; Forsén, Tom; Henriksson, Markus; Kajantie, Eero; Heinonen, Kati; Pesonen, Anu-Katriina; Leskinen, Jukka T; Laaksonen, Ilmo; Osmond, Clive; Barker, David J P; Eriksson, Johan G

2009-08-15

Slow childhood growth is associated with poorer intellectual ability. The critical periods of growth remain uncertain. Among 2,786 Finnish male military conscripts (1952-1972) born in 1934-1944, the authors tested how specific growth periods from birth to age 20 years predicted verbal, visuospatial, and arithmetic abilities at age 20. Small head circumference at birth predicted poorer verbal, visuospatial, and arithmetic abilities. The latter 2 measures were also associated with lower weight and body mass index (weight (kg)/height (m)(2)) at birth (for a 1-standard-deviation (SD) decrease in test score per SD decrease in body size > or = 0.05, P's < 0.04). Slow linear growth and weight gain between birth and age 6 months, between ages 6 months and 2 years, or both predicted poorer performance on all 3 tests (for a 1-SD decrease in test score per SD decrease in growth > or = 0.05, P's < 0.03). Reduced linear growth between ages 2 and 7 years predicted worse verbal ability, and between age 11 years and conscription it predicted worse performance on all 3 tests. Prenatal brain growth and linear growth up to 2 years after birth form a first critical period for intellectual development. There is a second critical period, specific for verbal development, between ages 2 and 7 years and a third critical period for all 3 tested outcomes during adolescence.

Implicit beliefs of ability, approach-avoidance goals and cognitive anxiety among team sport athletes.

PubMed

Stenling, Andreas; Hassmén, Peter; Holmström, Stefan

2014-01-01

People's implicit beliefs of ability have been suggested as an antecedent of achievement goal adoption, which has in turn been associated with behavioural, cognitive and affective outcomes. This study examined a conditional process model with team sport athletes' approach-avoidance achievement goals as mediators between their implicit beliefs of sport ability and sport-related cognitive anxiety. We expected gender to moderate the paths from implicit beliefs of ability to approach-avoidance goals and from approach-avoidance goals to cognitive anxiety. Team sport athletes with a mean age of 20 years (163 females and 152 males) responded to questionnaires about their implicit beliefs of sport ability, approach-avoidance goals and sport-related cognitive anxiety. Incremental beliefs, gender and the interaction between them predicted mastery-approach goals. Gender also predicted mastery-avoidance goals, with females reporting higher levels than males. Mastery-avoidance goals, gender and the interaction between them predicted cognitive anxiety, with females reporting higher levels of anxiety than males. Entity beliefs positively predicted performance-avoidance goals and the interaction between performance-approach and gender predicted anxiety. The indirect effects also showed gender differences in relation to performance-approach goals. Taken together, our results suggest that coaches trying to create a facilitating climate for their male and female athletes may be wise to consider their athletes' anxiety and achievement goal patterns as these may affect both the athletes' well-being and performance.

Mathematical (Dis)abilities Within the Opportunity-Propensity Model: The Choice of Math Test Matters

PubMed Central

Baten, Elke; Desoete, Annemie

2018-01-01

This study examined individual differences in mathematics learning by combining antecedent (A), opportunity (O), and propensity (P) indicators within the Opportunity-Propensity Model. Although there is already some evidence for this model based on secondary datasets, there currently is no primary data available that simultaneously takes into account A, O, and P factors in children with and without Mathematical Learning Disabilities (MLD). Therefore, the mathematical abilities of 114 school-aged children (grade 3 till 6) with and without MLD were analyzed and combined with information retrieved from standardized tests and questionnaires. Results indicated significant differences in personality, motivation, temperament, subjective well-being, self-esteem, self-perceived competence, and parental aspirations when comparing children with and without MLD. In addition, A, O, and P factors were found to underlie mathematical abilities and disabilities. For the A factors, parental aspirations explained about half of the variance in fact retrieval speed in children without MLD, and SES was especially involved in the prediction of procedural accuracy in general. Teachers’ experience contributed as O factor and explained about 6% of the variance in mathematical abilities. P indicators explained between 52 and 69% of the variance, with especially intelligence as overall significant predictor. Indirect effects pointed towards the interrelatedness of the predictors and the value of including A, O, and P indicators in a comprehensive model. The role parental aspirations played in fact retrieval speed was partially mediated through the self-perceived competence of the children, whereas the effect of SES on procedural accuracy was partially mediated through intelligence in children of both groups and through working memory capacity in children with MLD. Moreover, in line with the componential structure of mathematics, our findings were dependent on the math task used. Different A, O, and P indicators seemed to be important for fact retrieval speed compared to procedural accuracy. Also, mathematical development type (MLD or typical development) mattered since some A, O, and P factors were predictive for MLD only and the other way around. Practical implications of these findings and recommendations for future research on MLD and on individual differences in mathematical abilities are provided. PMID:29867645

Mathematical (Dis)abilities Within the Opportunity-Propensity Model: The Choice of Math Test Matters.

PubMed

Baten, Elke; Desoete, Annemie

2018-01-01

This study examined individual differences in mathematics learning by combining antecedent (A), opportunity (O), and propensity (P) indicators within the Opportunity-Propensity Model. Although there is already some evidence for this model based on secondary datasets, there currently is no primary data available that simultaneously takes into account A, O, and P factors in children with and without Mathematical Learning Disabilities (MLD). Therefore, the mathematical abilities of 114 school-aged children (grade 3 till 6) with and without MLD were analyzed and combined with information retrieved from standardized tests and questionnaires. Results indicated significant differences in personality, motivation, temperament, subjective well-being, self-esteem, self-perceived competence, and parental aspirations when comparing children with and without MLD. In addition, A, O, and P factors were found to underlie mathematical abilities and disabilities. For the A factors, parental aspirations explained about half of the variance in fact retrieval speed in children without MLD, and SES was especially involved in the prediction of procedural accuracy in general. Teachers' experience contributed as O factor and explained about 6% of the variance in mathematical abilities. P indicators explained between 52 and 69% of the variance, with especially intelligence as overall significant predictor. Indirect effects pointed towards the interrelatedness of the predictors and the value of including A, O, and P indicators in a comprehensive model. The role parental aspirations played in fact retrieval speed was partially mediated through the self-perceived competence of the children, whereas the effect of SES on procedural accuracy was partially mediated through intelligence in children of both groups and through working memory capacity in children with MLD. Moreover, in line with the componential structure of mathematics, our findings were dependent on the math task used. Different A, O, and P indicators seemed to be important for fact retrieval speed compared to procedural accuracy. Also, mathematical development type (MLD or typical development) mattered since some A, O, and P factors were predictive for MLD only and the other way around. Practical implications of these findings and recommendations for future research on MLD and on individual differences in mathematical abilities are provided.

Rhythm and Melody Tasks for School-Aged Children With and Without Musical Training: Age-Equivalent Scores and Reliability.

PubMed

Ireland, Kierla; Parker, Averil; Foster, Nicholas; Penhune, Virginia

2018-01-01

Measuring musical abilities in childhood can be challenging. When music training and maturation occur simultaneously, it is difficult to separate the effects of specific experience from age-based changes in cognitive and motor abilities. The goal of this study was to develop age-equivalent scores for two measures of musical ability that could be reliably used with school-aged children (7-13) with and without musical training. The children's Rhythm Synchronization Task (c-RST) and the children's Melody Discrimination Task (c-MDT) were adapted from adult tasks developed and used in our laboratories. The c-RST is a motor task in which children listen and then try to synchronize their taps with the notes of a woodblock rhythm while it plays twice in a row. The c-MDT is a perceptual task in which the child listens to two melodies and decides if the second was the same or different. We administered these tasks to 213 children in music camps (musicians, n = 130) and science camps (non-musicians, n = 83). We also measured children's paced tapping, non-paced tapping, and phonemic discrimination as baseline motor and auditory abilities We estimated internal-consistency reliability for both tasks, and compared children's performance to results from studies with adults. As expected, musically trained children outperformed those without music lessons, scores decreased as difficulty increased, and older children performed the best. Using non-musicians as a reference group, we generated a set of age-based z-scores, and used them to predict task performance with additional years of training. Years of lessons significantly predicted performance on both tasks, over and above the effect of age. We also assessed the relation between musician's scores on music tasks, baseline tasks, auditory working memory, and non-verbal reasoning. Unexpectedly, musician children outperformed non-musicians in two of three baseline tasks. The c-RST and c-MDT fill an important need for researchers interested in evaluating the impact of musical training in longitudinal studies, those interested in comparing the efficacy of different training methods, and for those assessing the impact of training on non-musical cognitive abilities such as language processing.