Theories of Willpower Affect Sustained Learning

PubMed Central

Miller, Eric M.; Walton, Gregory M.; Dweck, Carol S.; Job, Veronika; Trzesniewski, Kali H.; McClure, Samuel M.

2012-01-01

Building cognitive abilities often requires sustained engagement with effortful tasks. We demonstrate that beliefs about willpower–whether willpower is viewed as a limited or non-limited resource–impact sustained learning on a strenuous mental task. As predicted, beliefs about willpower did not affect accuracy or improvement during the initial phases of learning; however, participants who were led to view willpower as non-limited showed greater sustained learning over the full duration of the task. These findings highlight the interactive nature of motivational and cognitive processes: motivational factors can substantially affect people’s ability to recruit their cognitive resources to sustain learning over time. PMID:22745675

On the predictive ability of mechanistic models for the Haitian cholera epidemic.

PubMed

Mari, Lorenzo; Bertuzzo, Enrico; Finger, Flavio; Casagrandi, Renato; Gatto, Marino; Rinaldo, Andrea

2015-03-06

Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. We address the above issue in a formal model comparison framework and provide a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels and coupling mechanisms. Reference is made to records of the recent Haiti cholera epidemics. Our intensive computations and objective model comparisons show that spatially explicit models accounting for spatial connections have better explanatory power than spatially disconnected ones for short-to-intermediate calibration windows, while parsimonious, spatially disconnected models perform better with long training sets. On average, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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.

Midlife work ability and mobility limitation in old age among non-disability and disability retirees--a prospective study.

PubMed

von Bonsdorff, Monika E; Rantanen, Taina; Törmäkangas, Timo; Kulmala, Jenni; Hinrichs, Timo; Seitsamo, Jorma; Nygård, Clas-Håkan; Ilmarinen, Juhani; von Bonsdorff, Mikaela B

2016-02-16

Little is known about the wellbeing and mobility limitation of older disability retirees. Personal and environmental factors, such as time spent in working life, may either exacerbate or mitigate the onset of mobility limitation in general population. We aimed to study perceived midlife work ability as a determinant of self-reported mobility limitation in old age among municipal employees who transitioned into non-disability and disability retirement. 4329 participants of the Finnish Longitudinal Study of Municipal Employees (FLAME) had retired during January 1985 and July 2000. They had data on retirement, perceived work ability in 1985, and self-reported mobility limitation (non-disability retirement n = 2870, men 39%; and diagnose-specific disability retirement n = 1459, men 48%). Self-reported mobility was measured in 1985, 1992, 1997 and 2009. The latest score available was used to assess the number of mobility limitation. Work ability was measured by asking the respondents to evaluate their current work ability against their lifetime best in 1985. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for work ability predicting mobility limitation in non-disability and diagnose-specific disability retirement groups were calculated using Poisson regression models. The prevalence of mobility limitation for those who transitioned into non-disability retirement (Incidence Rate, IR = 0.45, 95% CI = 0.44-0.46) was lower compared to those who retired due to disability (IR = 0.65, CI = 0.63-0.66). A one-point increase in the work ability score decreased the risk for having one more mobility limitation among non-disability and all diagnose-specific retirement groups (musculoskeletal disease, cardiovascular disease, mental disorder, and other diseases). Better midlife work ability may protect from old age mobility limitation among those who retire due to non-disability and disability. Promoting work ability in midlife may lead to more independent, active aging, regardless of type of retirement.

The injury severity score or the new injury severity score for predicting mortality, intensive care unit admission and length of hospital stay: experience from a university hospital in a developing country.

PubMed

Tamim, Hala; Al Hazzouri, Adina Zeki; Mahfoud, Ziad; Atoui, Maria; El-Chemaly, Souheil

2008-01-01

Limited research has been performed to compare the predictive abilities of the injury severity score (ISS) and the new ISS (NISS) in the developing world. From January 2001 until January 2003 all trauma patients admitted to the American University of Beirut Medical Centre were enrolled. The statistical performance of the ISS/NISS in predicting mortality, admission to the intensive care unit (ICU) and length of hospital stay (LOS dichotomised as <10 or > or =10 days) was evaluated using receiver operating characteristic and the Hosmer-Lemeshow calibration statistic. A total of 891 consecutive patients were enrolled. The ISS and NISS were equivalent in predicting survival, and both performed better in patients younger than 65 years of age. However, the ISS predicted ICU admission and LOS better than the NISS. However, these predictive abilities were lower for the geriatric trauma patients aged 65 years and above compared to the other age groups. There are conflicting results in the literature about the abilities of ISS and NISS to predict mortality. However, this is the first study to report that ISS has a superior ability in predicting both LOS and ICU admission. The scoring of trauma severity may need to be individualised to different countries and trauma systems.

The social perception of emotional abilities: expanding what we know about observer ratings of emotional intelligence.

PubMed

Elfenbein, Hillary Anger; Barsade, Sigal G; Eisenkraft, Noah

2015-02-01

We examine the social perception of emotional intelligence (EI) through the use of observer ratings. Individuals frequently judge others' emotional abilities in real-world settings, yet we know little about the properties of such ratings. This article examines the social perception of EI and expands the evidence to evaluate its reliability and cross-judge agreement, as well as its convergent, divergent, and predictive validity. Three studies use real-world colleagues as observers and data from 2,521 participants. Results indicate significant consensus across observers about targets' EI, moderate but significant self-observer agreement, and modest but relatively consistent discriminant validity across the components of EI. Observer ratings significantly predicted interdependent task performance, even after controlling for numerous factors. Notably, predictive validity was greater for observer-rated than for self-rated or ability-tested EI. We discuss the minimal associations of observer ratings with ability-tested EI, study limitations, future directions, and practical implications. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Current gaps in understanding and predicting space weather: An operations perspective

NASA Astrophysics Data System (ADS)

Murtagh, W. J.

2016-12-01

The NOAA Space Weather Prediction Center (SWPC), one of the nine National Weather Service (NWS) National Centers for Environmental Prediction, is the Nation's official source for space weather alerts and warnings. Space weather effects the technology that forms the backbone of global economic vitality and national security, including satellite and airline operations, communications networks, and the electric power grid. Many of SWPC's over 48,000 subscribers rely on space weather forecasts for critical decision making. But extraordinary gaps still exist in our ability to meet customer needs for accurate and timely space weather forecasts and warnings. The 2015 National Space Weather Strategy recognizes that it is imperative that we improve the fundamental understanding of space weather and increase the accuracy, reliability, and timeliness of space-weather observations and forecasts in support of the growing demands. In this talk we provide a broad perspective of the key challenges that currently limit the forecaster's ability to better understand and predict space weather. We also examine the impact of these limitations on the end-user community.

Modelling complex phenomena in optical fibres

NASA Astrophysics Data System (ADS)

Allington-Smith, Jeremy; Murray, Graham; Lemke, Ulrike

2012-09-01

We present a new model for predicting the performance of fibre systems in the multimode limit. This is based on ray-­-tracing but includes a semi-­-empirical description of Focal Ratio Degradation (FRD). We show how FRD is simulated by the model. With this ability, it can be used to investigate a wide variety of phenomena including scrambling and the loss of light close to the limiting numerical aperture. It can also be used to predict the performance of non-­-round and asymmetric fibres.

Emotional intelligence predicts success in medical school.

PubMed

Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

2014-02-01

Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems. PsycINFO Database Record (c) 2014 APA, all rights reserved.

The predictive ability of the STarT Back Tool was limited in people with chronic low back pain: a prospective cohort study.

PubMed

Kendell, Michelle; Beales, Darren; O'Sullivan, Peter; Rabey, Martin; Hill, Jonathan; Smith, Anne

2018-04-01

In people with chronic non-specific low back pain (LBP), what is the predictive and discriminative validity of the STarT Back Tool (SBT) for pain intensity, self-reported LBP-related disability, and global self-perceived change at 1-year follow-up? What is the profile of the SBT risk subgroups with respect to demographic variables, pain intensity, self-reported LBP-related disability, and psychological measures? Prospective cohort study. A total of 290 adults with dominant axial LBP of≥3months' duration recruited from the general community, and private physiotherapy, psychology, and pain-management clinics in Western Australia. The 1-year follow-up measures were pain intensity, LBP-related disability, and global self-perceived change. Outcomes were collected on 264 participants. The SBT categorised 82 participants (28%) as low risk, 116 (40%) as medium risk, and 92 (32%) as high risk. The risk subgroups differed significantly (p<0.05) on baseline pain, disability, and psychological scores. The SBT's predictive ability was strongest for disability: RR was 2.30 (95% CI 1.28 to 4.10) in the medium-risk group and 2.86 (95% CI 1.60 to 5.11) in the high-risk group. The SBT's predictive ability was weaker for pain: RR was 1.25 (95% CI 1.04 to 1.51) in the medium-risk group and 1.26 (95% CI 1.03 to 1.52) in the high-risk group. For the SBT total score, the AUC was 0.71 (95% CI 0.64 to 0.77) for disability and 0.63 (95% CI 0.55 to 0.71) for pain. This was the first large study to investigate the SBT in a population exclusively with chronic LBP. The SBT provided an acceptable indication of 1-year disability, had poor predictive and discriminative ability for future pain, and was unable to predict or discriminate global perceived change. In this cohort with chronic non-specific LBP, the SBT's predictive and discriminative abilities were restricted to disability at 1year. [Kendell M, Beales D, O'Sullivan P, Rabey M, Hill J, Smith A (2018) The predictive ability of the STarT Back Tool was limited in people with chronic low back pain: a prospective cohort study. Journal of Physiotherapy 64: 107-113]. Copyright © 2018 Australian Physiotherapy Association. Published by Elsevier B.V. All rights reserved.

Investigating Predictors of Spelling Ability for Adults with Low Literacy Skills

PubMed Central

Talwar, Amani; Cote, Nicole Gilbert; Binder, Katherine S.

2014-01-01

This study examined whether the spelling abilities of adults with low literacy skills could be predicted by their phonological, orthographic, and morphological awareness. Sixty Adult Basic Education (ABE) students completed several literacy tasks. It was predicted that scores on phonological and orthographic tasks would explain variance in spelling scores, whereas scores on morphological tasks may not. Scores on all phonological tasks and on one orthographic task emerged as significant predictors of spelling scores. Additionally, error analyses revealed a limited influence of morphological knowledge in spelling attempts. Implications for ABE instruction are discussed. PMID:25364644

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.

Integrating Self-Determination and Job Demands-Resources Theory in Predicting Mental Health Provider Burnout.

PubMed

Dreison, Kimberly C; White, Dominique A; Bauer, Sarah M; Salyers, Michelle P; McGuire, Alan B

2018-01-01

Limited progress has been made in reducing burnout in mental health professionals. Accordingly, we identified factors that might protect against burnout and could be productive focal areas for future interventions. Guided by self-determination theory, we examined whether supervisor autonomy support, self-efficacy, and staff cohesion predict provider burnout. 358 staff from 13 agencies completed surveys. Higher levels of supervisor autonomy support, self-efficacy, and staff cohesion were predictive of lower burnout, even after accounting for job demands. Although administrators may be limited in their ability to reduce job demands, our findings suggest that increasing core job resources may be a viable alternative.

Preexposure to Objects That Contrast in Familiarity Improves Young Children's Lexical Knowledge Judgment

ERIC Educational Resources Information Center

Hartin, Travis L.; Stevenson, Colleen M.; Merriman, William E.

2016-01-01

The ability to judge the limits of one's own knowledge may play an important role in knowledge acquisition. The current study tested the prediction that preschoolers would judge the limits of their lexical knowledge more accurately if they were first exposed to a few objects of contrasting familiarity. Such preexposure was hypothesized to increase…

Simulated effect of pneumococcal vaccination in the Netherlands on existing rules constructed in a non-vaccinated cohort predicting sequelae after bacterial meningitis

PubMed Central

2010-01-01

Background Previously two prediction rules identifying children at risk of hearing loss and academic or behavioral limitations after bacterial meningitis were developed. Streptococcus pneumoniae as causative pathogen was an important risk factor in both. Since 2006 Dutch children receive seven-valent conjugate vaccination against S. pneumoniae. The presumed effect of vaccination was simulated by excluding all children infected by S. pneumoniae with the serotypes included in the vaccine, from both previous collected cohorts (between 1990-1995). Methods Children infected by one of the vaccine serotypes were excluded from both original cohorts (hearing loss: 70 of 628 children; academic or behavioral limitations: 26 of 182 children). All identified risk factors were included in multivariate logistic regression models. The discriminative ability of both new models was calculated. Results The same risk factors as in the original models were significant. The discriminative ability of the original hearing loss model was 0.84 and of the new model 0.87. In the academic or behavioral limitations model it was 0.83 and 0.84 respectively. Conclusion It can be assumed that the prediction rules will also be applicable on a vaccinated population. However, vaccination does not provide 100% coverage and evidence is available that serotype replacement will occur. The impact of vaccination on serotype replacement needs to be investigated, and the prediction rules must be validated externally. PMID:20815866

Investigating the running abilities of Tyrannosaurus rex using stress-constrained multibody dynamic analysis.

PubMed

Sellers, William I; Pond, Stuart B; Brassey, Charlotte A; Manning, Philip L; Bates, Karl T

2017-01-01

The running ability of Tyrannosaurus rex has been intensively studied due to its relevance to interpretations of feeding behaviour and the biomechanics of scaling in giant predatory dinosaurs. Different studies using differing methodologies have produced a very wide range of top speed estimates and there is therefore a need to develop techniques that can improve these predictions. Here we present a new approach that combines two separate biomechanical techniques (multibody dynamic analysis and skeletal stress analysis) to demonstrate that true running gaits would probably lead to unacceptably high skeletal loads in T. rex . Combining these two approaches reduces the high-level of uncertainty in previous predictions associated with unknown soft tissue parameters in dinosaurs, and demonstrates that the relatively long limb segments of T. rex -long argued to indicate competent running ability-would actually have mechanically limited this species to walking gaits. Being limited to walking speeds contradicts arguments of high-speed pursuit predation for the largest bipedal dinosaurs like T. rex , and demonstrates the power of multiphysics approaches for locomotor reconstructions of extinct animals.

Motor ability and inhibitory processes in children with ADHD: a neuroelectric study.

PubMed

Hung, Chiao-Ling; Chang, Yu-Kai; Chan, Yuan-Shuo; Shih, Chia-Hao; Huang, Chung-Ju; Hung, Tsung-Min

2013-06-01

The purpose of the current study was to examine the relationship between motor ability and response inhibition using behavioral and electrophysiological indices in children with ADHD. A total of 32 participants were recruited and underwent a motor ability assessment by administering the Basic Motor Ability Test-Revised (BMAT) as well as the Go/No-Go task and event-related potential (ERP) measurements at the same time. The results indicated that the BMAT scores were positively associated with the behavioral and ERP measures. Specifically, the BMAT average score was associated with a faster reaction time and higher accuracy, whereas higher BMAT subset scores predicted a shorter P3 latency in the Go condition. Although the association between the BMAT average score and the No-Go accuracy was limited, higher BMAT average and subset scores predicted a shorter N2 and P3 latency and a larger P3 amplitude in the No-Go condition. These findings suggest that motor abilities may play roles that benefit the cognitive performance of ADHD children.

Locomotor Tests Predict Community Mobility in Children and Youth with Cerebral Palsy

ERIC Educational Resources Information Center

Ferland, Chantale; Moffet, Helene; Maltais, Desiree

2012-01-01

Ambulatory children and youth with cerebral palsy have limitations in locomotor capacities and in community mobility. The ability of three locomotor tests to predict community mobility in this population (N = 49, 27 boys, 6-16 years old) was examined. The tests were a level ground walking test, the 6-min-Walk-Test (6MWT), and two tests of advanced…

Efficacy of functional movement screening for predicting injuries in coast guard cadets.

PubMed

Knapik, Joseph J; Cosio-Lima, Ludimila M; Reynolds, Katy L; Shumway, Richard S

2015-05-01

Functional movement screening (FMS) examines the ability of individuals to perform highly specific movements with the aim of identifying individuals who have functional limitations or asymmetries. It is assumed that individuals who can more effectively accomplish the required movements have a lower injury risk. This study determined the ability of FMS to predict injuries in the United States Coast Guard (USCG) cadets. Seven hundred seventy male and 275 female USCG freshman cadets were administered the 7 FMS tests before the physically intense 8-week Summer Warfare Annual Basic (SWAB) training. Physical training-related injuries were recorded during SWAB training. Cumulative injury incidence was calculated at various FMS cutpoint scores. The ability of the FMS total score to predict injuries was examined by calculating sensitivity and specificity. Determination of the FMS cutpoint that maximized specificity and sensitivity was determined from the Youden's index (sensitivity + specificity - 1). For men, FMS scores ≤ 12 were associated with higher injury risk than scores >12; for women, FMS scores ≤ 15 were associated with higher injury risk than scores >15. The Youden's Index indicated that the optimal FMS cutpoint was ≤ 11 for men (22% sensitivity, 87% specificity) and ≤ 14 for women (60% sensitivity, 61% specificity). Functional movement screening demonstrated moderate prognostic accuracy for determining injury risk among female Coast Guard cadets but relatively low accuracy among male cadets. Attempting to predict injury risk based on the FMS test seems to have some limited promise based on the present and past investigations.

Physical fitness is predictive for a decline in the ability to perform instrumental activities of daily living in older adults with intellectual disabilities: Results of the HA-ID study.

PubMed

Oppewal, Alyt; Hilgenkamp, Thessa I M; van Wijck, Ruud; Schoufour, Josje D; Evenhuis, Heleen M

2015-01-01

The ability to perform instrumental activities of daily living (IADL) is important for one's level of independence. A high incidence of limitations in IADL is seen in older adults with intellectual disabilities (ID), which is an important determinant for the amount of support one needs. The aim of this study was to assess the predictive value of physical fitness for the ability to perform IADL, over a 3-year follow-up period, in 601 older adults with ID. At baseline, an extensive physical fitness assessment was performed. In addition, professional caregivers completed the Lawton IADL scale, both at baseline and at follow-up. The average ability to perform IADL declined significantly over the 3-year follow-up period. A decline in the ability to perform IADL was seen in 44.3% of the participants. The percentage of participants being completely independent in IADL declined from 2.7% to 1.3%. Manual dexterity, balance, comfortable and fast gait speed, muscular endurance, and cardiorespiratory fitness were significant predictors for a decline in IADL after correcting for baseline IADL and personal characteristics (age, gender, level of ID, and Down syndrome). This can be interpreted as representing the predictive validity of the physical tests for a decline in IADL. This study shows that even though older adults with ID experience dependency on others due to cognitive limitations, physical fitness also is an important aspect for IADL, which stresses the importance of using physical fitness tests and physical fitness enhancing programs in the care for older adults with ID. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Predicting Upwelling Radiance on the West Florida Shelf

DTIC Science & Technology

2006-03-31

National Science Foundation . The chemical and biological model includes the ability to simulate multiple groups of phytoplankton, multiple limiting nutrients, spectral light harvesting by phytoplankton, multiple particulate and dissolved degradational pools of organic material, and non-stoichometric carbon, nitrogen, phosphorus, silica, and iron dynamics. It also includes a complete spectral light model for the prediction of Inherent Optical Properties (IOPs). The coupling of the predicted IOP model (Ecosim 2.0) with robust radiative transfer model (Ecolight

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

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

Age effects on sensory-processing abilities and their impact on handwriting.

PubMed

Engel-Yeger, Batya; Hus, Sari; Rosenblum, Sara

2012-12-01

Sensory-processing abilities are known to deteriorate in the elderly. As a result, daily activities such as handwriting may be impaired. Yet, knowledge about sensory-processing involvement in handwriting characteristics among older persons is limited. To examine how age influences sensory-processing abilities and the impact on handwriting as a daily performance. The study participants were 118 healthy, independently functioning adults divided into four age groups: 31-45, 46-60, 61-75 and 76+ years. All participants completed the Adolescent/ Adult Sensory Profile (AASP). Handwriting process was documented using the Computerized Handwriting Penmanship Evaluation Tool (ComPET). Age significantly affects sensory processing and handwriting pressure as well as temporal and spatial measures. Both handwriting time and spatial organization of the written product were predicted by sensory seeking. When examining age contribution to the prediction of handwriting by sensory processing, sensory seeking showed a tendency for predicting handwriting pressure (p = .06), while sensory sensitivity significantly predicted handwriting velocity. Age appears to influence sensory-processing abilities and affect daily performance tasks, such as handwriting, for which sensitivity and seeking for sensations are essential. Awareness of clinicians to sensory-processing deficits among older adults and examining their impact on broader daily activities are essential to improve daily performance and quality of life.

Model Predictive Control Based Motion Drive Algorithm for a Driving Simulator

NASA Astrophysics Data System (ADS)

Rehmatullah, Faizan

In this research, we develop a model predictive control based motion drive algorithm for the driving simulator at Toronto Rehabilitation Institute. Motion drive algorithms exploit the limitations of the human vestibular system to formulate a perception of motion within the constrained workspace of a simulator. In the absence of visual cues, the human perception system is unable to distinguish between acceleration and the force of gravity. The motion drive algorithm determines control inputs to displace the simulator platform, and by using the resulting inertial forces and angular rates, creates the perception of motion. By using model predictive control, we can optimize the use of simulator workspace for every maneuver while simulating the vehicle perception. With the ability to handle nonlinear constraints, the model predictive control allows us to incorporate workspace limitations.

Incremental Validity of the WJ III COG: Limited Predictive Effects beyond the GIA-E

ERIC Educational Resources Information Center

McGill, Ryan J.; Busse, R. T.

2015-01-01

This study is an examination of the incremental validity of Cattell-Horn-Carroll (CHC) broad clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ III ACH). The participants were children and adolescents, ages 6-18 (n = 4,722), drawn from the WJ…

Route Prediction on Tracking Data to Location-Based Services

NASA Astrophysics Data System (ADS)

Petróczi, Attila István; Gáspár-Papanek, Csaba

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

12 CFR 1002.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... security for the credit or collateral). The creditor shall exercise reasonable diligence in obtaining such... creditor utilizing the system (including, but not limited to, minimizing bad debt losses and operating... statistical principles and methodology and adjusted as necessary to maintain predictive ability. (2) A...

NATIONAL URBAN DATABASE AND ACCESS PROTAL TOOL

EPA Science Inventory

Current mesoscale weather prediction and microscale dispersion models are limited in their ability to perform accurate assessments in urban areas. A project called the National Urban Database with Access Portal Tool (NUDAPT) is beginning to provide urban data and improve the para...

Nonlinear rocket motor stability prediction: Limit amplitude, triggering, and mean pressure shifta)

NASA Astrophysics Data System (ADS)

Flandro, Gary A.; Fischbach, Sean R.; Majdalani, Joseph

2007-09-01

High-amplitude pressure oscillations in solid propellant rocket motor combustion chambers display nonlinear effects including: (1) limit cycle behavior in which the fluctuations may dwell for a considerable period of time near their peak amplitude, (2) elevated mean chamber pressure (DC shift), and (3) a triggering amplitude above which pulsing will cause an apparently stable system to transition to violent oscillations. Along with the obvious undesirable vibrations, these features constitute the most damaging impact of combustion instability on system reliability and structural integrity. The physical mechanisms behind these phenomena and their relationship to motor geometry and physical parameters must, therefore, be fully understood if instability is to be avoided in the design process, or if effective corrective measures must be devised during system development. Predictive algorithms now in use have limited ability to characterize the actual time evolution of the oscillations, and they do not supply the motor designer with information regarding peak amplitudes or the associated critical triggering amplitudes. A pivotal missing element is the ability to predict the mean pressure shift; clearly, the designer requires information regarding the maximum chamber pressure that might be experienced during motor operation. In this paper, a comprehensive nonlinear combustion instability model is described that supplies vital information. The central role played by steep-fronted waves is emphasized. The resulting algorithm provides both detailed physical models of nonlinear instability phenomena and the critically needed predictive capability. In particular, the origin of the DC shift is revealed.

The Relationship Between Speech, Language, and Phonological Awareness in Preschool-Age Children With Developmental Disabilities.

PubMed

Barton-Hulsey, Andrea; Sevcik, Rose A; Romski, MaryAnn

2018-05-03

A number of intrinsic factors, including expressive speech skills, have been suggested to place children with developmental disabilities at risk for limited development of reading skills. This study examines the relationship between these factors, speech ability, and children's phonological awareness skills. A nonexperimental study design was used to examine the relationship between intrinsic skills of speech, language, print, and letter-sound knowledge to phonological awareness in 42 children with developmental disabilities between the ages of 48 and 69 months. Hierarchical multiple regression was done to determine if speech ability accounted for a unique amount of variance in phonological awareness skill beyond what would be expected by developmental skills inclusive of receptive language and print and letter-sound knowledge. A range of skill in all areas of direct assessment was found. Children with limited speech were found to have emerging skills in print knowledge, letter-sound knowledge, and phonological awareness. Speech ability did not predict a significant amount of variance in phonological awareness beyond what would be expected by developmental skills of receptive language and print and letter-sound knowledge. Children with limited speech ability were found to have receptive language and letter-sound knowledge that supported the development of phonological awareness skills. This study provides implications for practitioners and researchers concerning the factors related to early reading development in children with limited speech ability and developmental disabilities.

Does working memory capacity predict cross-modally induced failures of awareness?

PubMed

Kreitz, Carina; Furley, Philip; Simons, Daniel J; Memmert, Daniel

2016-01-01

People often fail to notice unexpected stimuli when they are focusing attention on another task. Most studies of this phenomenon address visual failures induced by visual attention tasks (inattentional blindness). Yet, such failures also occur within audition (inattentional deafness), and people can even miss unexpected events in one sensory modality when focusing attention on tasks in another modality. Such cross-modal failures are revealing because they suggest the existence of a common, central resource limitation. And, such central limits might be predicted from individual differences in cognitive capacity. We replicated earlier evidence, establishing substantial rates of inattentional deafness during a visual task and inattentional blindness during an auditory task. However, neither individual working memory capacity nor the ability to perform the primary task predicted noticing in either modality. Thus, individual differences in cognitive capacity did not predict failures of awareness even though the failures presumably resulted from central resource limitations. Copyright © 2015 Elsevier Inc. All rights reserved.

Sex differences in cognitive ageing: testing predictions derived from life-history theory in a dioecious nematode.

PubMed

Zwoinska, Martyna K; Kolm, Niclas; Maklakov, Alexei A

2013-12-01

Life-history theory maintains that organisms allocate limited resources to different traits to maximize fitness. Learning ability and memory are costly and known to trade-off with longevity in invertebrates. However, since the relationship between longevity and fitness often differs between the sexes, it is likely that sexes will differentially resolve the trade-off between learning and longevity. We used an established associative learning paradigm in the dioecious nematode Caenorhabditis remanei, which is sexually dimorphic for lifespan, to study age-related learning ability in males and females. In particular, we tested the hypothesis that females (the shorter-lived sex) show higher learning ability than males early in life but senesce faster. Indeed, young females outperformed young males in learning a novel association between an odour (butanone) and food (bacteria). However, while learning ability and offspring production declined rapidly with age in females, males maintained high levels of these traits until mid-age. These results not only demonstrate sexual dimorphism in age-related learning ability but also suggest that it conforms to predictions derived from the life-history theory. © 2013.

12 CFR 202.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... creditor shall exercise reasonable diligence in obtaining such information. (g) Business credit refers to... system (including, but not limited to, minimizing bad debt losses and operating expenses in accordance... principles and methodology and adjusted as necessary to maintain predictive ability. (2) A creditor may use...

A three-dimensional turbulent separated flow and related mesurements

NASA Technical Reports Server (NTRS)

Pierce, F. J.

1985-01-01

The applicability of and the limits on the applicability of 11 near wall similarity laws characterizing three-dimensional turbulent boundary layer flows were determined. A direct force sensing local wall shear stress meter was used in both pressure-driven and shear-driven three-dimensional turbulent boundary layers, together with extensive mean velocity field and wall pressure field data. This resulted in a relatively large number of graphical comparisons of the predictive ability of 10 of these 11 similarity models relative to measured data over a wide range of flow conditions. Documentation of a complex, separated three-dimensional turbulent flow as a standard test case for evaluating the predictive ability of numerical codes solving such flows is presented.

Predicting perceived safety to drive the morning after drinking: The importance of hangover symptoms.

PubMed

Cameron, Elaine; French, David P

2016-07-01

People driving the day after drinking are at risk of impaired performance and accidents due to continued intoxication or the effects of alcohol hangover. Drivers are poor at estimating their own blood alcohol concentration, and some drive despite believing they are over the legal limit. It is therefore important to identify other factors influencing perceived ability to drive 'the morning after'. This study tested how accurately participants estimated their legal driving status, and the contribution of beliefs and hangover symptoms to the prediction of perceived driving safety. This cross-sectional study involved 193 students completing a questionnaire and alcohol breath test the morning after heavy alcohol consumption. Indicators of subjective intoxication, severity of hangover symptoms, estimated legal status and perceived safety to drive were measured. A hierarchical linear regression analysis was conducted. No participants thought they were under the English legal limit when they were not, and 47% thought they were over the limit when they were in fact legally permissible to drive. However, 20% of those believing they were over the limit nevertheless rated themselves as safe to drive. Hangover symptoms added 17% variance to the prediction of perceived safety to drive, over and above objective and subjective measures of intoxication. Perceived severity of hangover symptoms influence beliefs about driving ability: When judging safety to drive, people experiencing less severe symptoms believe they are less impaired. If this finding is robust, health promotion campaigns should aim to correct this misapprehension. [Cameron E, French D. Predicting perceived safety to drive the morning after drinking: The importance of hangover symptoms. Drug Alcohol Rev 2016;35:442-446]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Predicting paclitaxel-induced neutropenia using the DMET platform.

PubMed

Nieuweboer, Annemieke J M; Smid, Marcel; de Graan, Anne-Joy M; Elbouazzaoui, Samira; de Bruijn, Peter; Martens, John W; Mathijssen, Ron H J; van Schaik, Ron H N

2015-01-01

The use of paclitaxel in cancer treatment is limited by paclitaxel-induced neutropenia. We investigated the ability of genetic variation in drug-metabolizing enzymes and transporters to predict hematological toxicity. Using a discovery and validation approach, we identified a pharmacogenetic predictive model for neutropenia. For this, a drug-metabolizing enzymes and transporters plus DNA chip was used, which contains 1936 SNPs in 225 metabolic enzyme and drug-transporter genes. Our 10-SNP model in 279 paclitaxel-dosed patients reached 43% sensitivity in the validation cohort. Analysis in 3-weekly treated patients only resulted in improved sensitivity of 79%, with a specificity of 33%. None of our models reached statistical significance. Our drug-metabolizing enzymes and transporters-based SNP-models are currently of limited value for predicting paclitaxel-induced neutropenia in clinical practice. Original submitted 9 March 2015; Revision submitted 20 May 2015.

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.

Measures of functional limitation as predictors of disablement in athletes with acute ankle sprains.

PubMed

Wilson, R W; Gansneder, B M

2000-09-01

Prospective multivariate design. To determine the usefulness of activity scores, self-reported athletic ability, and selected measures of physical impairment as predictors of disability duration in athletes with ankle inversion sprains. Although several measures of physical impairment and functional limitation are used to assess the consequences of injury following ankle sprain, researchers have yet to establish which measures provide the most accurate predictions of disability duration. Physical impairment, activity limitation, and disability duration were measured in 21 athletes (13 men and 8 women; mean age = 20.3 +/- 1.7 years) with acute ankle sprains. Sagittal plane ankle range of motion and volumetric displacement were used as impairment indicators. Weight-bearing activity scores (task completion count) and self-reported athletic ability (visual analog scale) were used to represent functional limitation. Elapsed time from injury to return to full athletic participation was used as the criterion measure of disability duration. The impairment measures accounted for approximately one-third of the variance in disability duration (R2 = 0.342). Adding the activity limitation measures to the regression model improved predictions of disability duration (R2 = 0.670; stepwise R2 change = 0.328). The measures of activity limitation alone, however, accounted for approximately 67% (R2 = 0.665) of the total variance in the number of days lost due to injury. Measures of activity limitation were the strongest predictors of elapsed time from injury to return to full athletic participation.

Implicit Theories, Expectancies, and Values Predict Mathematics Motivation and Behavior across High School and College.

PubMed

Priess-Groben, Heather A; Hyde, Janet Shibley

2017-06-01

Mathematics motivation declines for many adolescents, which limits future educational and career options. The present study sought to identify predictors of this decline by examining whether implicit theories assessed in ninth grade (incremental/entity) predicted course-taking behaviors and utility value in college. The study integrated implicit theory with variables from expectancy-value theory to examine potential moderators and mediators of the association of implicit theories with college mathematics outcomes. Implicit theories and expectancy-value variables were assessed in 165 American high school students (47 % female; 92 % White), who were then followed into their college years, at which time mathematics courses taken, course-taking intentions, and utility value were assessed. Implicit theories predicted course-taking intentions and utility value, but only self-concept of ability predicted courses taken, course-taking intentions, and utility value after controlling for prior mathematics achievement and baseline values. Expectancy for success in mathematics mediated associations between self-concept of ability and college outcomes. This research identifies self-concept of ability as a stronger predictor than implicit theories of mathematics motivation and behavior across several years: math self-concept is critical to sustained engagement in mathematics.

Predictive Validation of an Influenza Spread Model

PubMed Central

Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

2013-01-01

Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive ability. PMID:23755236

Identifying and Assessing Gaps in Subseasonal to Seasonal Prediction Skill using the North American Multi-model Ensemble

NASA Astrophysics Data System (ADS)

Pegion, K.; DelSole, T. M.; Becker, E.; Cicerone, T.

2016-12-01

Predictability represents the upper limit of prediction skill if we had an infinite member ensemble and a perfect model. It is an intrinsic limit of the climate system associated with the chaotic nature of the atmosphere. Producing a forecast system that can make predictions very near to this limit is the ultimate goal of forecast system development. Estimates of predictability together with calculations of current prediction skill are often used to define the gaps in our prediction capabilities on subseasonal to seasonal timescales and to inform the scientific issues that must be addressed to build the next forecast system. Quantification of the predictability is also important for providing a scientific basis for relaying to stakeholders what kind of climate information can be provided to inform decision-making and what kind of information is not possible given the intrinsic predictability of the climate system. One challenge with predictability estimates is that different prediction systems can give different estimates of the upper limit of skill. How do we know which estimate of predictability is most representative of the true predictability of the climate system? Previous studies have used the spread-error relationship and the autocorrelation to evaluate the fidelity of the signal and noise estimates. Using a multi-model ensemble prediction system, we can quantify whether these metrics accurately indicate an individual model's ability to properly estimate the signal, noise, and predictability. We use this information to identify the best estimates of predictability for 2-meter temperature, precipitation, and sea surface temperature from the North American Multi-model Ensemble and compare with current skill to indicate the regions with potential for improving skill.

ABOVEGROUND NITROGEN USE EFFICIENCY AND GROWTH DYNAMICS IN SPARTINA ALTERNIFLORA AND DISTICHLIS SPICATA

EPA Science Inventory

Long-term nitrogen (N) fertilization studies suggest shifting dominance from Spartina alterniflora to Distichlis spicata, although the underlying mechanism is unclear. A limitation on our ability to predict changes is a poor understanding of resource use under ambient conditions....

in vitro Models if Human Embryonic Mesenchymal Transitions in Morphogenesis

EPA Science Inventory

Our ability to predict human developmental consequences produced by exposure to environmental chemicals is limited by the current experimental and computational models.Human heart defects are among the most common type of birth defects and affect 1% of children (~40,000 children)...

Use of the triglyceride to HDL cholesterol ratio for assessing insulin sensitivity in overweight and obese children in rural Appalachia

PubMed Central

Bridges, Kristie Grove; Jarrett, Traci; Thorpe, Anthony; Baus, Adam; Cochran, Jill

2015-01-01

Background Studies have suggested that triglyceride to HDL-cholesterol ratio (TRG/HDL) is a surrogate marker of insulin resistance (IR), but information regarding its use in pediatric patients is limited. Objective This study investigated the ability of TRG/HDL ratio to assess IR in obese and overweight children. Subjects The sample consisted of de-identified electronic medical records of patients aged 10–17 years (n = 223). Materials and methods Logistic regression was performed using TRG/HDL ratio as a predictor of hyperinsulinemia or IR defined using homeostasis model assessment score. Results TRG/HDL ratio had limited ability to predict hyperinsulinemia (AUROC 0.71) or IR (AUROC 0.72). Although females had higher insulin levels, male patients were significantly more likely to have hypertriglyceridemia and impaired fasting glucose. Conclusions TRG/HDL ratio was not adequate for predicting IR in this population. Gender differences in the development of obesity-related metabolic abnormalities may impact the choice of screening studies in pediatric patients. PMID:26352085

Paving the Way for Predictive Ecotoxicology in the 21st Century

EPA Science Inventory

The ability to conduct traditional whole organism toxicity tests for increasingly wide inventories of chemicals of concern is limited by the resource-intensity of the approach in terms of cost, person-hours, and animal use. In a 2007 report, a National Research Council Committee ...

Large-scale optimization-based classification models in medicine and biology.

PubMed

Lee, Eva K

2007-06-01

We present novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule); and (5) successive multi-stage classification capability to handle data points placed in the reserved-judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multi-group prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80 to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

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

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.

A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following

NASA Astrophysics Data System (ADS)

Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar

2010-04-01

In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (< 30miles/h) car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.

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

Exploring the Relationship between Adolescent's Reading Skills, Reading Motivation and Reading Habits

ERIC Educational Resources Information Center

McGeown, Sarah P.; Duncan, Lynne G.; Griffiths, Yvonne M.; Stothard, Sue E.

2015-01-01

The present study examines the extent to which adolescents' reading affect (reading motivation) and behaviour (reading habits) predict different components of reading (word reading, comprehension, summarisation and text reading speed) and also adds to the limited research examining group differences (gender, age, ability) in adolescents' reading…

Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis

USDA-ARS?s Scientific Manuscript database

The proliferation of tower-mounted cameras co-located with eddy covariance instrumentation provides a novel opportunity to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper, we describe the abilities and limitations of webcams to ...

Toward an index of desiccation times to tree mortality under drought

USDA-ARS?s Scientific Manuscript database

Research in plant hydraulics has provided important insights into plant responses to drought and species absolute drought tolerance. However our ability to predict when plants will die under extreme drought may be limited by a lack of knowledge with regards to the dynamics of plant desiccation from ...

Prediction of aquatic toxicity mode of action using linear discriminant and random forest models

EPA Science Inventory

The ability to determine the mode of action (MOA) for a diverse group of chemicals is a critical part of ecological risk assessment and chemical regulation. However, existing MOA assignment approaches in ecotoxicology have been limited to a relatively few MOAs, have high uncertai...

Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.

PubMed

Müller, Bárbara S F; Neves, Leandro G; de Almeida Filho, Janeo E; Resende, Márcio F R; Muñoz, Patricio R; Dos Santos, Paulo E T; Filho, Estefano Paludzyszyn; Kirst, Matias; Grattapaglia, Dario

2017-07-11

The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses. Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000-10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study. This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.

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

PubMed

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

2013-04-01

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

Assessing Workplace Emotional Intelligence: Development and Validation of an Ability-based Measure.

PubMed

Krishnakumar, Sukumarakurup; Hopkins, Kay; Szmerekovsky, Joseph G; Robinson, Michael D

2016-01-01

Existing measures of Emotional Intelligence (EI), defined as the ability to perceive, understand, and manage emotions for productive purposes, have displayed limitations in predicting workplace outcomes, likely in part because they do not target this context. Such considerations led to the development of an ability EI measure with work-related scenarios in which respondents infer the likely emotions (perception) and combinations of emotion (understanding) that would occur to protagonists while rating the effectiveness of ways of responding (management). Study 1 (n = 290 undergraduates) used item-total correlations to select scenarios from a larger pool and Study 2 (n = 578) reduced the measure-termed the NEAT-to 30 scenarios on the basis of structural equation modeling. Study 3 (n = 96) then showed that the NEAT had expected correlations with personality and cognitive ability and Study 4 (n = 85) demonstrated convergent validity with other ability EI measures. Last, study 5 (n = 91) established that the NEAT had predictive validity with respect to job satisfaction, job stress, and job performance. The findings affirm the importance of EI in the workplace in the context of a valid new instrument for assessing relevant skills.

Know the risk, take the win: how executive functions and probability processing influence advantageous decision making under risk conditions.

PubMed

Brand, Matthias; Schiebener, Johannes; Pertl, Marie-Theres; Delazer, Margarete

2014-01-01

Recent models on decision making under risk conditions have suggested that numerical abilities are important ingredients of advantageous decision-making performance, but empirical evidence is still limited. The results of our first study show that logical reasoning and basic mental calculation capacities predict ratio processing and that ratio processing predicts decision making under risk. In the second study, logical reasoning together with executive functions predicted probability processing (numeracy and probability knowledge), and probability processing predicted decision making under risk. These findings suggest that increasing an individual's understanding of ratios and probabilities should lead to more advantageous decisions under risk conditions.

Testing the transtheoretical model in predicting smoking relapse among Malaysian adult smokers receiving assistance in quitting.

PubMed

Yasin, Siti Munira; Retneswari, Masilamani; Moy, Foong Ming; Taib, Khairul Mizan; Isahak, Marzuki; Koh, David

2013-01-01

The role of The Transtheoretical Model (TTM) in predicting relapse is limited. We aimed to assess whether this model can be utilised to predict relapse during the action stage. The participants included 120 smokers who had abstained from smoking for at least 24 hours following two Malaysian universities' smoking cessation programme. The smokers who relapsed perceived significantly greater advantages related to smoking and increasing doubt in their ability to quit. In contrast, former smokers with greater self-liberation and determination to abstain were less likely to relapse. The findings suggest that TTM can be used to predict relapse among quitting smokers.

Limitations of BCC_CSM's ability to predict summer precipitation over East Asia and the Northwestern Pacific

NASA Astrophysics Data System (ADS)

Gong, Zhiqiang; Dogar, Muhammad Mubashar Ahmad; Qiao, Shaobo; Hu, Po; Feng, Guolin

2017-09-01

This study examines the ability of the Beijing Climate Center Climate System Model (BCC_CSM) to predict the meridional pattern of summer precipitation over East Asia-Northwest Pacific (EA-NWP) and its East Asia-Pacific (EAP) teleconnection. The differences of summer precipitation modes of the empirical orthogonal function and the bias of atmospheric circulations over EA-NWP are analyzed to determine the reason for the precipitation prediction errors. Results indicate that the BCC_CSM could not reproduce the positive-negative-positive meridional tripole pattern from south to north that differs markedly from that observed over the last 20 years. This failure can be attributed to the bias of the BCC_CSM hindcasts of the summer EAP teleconnection and the low predictability of 500 hPa at the mid-high latitude lobe of the EAP. Meanwhile, the BCC_CSM hindcasts' deficiencies of atmospheric responses to SST anomalies over the Indonesia maritime continent (IMC) resulted in opposite and geographically shifted geopotential anomalies at 500 hPa as well as wind and vorticity anomalies at 850 hPa, rendering the BCC_CSM unable to correctly reproduce the EAP teleconnection pattern. Understanding these two problems will help further improve BCC_CSM's summer precipitation forecasting ability over EA-NWP.

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.

Neural Activity Reveals Preferences Without Choices

PubMed Central

Smith, Alec; Bernheim, B. Douglas; Camerer, Colin

2014-01-01

We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to “non-choice” neural responses and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach. PMID:25729468

Non-climatic constraints on upper elevational plant range expansion under climate change

PubMed Central

Brown, Carissa D.; Vellend, Mark

2014-01-01

We are limited in our ability to predict climate-change-induced range shifts by our inadequate understanding of how non-climatic factors contribute to determining range limits along putatively climatic gradients. Here, we present a unique combination of observations and experiments demonstrating that seed predation and soil properties strongly limit regeneration beyond the upper elevational range limit of sugar maple, a tree species of major economic importance. Most strikingly, regeneration beyond the range limit occurred almost exclusively when seeds were experimentally protected from predators. Regeneration from seed was depressed on soil from beyond the range edge when this soil was transplanted to sites within the range, with indirect evidence suggesting that fungal pathogens play a role. Non-climatic factors are clearly in need of careful attention when attempting to predict the biotic consequences of climate change. At minimum, we can expect non-climatic factors to create substantial time lags between the creation of more favourable climatic conditions and range expansion. PMID:25253462

Use of self-report to predict ability to walk 400 meters in mobility-limited older adults.

PubMed

Sayers, Stephen P; Brach, Jennifer S; Newman, Anne B; Heeren, Tim C; Guralnik, Jack M; Fielding, Roger A

2004-12-01

To determine whether the ability to walk 400 m could be predicted from self-reported walking habits and abilities in older adults and to develop an accurate self-report measure appropriate for observational trials of mobility when functional measures are impractical to collect. Cross-sectional. University-based human physiology laboratory. One hundred fifty community-dwelling older men and women (mean age+/-standard error= 79.8+/-0.3). An 18-item questionnaire assessing walking habits and ability was administered to each participant, followed by a 400-m walk test. Ninety-eight (65%) volunteers were able to complete the 400-m walk; 52 (35%) were unable. Logistic regression was performed using response items from a questionnaire as predictors and 400-m walk as the outcome. Three questions (Do you think you could walk one-quarter of a mile now without sitting down to rest. Because of a health or physical problem, do you have difficulty walking 1 mile? Could you walk up and down every aisle of a grocery store without sitting down to rest or leaning on a cart?) were predictive of 400-m walking ability and were included in the model. If participants answered all three questions compatible with the inability to walk 400 m, there was a 91% probability that they were unable to walk 400 m, with a sensitivity of 46% and a specificity of 97%. A three-item self-report developed in the study was able to accurately predict mobility disability. The utility of this instrument may be in evaluating self-reported mobility in large observational trials on mobility when functional mobility tasks are impractical to collect.

The Physiochemistry of Capped Nanosilver Predicts Its Biological Activity in Rat Brain Endothelial Cells (REBEC4)

EPA Science Inventory

The “capping” or coating of nanosilver (nanoAg) extends its potency by limiting its oxidation and aggregation and stabilizing its size and shape. The ability of such coated nanoAg to alter the permeability and activate oxidative stress pathways in rat brain endothelia...

Multiple-Stimulus without Replacement Preference Assessment for Students at Risk for Emotional Disturbance

ERIC Educational Resources Information Center

King, Seth A.

2016-01-01

The ability of educators to identify consequences that act as reinforcers may predict the success of behavior change strategies predicated on the use of reinforcement. Supported for individuals with severe disabilities, research concerning the effectiveness of choice-stimulus assessment for students with emotional disturbance (ED) remains limited.…

Investigating the running abilities of Tyrannosaurus rex using stress-constrained multibody dynamic analysis

PubMed Central

Pond, Stuart B.; Brassey, Charlotte A.; Manning, Philip L.; Bates, Karl T.

2017-01-01

The running ability of Tyrannosaurus rex has been intensively studied due to its relevance to interpretations of feeding behaviour and the biomechanics of scaling in giant predatory dinosaurs. Different studies using differing methodologies have produced a very wide range of top speed estimates and there is therefore a need to develop techniques that can improve these predictions. Here we present a new approach that combines two separate biomechanical techniques (multibody dynamic analysis and skeletal stress analysis) to demonstrate that true running gaits would probably lead to unacceptably high skeletal loads in T. rex. Combining these two approaches reduces the high-level of uncertainty in previous predictions associated with unknown soft tissue parameters in dinosaurs, and demonstrates that the relatively long limb segments of T. rex—long argued to indicate competent running ability—would actually have mechanically limited this species to walking gaits. Being limited to walking speeds contradicts arguments of high-speed pursuit predation for the largest bipedal dinosaurs like T. rex, and demonstrates the power of multiphysics approaches for locomotor reconstructions of extinct animals. PMID:28740745

Cognitive Predictors of Everyday Problem Solving across the Lifespan.

PubMed

Chen, Xi; Hertzog, Christopher; Park, Denise C

2017-01-01

An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24-93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on EPT. Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of 50 years. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. © 2017 S. Karger AG, Basel.

Classification and disease prediction via mathematical programming

NASA Astrophysics Data System (ADS)

Lee, Eva K.; Wu, Tsung-Lin

2007-11-01

In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80% to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

PubMed

Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

2010-10-01

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

Observer properties for understanding dynamical displays: Capacities, limitations, and defaults

NASA Technical Reports Server (NTRS)

Proffitt, Dennis R.; Kaiser, Mary K.

1991-01-01

People's ability to extract relevant information while viewing ongoing events is discussed in terms of human capabilities, limitations, and defaults. A taxonomy of event complexity is developed which predicts which dynamical events people can and cannot construe. This taxonomy is related to the distinction drawn in classical mechanics between particle and extended body motions. People's commonsense understandings of simple mechanical systems are impacted little by formal training, but rather reflect heuristical simplifications that focus on a single dimension of perceived dynamical relevance.

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

Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT.

PubMed

Shouval, R; Bondi, O; Mishan, H; Shimoni, A; Unger, R; Nagler, A

2014-03-01

Data collected from hematopoietic SCT (HSCT) centers are becoming more abundant and complex owing to the formation of organized registries and incorporation of biological data. Typically, conventional statistical methods are used for the development of outcome prediction models and risk scores. However, these analyses carry inherent properties limiting their ability to cope with large data sets with multiple variables and samples. Machine learning (ML), a field stemming from artificial intelligence, is part of a wider approach for data analysis termed data mining (DM). It enables prediction in complex data scenarios, familiar to practitioners and researchers. Technological and commercial applications are all around us, gradually entering clinical research. In the following review, we would like to expose hematologists and stem cell transplanters to the concepts, clinical applications, strengths and limitations of such methods and discuss current research in HSCT. The aim of this review is to encourage utilization of the ML and DM techniques in the field of HSCT, including prediction of transplantation outcome and donor selection.

Direct and indirect measures of Level-2 perspective-taking in children and adults.

PubMed

Surtees, Andrew D R; Butterfill, Stephen A; Apperly, Ian A

2012-03-01

Studies with infants show divergence between performance on theory of mind tasks depending on whether direct or indirect measures are used. It has been suggested that direct measures assess a flexible but cognitively demanding ability to reason about the minds of others, whereas indirect measures assess distinct processes which afford more efficient but less flexible theory of mind abilities (Apperly & Butterfill, 2009). This leads to the prediction that performance on indirect measures should be subject to signature limits. The current study tested whether the Level-1/Level-2 distinction might constitute one such limit. The study adapted a task that has shown evidence of Level-1 perspective-taking on both direct and indirect measures (Samson, Apperly, Braithwaite, Andrews, & Bodley-Scott, 2010). The aim was to test Level-2 perspective-taking in a sample of 6- to 11-year-olds (N = 80) and adults (N = 20). Participants were able to make Level-2 judgements on the direct measure. In contrast with the findings from Level-1 perspective-taking, there was no evidence of automatic processing of Level-2 perspectives on the indirect measure. This finding is consistent with the view that theory of mind abilities assessed by indirect measures are subject to signature limits. The Level-1/Level-2 distinction, suitably refined, marks one way in which efficient but inflexible theory of mind abilities are limited. © 2011 The British Psychological Society.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

PubMed

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian whip snake.

PubMed

Sahlean, Tiberiu C; Gherghel, Iulian; Papeş, Monica; Strugariu, Alexandru; Zamfirescu, Ştefan R

2014-01-01

Climate warming is one of the most important threats to biodiversity. Ectothermic organisms such as amphibians and reptiles are especially vulnerable as climatic conditions affect them directly. Ecological niche models (ENMs) are increasingly popular in ecological studies, but several drawbacks exist, including the limited ability to account for the dispersal potential of the species. In this study, we use ENMs to explore the impact of global climate change on the Caspian whip snake (Dolichophis caspius) as model for organisms with low dispersal abilities and to quantify dispersal to novel areas using GIS techniques. Models generated using Maxent 3.3.3 k and GARP for current distribution were projected on future climatic scenarios. A cost-distance analysis was run in ArcGIS 10 using geomorphological features, ecological conditions, and human footprint as "costs" to dispersal of the species to obtain a Maximum Dispersal Range (MDR) estimate. All models developed were statistically significant (P<0.05) and recovered the currently known distribution of D. caspius. Models projected on future climatic conditions using Maxent predicted a doubling of suitable climatic area, while GARP predicted a more conservative expansion. Both models agreed on an expansion of suitable area northwards, with minor decreases at the southern distribution limit. The MDR area calculated using the Maxent model represented a third of the total area of the projected model. The MDR based on GARP models recovered only about 20% of the total area of the projected model. Thus, incorporating measures of species' dispersal abilities greatly reduced estimated area of potential future distributions.

Predicting the potential future distribution of four tree species in Ohio using current habitat availability and climatic forcing

Treesearch

Mark W. Schwartz; Louis R. Iverson; Anantha M. Prasad

2001-01-01

We investigated the effect of habitat loss on the ability of trees to shift in distribution across a landscape dominated by agriculture. The potential distribution shifts of four tree species (Diospyros virginiana, Oxydendron arboreum, Pinus virginiana, Quercus falcata var. falcata) whose northern distribution limits fall in the...

Uncertainty in natural hazards, modeling and decision support: An introduction to this volume [Chapter 1

Treesearch

Karin Riley; Matthew Thompson; Peter Webley; Kevin D. Hyde

2017-01-01

Modeling has been used to characterize and map natural hazards and hazard susceptibility for decades. Uncertainties are pervasive in natural hazards analysis, including a limited ability to predict where and when extreme events will occur, with what consequences, and driven by what contributing factors. Modeling efforts are challenged by the intrinsic...

Prognostic Indicators: Predicting Degree of Change from Interventions for Adolescents at Risk for Language Weakness

ERIC Educational Resources Information Center

Poll, Gerard H.; Burke, Lisa; Miller, Carol A.; Fiene, Judy

2017-01-01

Prognostic statements are a standard component of assessments for adolescents at risk for language-learning disabilities, but there is limited evidence on the validity of prognostic indicators. In two studies, we collected measures of language ability and candidate prognostic indicators from adolescents age 12 to 13. We conducted an expository…

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/.

The predictability of a lake phytoplankton community, over time-scales of hours to years.

PubMed

Thomas, Mridul K; Fontana, Simone; Reyes, Marta; Kehoe, Michael; Pomati, Francesco

2018-05-01

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R 2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics. © 2018 John Wiley & Sons Ltd/CNRS.

A methodology for reduced order modeling and calibration of the upper atmosphere

NASA Astrophysics Data System (ADS)

Mehta, Piyush M.; Linares, Richard

2017-10-01

Atmospheric drag is the largest source of uncertainty in accurately predicting the orbit of satellites in low Earth orbit (LEO). Accurately predicting drag for objects that traverse LEO is critical to space situational awareness. Atmospheric models used for orbital drag calculations can be characterized either as empirical or physics-based (first principles based). Empirical models are fast to evaluate but offer limited real-time predictive/forecasting ability, while physics based models offer greater predictive/forecasting ability but require dedicated parallel computational resources. Also, calibration with accurate data is required for either type of models. This paper presents a new methodology based on proper orthogonal decomposition toward development of a quasi-physical, predictive, reduced order model that combines the speed of empirical and the predictive/forecasting capabilities of physics-based models. The methodology is developed to reduce the high dimensionality of physics-based models while maintaining its capabilities. We develop the methodology using the Naval Research Lab's Mass Spectrometer Incoherent Scatter model and show that the diurnal and seasonal variations can be captured using a small number of modes and parameters. We also present calibration of the reduced order model using the CHAMP and GRACE accelerometer-derived densities. Results show that the method performs well for modeling and calibration of the upper atmosphere.

Hurricane and Monsoon Tracking with Driftsondes

NASA Astrophysics Data System (ADS)

Drobinski, Philippe; Cocquerez, Philippe; Doerenbecher, A.; Hock, Terrence; Lavaysse, C.; Parsons, D.; Redelsperger, J. L.

Tropical cyclones (TCs) are a typical weather threat. The threat can apply to humans, their properties, and activities. Their prediction, particularly their trajectory and intensity, remains difficult. In addition, TCs develop above the tropical oceans where the coverage by in situ observations is poor and within cloud clusters (mesoscale convective systems MCS) that limit the ability of numerical weather prediction (NWP) models to assimilate satellite data [18]. Improved forecast of TCs trajectories is a huge benefit in terms of material costs of evacuations and damage, not being able to quantify saved life.

The ‘unskilled and unaware’ effect is linear in a real-world setting

PubMed Central

Sawdon, Marina; Finn, Gabrielle

2014-01-01

Self-assessment ability in medical students and practising physicians is generally poor, yet essential for academic progress and professional development. The aim of this study was to determine undergraduate medical students' ability to self-assess their exam performance accurately in a real-world, high-stakes exam setting, something not previously investigated. Year 1 and Year 2 medical students (n = 74) participated in a self-assessment exercise. Students predicted their exam grade (%) on the anatomy practical exam. This exercise was completed online immediately after the exam. Students' predicted exam grades were correlated with their actual attained exam grades using a Pearson's correlation. Demographic data were analysed using an independent t-test. A negative correlation was found between students' overall predicted and attained exam grades (P < 0.0001). There was a significant difference between the students' predicted grades and actual grades in the bottom, 3rd and top (P < 0.0001), but not 2nd quartiles of participants. There was no relationship between the students' entry status into medical school and self-assessment ability (Year 1: P = 0.112; Year 2: P = 0.236) or between males and females (Year 1: P = 0.174). However, a relationship was determined for these variables in Year 2 (P = 0.022). The number of hours of additional self-directed learning undertaken did not influence students' self-assessment in both years. Our results demonstrate the ‘unskilled and unaware’ phenomenon in a real-world, high-stakes and practice-related setting. Students in all quartiles were unable to self-assess their exam performance, except for a group of mid-range students in the 2nd quartile. Poor performers were shown to overestimate their ability and, conversely, high achievers to underestimate their performance. We present evidence of a strong, significant linear relationship between medical students' ability to self-assess their performance in an anatomy practical exam, and their actual performance; in a real world setting. Despite the limited ability to self-assess reported in the literature, our results may inform approaches to revalidation, which currently frequently rely on an ability to self-assess. PMID:23781887

Injury severity and disability in the selection of next level of care following acute medical treatment for traumatic brain injury.

PubMed

Malec, James F; Mandrekar, Jayawant N; Brown, Allen W; Moessner, Anne M

2009-01-01

To evaluate the association of demographic factors, post-traumatic amnesia (PTA) and a standardized measure of ability limitations with clinical decisions for Next Level of Care following acute hospital treatment for moderate-severe traumatic brain injury (TBI). A TBI Clinical Nurse specialist recorded PTA for 212 individuals and rated 159 on the Ability and Adjustment Indices of the Mayo-Portland Adaptability Inventory (MPAI-4) for comparison with clinical decisions. Multivariate logistic regression analyses revealed that independent ratings on the MPAI-4 Ability Index and PTA were associated with the clinical decision to admit to Inpatient Rehabilitation vs discharge to Home in 92.7% of the sample; ratings on the Ability Index alone were associated with this decision in 92.2% of cases. Age over 65 was the only variable associated with discharge to a Skilled Nursing Facility, correctly predicting this decision in 64% of cases. Use of a standardized measure of ability limitations appears feasible to provide supportive documentation and potentially improve the consistency of decision-making in recommending Inpatient Rehabilitation vs discharge to Home. Although age is a significant factor in the decision to discharge to a Skilled Nursing Facility, this decision appears complex and merits further study.

Cognitive Predictors of Everyday Problem Solving across the Lifespan

PubMed Central

Chen, Xi; Hertzog, Christopher; Park, Denise C.

2017-01-01

Background An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. Objectives The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT; [1]). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Method Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24–93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on the Everyday Problems Test. Results Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of fifty. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. Conclusion This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. PMID:28273664

The Potential for Predicting Precipitation on Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, R. D.

1999-01-01

The ability to predict precipitation several months in advance would have a significant impact on water resource management. This talk provides an overview of a project aimed at developing this prediction capability. NASA's Seasonal-to-Interannual Prediction Project (NSIPP) will generate seasonal-to-interannual sea surface temperature predictions through detailed ocean circulation modeling and will then translate these SST forecasts into forecasts of continental precipitation through the application of an atmospheric general circulation model and a "SVAT"-type land surface model. As part of the process, ocean variables (e.g., height) and land variables (e.g., soil moisture) will be updated regularly via data assimilation. The overview will include a discussion of the variability inherent in such a modeling system and will provide some quantitative estimates of the absolute upper limits of seasonal-to-interannual precipitation predictability.

Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

NASA Technical Reports Server (NTRS)

Smith, Craig; Morscher, Gregory; Xia, Zhenhai

2009-01-01

Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

Unpredictability of escape trajectory explains predator evasion ability and microhabitat preference of desert rodents.

PubMed

Moore, Talia Y; Cooper, Kimberly L; Biewener, Andrew A; Vasudevan, Ramanarayan

2017-09-05

Mechanistically linking movement behaviors and ecology is key to understanding the adaptive evolution of locomotion. Predator evasion, a behavior that enhances fitness, may depend upon short bursts or complex patterns of locomotion. However, such movements are poorly characterized by existing biomechanical metrics. We present methods based on the entropy measure of randomness from Information Theory to quantitatively characterize the unpredictability of non-steady-state locomotion. We then apply the method by examining sympatric rodent species whose escape trajectories differ in dimensionality. Unlike the speed-regulated gait use of cursorial animals to enhance locomotor economy, bipedal jerboa (family Dipodidae) gait transitions likely enhance maneuverability. In field-based observations, jerboa trajectories are significantly less predictable than those of quadrupedal rodents, likely increasing predator evasion ability. Consistent with this hypothesis, jerboas exhibit lower anxiety in open fields than quadrupedal rodents, a behavior that varies inversely with predator evasion ability. Our unpredictability metric expands the scope of quantitative biomechanical studies to include non-steady-state locomotion in a variety of evolutionary and ecologically significant contexts.Biomechanical understanding of animal gait and maneuverability has primarily been limited to species with more predictable, steady-state movement patterns. Here, the authors develop a method to quantify movement predictability, and apply the method to study escape-related movement in several species of desert rodents.

Socio-cultural Input Facilitates Children’s Developing Understanding of Extraordinary Minds

PubMed Central

Lane, Jonathan D.; Wellman, Henry M.; Evans, E. Margaret

2012-01-01

Three- to 5-year-old (N=61) religiously-schooled preschoolers received theory-of-mind tasks about the mental states of ordinary humans and agents with exceptional perceptual or mental capacities. Consistent with an anthropomorphism hypothesis, children beginning to appreciate limitations of human minds (e.g., ignorance) attributed those limits to God. Only 5-year-olds differentiated between humans’ fallible minds and God’s less fallible mind. Unlike secularly-schooled children, religiously-schooled 4-year-olds did appreciate another agent’s less fallible mental abilities when instructed and reminded about those abilities. Among children who understood ordinary humans’ mental fallibilities, knowledge of God predicted attributions of correct epistemic states to extraordinary agents. Results suggest that, at a certain point in theory-of-mind development, socio-cultural input can facilitate an appreciation for extraordinary minds. PMID:22372590

A Limiting Feature of the Mozart Effect: Listening Enhances Mental Rotation Abilities in Non-Musicians but Not Musicians

ERIC Educational Resources Information Center

Aheadi, Afshin; Dixon, Peter; Glover, Scott

2010-01-01

The "Mozart effect" occurs when performance on spatial cognitive tasks improves following exposure to Mozart. It is hypothesized that the Mozart effect arises because listening to complex music activates similar regions of the right cerebral hemisphere as are involved in spatial cognition. A counter-intuitive prediction of this hypothesis (and one…

Effects of bathymetric lidar errors on flow properties predicted with a multi-dimensional hydraulic model

Treesearch

J. McKean; D. Tonina; C. Bohn; C. W. Wright

2014-01-01

New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional...

New Perspectives on Popular Culture, Science and Technology: Web Browsers and the New Illiteracy

ERIC Educational Resources Information Center

Charters, Elizabeth

2004-01-01

Analysts predict that the knowledge economy of the near future will require people to be both computer literate and print literate. However, some of the reading and thinking habits of current college students suggest that electronic media such as web browsers may be limiting the new generation's ability to absorb and process what they read. Their…

Does Part-Time Faculty's Self-Efficacy Predict Critical Dimensions of Online College Teaching?

ERIC Educational Resources Information Center

Hardy, Pamela; Shepard, Melvin; Pilotti, Maura

2017-01-01

Surveys have repeatedly depicted a dismal picture of part-time teaching in academia, including low pay, scant benefits, limited institutional support, and lack of job security. Thus, the main purpose of the present study was to delve deeper into part-time faculty's ability to sustain the demands of a tough work environment by examining the extent…

Reading the Mind in the Eyes or reading between the lines? Theory of Mind predicts collective intelligence equally well online and face-to-face.

PubMed

Engel, David; Woolley, Anita Williams; Jing, Lisa X; Chabris, Christopher F; Malone, Thomas W

2014-01-01

Recent research with face-to-face groups found that a measure of general group effectiveness (called "collective intelligence") predicted a group's performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members' ability to reason about the mental states of others (an ability called "Theory of Mind" or "ToM"). Since ToM was measured in this work by a test that requires participants to "read" the mental states of others from looking at their eyes (the "Reading the Mind in the Eyes" test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available. Here we find that: (1) a collective intelligence factor characterizes group performance approximately as well for online groups as for face-to-face groups; and (2) surprisingly, the ToM measure is equally predictive of collective intelligence in both face-to-face and online groups, even though the online groups communicate only via text and never see each other at all. This provides strong evidence that ToM abilities are just as important to group performance in online environments with limited nonverbal cues as they are face-to-face. It also suggests that the Reading the Mind in the Eyes test measures a deeper, domain-independent aspect of social reasoning, not merely the ability to recognize facial expressions of mental states.

Genotype-specific relationships among phosphorus use, growth and abundance in Daphnia pulicaria

PubMed Central

Chowdhury, Priyanka Roy; Baker, Kristina D.; Weider, Lawrence J.; Jeyasingh, Punidan D.

2017-01-01

The framework ecological stoichiometry uses elemental composition of species to make predictions about growth and competitive ability in defined elemental supply conditions. Although intraspecific differences in stoichiometry have been observed, we have yet to understand the mechanisms generating and maintaining such variation. We used variation in phosphorus (P) content within a Daphnia species to test the extent to which %P can explain variation in growth and competition. Further, we measured 33P kinetics (acquisition, assimilation, incorporation and retention) to understand the extent to which such variables improved predictions. Genotypes showed significant variation in P content, 33P kinetics and growth rate. P content alone was a poor predictor of growth rate and competitive ability. While most genotypes exhibited the typical growth penalty under P limitation, a few varied little in growth between P diets. These observations indicate that some genotypes can maintain growth under P-limited conditions by altering P use, suggesting that decomposing P content of an individual into physiological components of P kinetics will improve stoichiometric models. More generally, attention to the interplay between nutrient content and nutrient-use is required to make inferences regarding the success of genotypes in defined conditions of nutrient supply. PMID:29308224

Upper Limits of Predictability in Long-Range Climate/Hydrologic Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Suarez, M. J.; Heiser, M.

1998-01-01

The accurate forecasting of el nino or la nina conditions in the tropical Pacific can potentially lead to valuable predictions of hydrological anomalies over land at seasonal to interannual timescales. Even with highly accurate earth system models, though, our ability to generate these continental forecasts will always be limited by the chaotic nature of the atmospheric circulation. The nature of this fundamental limitation is explored through the use of 16-member ensembles of multi-decade GCM simulations. In each simulation of the first ensemble, sea surface temperatures (SSTs) are given the same realistic interannual variations over a 45-year period, and land surface state is allowed to evolve with that of the atmosphere. Analysis of the results shows that the SSTs control the temporal organization of continental precipitation anomalies to a significant extent in the tropics and to a much smaller extent in midlatitudes. In each simulation of the second ensemble, we prescribe SSTs as before, but we also prescribe interannual variations in the low frequency component of evaporation efficiency over land. Thus, in the second ensemble, we effectively make the extreme assumption that surface boundary conditions across the globe are perfectly predictable, and we quantify the consistency with which the atmosphere (particularly precipitation) responds to these boundary conditions. The resulting "absolute upper limit" on the predictability of precipitation is found to be quite high in the tropics yet only moderate in many midlatitude regions.

Using the satellite-derived NDVI to assess ecological responses to environmental change.

PubMed

Pettorelli, Nathalie; Vik, Jon Olav; Mysterud, Atle; Gaillard, Jean-Michel; Tucker, Compton J; Stenseth, Nils Chr

2005-09-01

Assessing how environmental changes affect the distribution and dynamics of vegetation and animal populations is becoming increasingly important for terrestrial ecologists to enable better predictions of the effects of global warming, biodiversity reduction or habitat degradation. The ability to predict ecological responses has often been hampered by our rather limited understanding of trophic interactions. Indeed, it has proven difficult to discern direct and indirect effects of environmental change on animal populations owing to limited information about vegetation at large temporal and spatial scales. The rapidly increasing use of the Normalized Difference Vegetation Index (NDVI) in ecological studies has recently changed this situation. Here, we review the use of the NDVI in recent ecological studies and outline its possible key role in future research of environmental change in an ecosystem context.

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.

Plant functional traits in relation to fire in crown-fire ecosystems

USGS Publications Warehouse

Pausas, Juli G.; Bradstock, Ross A.; Keith, David A.; Keeley, Jon E.

2004-01-01

Disturbance is a dominant factor in many ecosystems, and the disturbance regime is likely to change over the next decades in response to land-use changes and global warming. We assume that predictions of vegetation dynamics can be made on the basis of a set of life-history traits that characterize the response of a species to disturbance. For crown-fire ecosystems, the main plant traits related to postfire persistence are the ability to resprout (persistence of individuals) and the ability to retain a persistent seed bank (persistence of populations). In this context, we asked (1) to what extent do different life-history traits co-occur with the ability to resprout and/or the ability to retain a persistent seed bank among differing ecosystems and (2) to what extent do combinations of fire-related traits (fire syndromes) change in a fire regime gradient? We explored these questions by reviewing the literature and analyzing databases compiled from different crown-fire ecosystems (mainly eastern Australia, California, and the Mediterranean basin). The review suggests that the pattern of correlation between the two basic postfire persistent traits and other plant traits varies between continents and ecosystems. From these results we predict, for instance, that not all resprouters respond in a similar way everywhere because the associated plant traits of resprouter species vary in different places. Thus, attempts to generalize predictions on the basis of the resprouting capacity may have limited power at a global scale. An example is presented for Australian heathlands. Considering the combination of persistence at individual (resprouting) and at population (seed bank) level, the predictive power at local scale was significantly increased.

Search, Memory, and Choice Error: An Experiment

PubMed Central

Sanjurjo, Adam

2015-01-01

Multiple attribute search is a central feature of economic life: we consider much more than price when purchasing a home, and more than wage when choosing a job. An experiment is conducted in order to explore the effects of cognitive limitations on choice in these rich settings, in accordance with the predictions of a new model of search memory load. In each task, subjects are made to search the same information in one of two orders, which differ in predicted memory load. Despite standard models of choice treating such variations in order of acquisition as irrelevant, lower predicted memory load search orders are found to lead to substantially fewer choice errors. An implication of the result for search behavior, more generally, is that in order to reduce memory load (thus choice error) a limited memory searcher ought to deviate from the search path of an unlimited memory searcher in predictable ways-a mechanism that can explain the systematic deviations from optimal sequential search that have recently been discovered in peoples' behavior. Further, as cognitive load is induced endogenously (within the task), and found to affect choice behavior, this result contributes to the cognitive load literature (in which load is induced exogenously), as well as the cognitive ability literature (in which cognitive ability is measured in a separate task). In addition, while the information overload literature has focused on the detrimental effects of the quantity of information on choice, this result suggests that, holding quantity constant, the order that information is observed in is an essential determinant of choice failure. PMID:26121356

Face emotion recognition is related to individual differences in psychosis-proneness.

PubMed

Germine, L T; Hooker, C I

2011-05-01

Deficits in face emotion recognition (FER) in schizophrenia are well documented, and have been proposed as a potential intermediate phenotype for schizophrenia liability. However, research on the relationship between psychosis vulnerability and FER has mixed findings and methodological limitations. Moreover, no study has yet characterized the relationship between FER ability and level of psychosis-proneness. If FER ability varies continuously with psychosis-proneness, this suggests a relationship between FER and polygenic risk factors. We tested two large internet samples to see whether psychometric psychosis-proneness, as measured by the Schizotypal Personality Questionnaire-Brief (SPQ-B), is related to differences in face emotion identification and discrimination or other face processing abilities. Experiment 1 (n=2332) showed that psychosis-proneness predicts face emotion identification ability but not face gender identification ability. Experiment 2 (n=1514) demonstrated that psychosis-proneness also predicts performance on face emotion but not face identity discrimination. The tasks in Experiment 2 used identical stimuli and task parameters, differing only in emotion/identity judgment. Notably, the relationships demonstrated in Experiments 1 and 2 persisted even when individuals with the highest psychosis-proneness levels (the putative high-risk group) were excluded from analysis. Our data suggest that FER ability is related to individual differences in psychosis-like characteristics in the normal population, and that these differences cannot be accounted for by differences in face processing and/or visual perception. Our results suggest that FER may provide a useful candidate intermediate phenotype.

Numerical ability predicts mortgage default

PubMed Central

Gerardi, Kristopher; Goette, Lorenz; Meier, Stephan

2013-01-01

Unprecedented levels of US subprime mortgage defaults precipitated a severe global financial crisis in late 2008, plunging much of the industrialized world into a deep recession. However, the fundamental reasons for why US mortgages defaulted at such spectacular rates remain largely unknown. This paper presents empirical evidence showing that the ability to perform basic mathematical calculations is negatively associated with the propensity to default on one’s mortgage. We measure several aspects of financial literacy and cognitive ability in a survey of subprime mortgage borrowers who took out loans in 2006 and 2007, and match them to objective, detailed administrative data on mortgage characteristics and payment histories. The relationship between numerical ability and mortgage default is robust to controlling for a broad set of sociodemographic variables, and is not driven by other aspects of cognitive ability. We find no support for the hypothesis that numerical ability impacts mortgage outcomes through the choice of the mortgage contract. Rather, our results suggest that individuals with limited numerical ability default on their mortgage due to behavior unrelated to the initial choice of their mortgage. PMID:23798401

Numerical ability predicts mortgage default.

PubMed

Gerardi, Kristopher; Goette, Lorenz; Meier, Stephan

2013-07-09

Unprecedented levels of US subprime mortgage defaults precipitated a severe global financial crisis in late 2008, plunging much of the industrialized world into a deep recession. However, the fundamental reasons for why US mortgages defaulted at such spectacular rates remain largely unknown. This paper presents empirical evidence showing that the ability to perform basic mathematical calculations is negatively associated with the propensity to default on one's mortgage. We measure several aspects of financial literacy and cognitive ability in a survey of subprime mortgage borrowers who took out loans in 2006 and 2007, and match them to objective, detailed administrative data on mortgage characteristics and payment histories. The relationship between numerical ability and mortgage default is robust to controlling for a broad set of sociodemographic variables, and is not driven by other aspects of cognitive ability. We find no support for the hypothesis that numerical ability impacts mortgage outcomes through the choice of the mortgage contract. Rather, our results suggest that individuals with limited numerical ability default on their mortgage due to behavior unrelated to the initial choice of their mortgage.

Assessment of wastewater treatment facility compliance with decreasing ammonia discharge limits using a regression tree model.

PubMed

Suchetana, Bihu; Rajagopalan, Balaji; Silverstein, JoAnn

2017-11-15

A regression tree-based diagnostic approach is developed to evaluate factors affecting US wastewater treatment plant compliance with ammonia discharge permit limits using Discharge Monthly Report (DMR) data from a sample of 106 municipal treatment plants for the period of 2004-2008. Predictor variables used to fit the regression tree are selected using random forests, and consist of the previous month's effluent ammonia, influent flow rates and plant capacity utilization. The tree models are first used to evaluate compliance with existing ammonia discharge standards at each facility and then applied assuming more stringent discharge limits, under consideration in many states. The model predicts that the ability to meet both current and future limits depends primarily on the previous month's treatment performance. With more stringent discharge limits predicted ammonia concentration relative to the discharge limit, increases. In-sample validation shows that the regression trees can provide a median classification accuracy of >70%. The regression tree model is validated using ammonia discharge data from an operating wastewater treatment plant and is able to accurately predict the observed ammonia discharge category approximately 80% of the time, indicating that the regression tree model can be applied to predict compliance for individual treatment plants providing practical guidance for utilities and regulators with an interest in controlling ammonia discharges. The proposed methodology is also used to demonstrate how to delineate reliable sources of demand and supply in a point source-to-point source nutrient credit trading scheme, as well as how planners and decision makers can set reasonable discharge limits in future. Copyright © 2017 Elsevier B.V. All rights reserved.

Seasonal Patterns of Nitrogen and Phosphorus Limitation in Four German Lakes and the Predictability of Limitation Status from Ambient Nutrient Concentrations

PubMed Central

Kolzau, Sebastian; Wiedner, Claudia; Rücker, Jacqueline; Köhler, Jan; Köhler, Antje; Dolman, Andrew M.

2014-01-01

To identify the seasonal pattern of nitrogen (N) and phosphorus (P) limitation of phytoplankton in four different lakes, biweekly experiments were conducted from the end of March to September 2011. Lake water samples were enriched with N, P or both nutrients and incubated under two different light intensities. Chlorophyll a fluorescence (Chla) was measured and a model selection procedure was used to assign bioassay outcomes to different limitation categories. N and P were both limiting at some point. For the shallow lakes there was a trend from P limitation in spring to N or light limitation later in the year, while the deep lake remained predominantly P limited. To determine the ability of in-lake N:P ratios to predict the relative strength of N vs. P limitation, three separate regression models were fit with the log-transformed ratio of Chla of the P and N treatments (Response ratio = RR) as the response variable and those of ambient total phosphorus:total nitrogen (TN:TP), dissolved inorganic nitrogen:soluble reactive phosphorus (DIN:SRP), TN:SRP and DIN:TP mass ratios as predictors. All four N:P ratios had significant positive relationships with RR, such that high N:P ratios were associated with P limitation and low N:P ratios with N limitation. The TN:TP and DIN:TP ratios performed better than the DIN:SRP and TN:SRP in terms of misclassification rate and the DIN:TP ratio had the highest R2 value. Nitrogen limitation was predictable, frequent and persistent, suggesting that nitrogen reduction could play a role in water quality management. However, there is still uncertainty about the efficacy of N restriction to control populations of N2 fixing cyanobacteria. PMID:24755935

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.

Adaptive envelope protection methods for aircraft

NASA Astrophysics Data System (ADS)

Unnikrishnan, Suraj

Carefree handling refers to the ability of a pilot to operate an aircraft without the need to continuously monitor aircraft operating limits. At the heart of all carefree handling or maneuvering systems, also referred to as envelope protection systems, are algorithms and methods for predicting future limit violations. Recently, envelope protection methods that have gained more acceptance, translate limit proximity information to its equivalent in the control channel. Envelope protection algorithms either use very small prediction horizon or are static methods with no capability to adapt to changes in system configurations. Adaptive approaches maximizing prediction horizon such as dynamic trim, are only applicable to steady-state-response critical limit parameters. In this thesis, a new adaptive envelope protection method is developed that is applicable to steady-state and transient response critical limit parameters. The approach is based upon devising the most aggressive optimal control profile to the limit boundary and using it to compute control limits. Pilot-in-the-loop evaluations of the proposed approach are conducted at the Georgia Tech Carefree Maneuver lab for transient longitudinal hub moment limit protection. Carefree maneuvering is the dual of carefree handling in the realm of autonomous Uninhabited Aerial Vehicles (UAVs). Designing a flight control system to fully and effectively utilize the operational flight envelope is very difficult. With the increasing role and demands for extreme maneuverability there is a need for developing envelope protection methods for autonomous UAVs. In this thesis, a full-authority automatic envelope protection method is proposed for limit protection in UAVs. The approach uses adaptive estimate of limit parameter dynamics and finite-time horizon predictions to detect impending limit boundary violations. Limit violations are prevented by treating the limit boundary as an obstacle and by correcting nominal control/command inputs to track a limit parameter safe-response profile near the limit boundary. The method is evaluated using software-in-the-loop and flight evaluations on the Georgia Tech unmanned rotorcraft platform---GTMax. The thesis also develops and evaluates an extension for calculating control margins based on restricting limit parameter response aggressiveness near the limit boundary.

Prediction complements explanation in understanding the developing brain.

PubMed

Rosenberg, Monica D; Casey, B J; Holmes, Avram J

2018-02-21

A central aim of human neuroscience is understanding the neurobiology of cognition and behavior. Although we have made significant progress towards this goal, reliance on group-level studies of the developed adult brain has limited our ability to explain population variability and developmental changes in neural circuitry and behavior. In this review, we suggest that predictive modeling, a method for predicting individual differences in behavior from brain features, can complement descriptive approaches and provide new ways to account for this variability. Highlighting the outsized scientific and clinical benefits of prediction in developmental populations including adolescence, we show that predictive brain-based models are already providing new insights on adolescent-specific risk-related behaviors. Together with large-scale developmental neuroimaging datasets and complementary analytic approaches, predictive modeling affords us the opportunity and obligation to identify novel treatment targets and individually tailor the course of interventions for developmental psychopathologies that impact so many young people today.

The effects of changing climate on faunal depth distributions determine winners and losers.

PubMed

Brown, Alastair; Thatje, Sven

2015-01-01

Changing climate is predicted to impact all depths of the global oceans, yet projections of range shifts in marine faunal distributions in response to changing climate seldom evaluate potential shifts in depth distribution. Marine ectotherms' thermal tolerance is limited by their ability to maintain aerobic metabolism (oxygen- and capacity-limited tolerance), and is functionally associated with their hypoxia tolerance. Shallow-water (<200 m depth) marine invertebrates and fishes demonstrate limited tolerance of increasing hydrostatic pressure (pressure exerted by the overlying mass of water), and hyperbaric (increased pressure) tolerance is proposed to depend on the ability to maintain aerobic metabolism, too. Here, we report significant correlation between the hypoxia thresholds and the hyperbaric thresholds of taxonomic groups of shallow-water fauna, suggesting that pressure tolerance is indeed oxygen limited. Consequently, it appears that the combined effects of temperature, pressure and oxygen concentration constrain the fundamental ecological niches (FENs) of marine invertebrates and fishes. Including depth in a conceptual model of oxygen- and capacity-limited FENs' responses to ocean warming and deoxygenation confirms previous predictions made based solely on consideration of the latitudinal effects of ocean warming (e.g. Cheung et al., 2009), that polar taxa are most vulnerable to the effects of climate change, with Arctic fauna experiencing the greatest FEN contraction. In contrast, the inclusion of depth in the conceptual model reveals for the first time that temperate fauna as well as tropical fauna may experience substantial FEN expansion with ocean warming and deoxygenation, rather than FEN maintenance or contraction suggested by solely considering latitudinal range shifts. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Resource limitation and responses to rivals in males of the fruit fly Drosophila melanogaster.

PubMed

Mason, J S; Rostant, W G; Chapman, T

2016-10-01

Diet has a profound direct and indirect effect on reproductive success in both sexes. Variation in diet quality and quantity can significantly alter the capacity of females to lay eggs and of males to deliver courtship. Here, we tested the effect of dietary resource limitation on the ability of male Drosophila melanogaster to respond adaptively to rivals by extending their mating duration. Previous work carried out under ad libitum diet conditions showed that males exposed to rivals prior to mating significantly extend mating duration, transfer more ejaculate proteins and achieve higher reproductive success. Such adaptive responses are predicted to occur because male ejaculate production may be limited. Hence, ejaculate resources require allocation across different reproductive bouts, to balance current vs. future reproductive success. However, when males suffer dietary limitation, and potentially have fewer reproductive resources to apportion, we expect adaptive allocation of responses to rivals to be minimized. We tested this prediction and found that males held on agar-only diets for 5-7 days lost the ability to extend mating following exposure to rivals. Interestingly, extended mating was retained in males held on low yeast/sugar: no sugar/yeast diet treatments, but was mostly lost when males were maintained on 'imbalanced' diets in which there was high yeast: no sugar and vice versa. Overall, the results show that males exhibit adaptive responses to rivals according to the degree of dietary resource limitation and to the ratio of individual diet components. © 2016 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia.

PubMed

Clennon, Julie A; Kamanga, Aniset; Musapa, Mulenga; Shiff, Clive; Glass, Gregory E

2010-11-05

Malaria, caused by the parasite Plasmodium falciparum, is a significant source of morbidity and mortality in southern Zambia. In the Mapanza Chiefdom, where transmission is seasonal, Anopheles arabiensis is the dominant malaria vector. The ability to predict larval habitats can help focus control measures. A survey was conducted in March-April 2007, at the end of the rainy season, to identify and map locations of water pooling and the occurrence anopheline larval habitats; this was repeated in October 2007 at the end of the dry season and in March-April 2008 during the next rainy season. Logistic regression and generalized linear mixed modeling were applied to assess the predictive value of terrain-based landscape indices along with LandSat imagery to identify aquatic habitats and, especially, those with anopheline mosquito larvae. Approximately two hundred aquatic habitat sites were identified with 69 percent positive for anopheline mosquitoes. Nine species of anopheline mosquitoes were identified, of which, 19% were An. arabiensis. Terrain-based landscape indices combined with LandSat predicted sites with water, sites with anopheline mosquitoes and sites specifically with An. arabiensis. These models were especially successful at ruling out potential locations, but had limited ability in predicting which anopheline species inhabited aquatic sites. Terrain indices derived from 90 meter Shuttle Radar Topography Mission (SRTM) digital elevation data (DEM) were better at predicting water drainage patterns and characterizing the landscape than those derived from 30 m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM. The low number of aquatic habitats available and the ability to locate the limited number of aquatic habitat locations for surveillance, especially those containing anopheline larvae, suggest that larval control maybe a cost-effective control measure in the fight against malaria in Zambia and other regions with seasonal transmission. This work shows that, in areas of seasonal malaria transmission, incorporating terrain-based landscape models to the planning stages of vector control allows for the exclusion of significant portions of landscape that would be unsuitable for water to accumulate and for mosquito larvae occupation. With increasing free availability of satellite imagery such as SRTM and LandSat, the development of satellite imagery-based prediction models is becoming more accessible to vector management coordinators.

Incremental Validity of Useful Field of View Subtests for the Prediction of Instrumental Activities of Daily Living

PubMed Central

Aust, Frederik; Edwards, Jerri D.

2015-01-01

Introduction The Useful Field of View Test (UFOV®) is a cognitive measure that predicts older adults’ ability to perform a range of everyday activities. However, little is known about the individual contribution of each subtest to these predictions and the underlying constructs of UFOV performance remain a topic of debate. Method We investigated the incremental validity of UFOV subtests for the prediction of Instrumental Activities of Daily Living (IADL) performance in two independent datasets, the SKILL (n = 828) and ACTIVE (n = 2426) studies. We, then, explored the cognitive and visual abilities assessed by UFOV using a range of neuropsychological and vision tests administered in the SKILL study. Results In the four subtest variant of UFOV, only subtests 2 and 3 consistently made independent contributions to the prediction of IADL performance across three different behavioral measures. In all cases, the incremental validity of UFOV subtests 1 and 4 was negligible. Furthermore, we found that UFOV was related to processing speed, general non-speeded cognition, and visual function; the omission of subtests 1 and 4 from the test score did not affect these associations. Conclusions UFOV subtests 1 and 4 appear to be of limited use to predict IADL and possibly other everyday activities. Future experimental research should investigate if shortening the UFOV by omitting these subtests is a reliable and valid assessment approach. PMID:26782018

Can the everyday technology use questionnaire predict overall functional level among older adults with mild cognitive impairment or mild-stage alzheimer's disease? - a pilot study.

PubMed

Ryd, Charlotta; Nygård, Louise; Malinowsky, Camilla; Öhman, Annika; Kottorp, Anders

2017-03-01

The number of older adults living with mild cognitive impairment (MCI) or mild-stage Alzheimer's disease (AD) is increasing and they are often expected to live in their own homes without support, despite limited ability to perform daily life activities. The Everyday Technology Use Questionnaire (ETUQ) has proven to be able to separate these groups and might also have potential to predict overall functional level (need of assistance in daily life activities) among them. To investigate whether the ETUQ can predict overall functional level among older adults with MCI or mild-stage AD. Participants were older adults with a mean age of 76 years with MCI (n = 28) or mild-stage AD (n = 39). A three-step scale indicating (i) independence, (ii) need for minimal assistance or (iii) need for moderate to maximal assistance in daily life was dichotomised in two ways and used as outcome variables in two logistic regression models. Predictors in both models were perceived ability to use everyday technology (ET) and amount of relevant everyday technologies measured by the ETUQ. Ethical approval was obtained from the regional Ethical Committee. Perceived ability to use ET discriminated individuals who were independent or in need of minimal support from those in need of moderate to maximal assistance (OR = 1.82, p < 0.01, confidence interval = 95%; 1.76-2.82). The amount of relevant everyday technologies discriminated individuals who were independent from those in need of assistance at any level (OR = 1.39; p < 0.01; confidence interval = 95%; 1.11-1.75). Both perceived ability to use ET and amount of relevant everyday technologies had potential to predict overall function but at different levels. The findings support the predictive validity of the ETUQ and suggest further research for the development of clinical cut-off criteria. © 2016 Nordic College of Caring Science.

Computational investigation of noble gas adsorption and separation by nanoporous materials.

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

Allendorf, Mark D.; Sanders, Joseph C.; Greathouse, Jeffery A.

2008-10-01

Molecular simulations are used to assess the ability of metal-organic framework (MOF) materials to store and separate noble gases. Specifically, grand canonical Monte Carlo simulation techniques are used to predict noble gas adsorption isotherms at room temperature. Experimental trends of noble gas inflation curves of a Zn-based material (IRMOF-1) are matched by the simulation results. The simulations also predict that IRMOF-1 selectively adsorbs Xe atoms in Xe/Kr and Xe/Ar mixtures at total feed gas pressures of 1 bar (14.7 psia) and 10 bar (147 psia). Finally, simulations of a copper-based MOF (Cu-BTC) predict this material's ability to selectively adsorb Xemore » and Kr atoms when present in trace amounts in atmospheric air samples. These preliminary results suggest that Cu-BTC may be an ideal candidate for the pre-concentration of noble gases from air samples. Additional simulations and experiments are needed to determine the saturation limit of Cu-BTC for xenon, and whether any krypton atoms would remain in the Cu-BTC pores upon saturation.« less

Does the KABC-II Display Ethnic Bias in the Prediction of Reading, Math, and Writing in Elementary School Through High School?

PubMed

Scheiber, Caroline

2017-09-01

This study explored whether the Kaufman Assessment Battery for Children-Second Edition (KABC-II) predicted academic achievement outcomes of the Kaufman Test of Educational Achievement-Second Edition (KTEA-II) equally well across a representative sample of African American, Hispanic, and Caucasian school-aged children ( N = 2,001) in three grade groups (1-4, 5-8, 9-12). It was of interest to study possible prediction bias in the slope and intercept of the five underlying Cattell-Horn-Carroll (CHC) cognitive factors of the KABC-II-Sequential/Gsm (Short-Term Memory), Learning/Glr (Long-Term Storage and Retrieval), Simultaneous/Gv (Visual Processing), Planning/Gf (Fluid Reasoning), and Knowledge/Gc (Crystallized Ability)-in estimating reading, writing, and math. Structural equation modeling techniques demonstrated a lack of bias in the slopes; however, four of the five CHC indexes showed a persistent overprediction of the minority groups' achievement in the intercept. The overprediction is likely attributable to institutional or societal contributions, which limit the students' ability to achieve to their fullest potential.

Analytic cognitive style predicts paranormal explanations of anomalous experiences but not the experiences themselves: Implications for cognitive theories of delusions.

PubMed

Ross, Robert M; Hartig, Bjoern; McKay, Ryan

2017-09-01

It has been proposed that delusional beliefs are attempts to explain anomalous experiences. Why, then, do anomalous experiences induce delusions in some people but not in others? One possibility is that people with delusions have reasoning biases that result in them failing to reject implausible candidate explanations for anomalous experiences. We examine this hypothesis by studying paranormal interpretations of anomalous experiences. We examined whether analytic cognitive style (i.e. the willingness or disposition to critically evaluate outputs from intuitive processing and engage in effortful analytic processing) predicted anomalous experiences and paranormal explanations for these experiences after controlling for demographic variables and cognitive ability. Analytic cognitive style predicted paranormal explanations for anomalous experiences, but not the anomalous experiences themselves. We did not study clinical delusions. Our attempts to control for cognitive ability may have been inadequate. Our sample was predominantly students. Limited analytic cognitive style might contribute to the interpretation of anomalous experiences in terms of delusional beliefs. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns.

PubMed

Kumkale, G Tarcan; Albarracín, Dolores; Seignourel, Paul J

2010-06-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed.

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns1

PubMed Central

Kumkale, G. Tarcan; AlbarracÍn, Dolores; Seignourel, Paul J.

2011-01-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed. PMID:21625405

Safe Operation of Mobile Unmanned Ground Vehicle (UGV) Systems

DTIC Science & Technology

2010-07-13

vehicle could go during uncommanded movement and full throttle acceleration. 4. TEST PROCEDURES. 4.1 Vehicle Subsystem Tests. These tests identify...time required to go from straight ahead to full deflection in one direction. (sec) i. Observations on ability of the remote operator to maintain...were well below the lateral acceleration limits of the vehicle resulting in very predictable handling traits. The primary concern , albeit subjective

Predicting the potential future distribution of four tree species in Ohio using current habitat availability and climatic forcing

Treesearch

Mark W. Schwartz; Louis R. Iverson; Anantha M. Prasad; Anantha M. Prasad

2000-01-01

We investigated the effect of habitat loss on the ability of trees to shift in distribution across a landscape dominated by agriculture. The potential distribution shifts of four tree species (Diospyros virginiana, Oxydendron arboreum, Pinus virginiana, Quercus falcata var. falcata) whose northern distribution limits fall in the southern third of Ohio were used to...

Contemporary Tectonics of China

DTIC Science & Technology

1978-02-01

that it would be of value to the United States to understand seismicity in China because their methods used in predicting large intraplate seismic...ability to discriminate between natural events and nuclear explosions. General Method In order to circumvent the limitations placed on studies of...accurate relative locations. Fault planes maybe determined with this method , thereby removing the ambiguity of the choice of fault plane from a fault plane

Persistence of soil organic matter as an ecosystem property.

PubMed

Schmidt, Michael W I; Torn, Margaret S; Abiven, Samuel; Dittmar, Thorsten; Guggenberger, Georg; Janssens, Ivan A; Kleber, Markus; Kögel-Knabner, Ingrid; Lehmann, Johannes; Manning, David A C; Nannipieri, Paolo; Rasse, Daniel P; Weiner, Steve; Trumbore, Susan E

2011-10-05

Globally, soil organic matter (SOM) contains more than three times as much carbon as either the atmosphere or terrestrial vegetation. Yet it remains largely unknown why some SOM persists for millennia whereas other SOM decomposes readily--and this limits our ability to predict how soils will respond to climate change. Recent analytical and experimental advances have demonstrated that molecular structure alone does not control SOM stability: in fact, environmental and biological controls predominate. Here we propose ways to include this understanding in a new generation of experiments and soil carbon models, thereby improving predictions of the SOM response to global warming.

Persistence of soil organic matter as an ecosystem property

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

Schmidt, M.W.; Torn, M. S.; Abiven, S.

2011-08-15

Globally, soil organic matter (SOM) contains more than three times as much carbon as either the atmosphere or terrestrial vegetation. Yet it remains largely unknown why some SOM persists for millennia whereas other SOM decomposes readily—and this limits our ability to predict how soils will respond to climate change. Recent analytical and experimental advances have demonstrated that molecular structure alone does not control SOM stability: in fact, environmental and biological controls predominate. Here we propose ways to include this understanding in a new generation of experiments and soil carbon models, thereby improving predictions of the SOM response to global warming.

Numerical modeling of consolidation processes in hydraulically deposited soils

NASA Astrophysics Data System (ADS)

Brink, Nicholas Robert

Hydraulically deposited soils are encountered in many common engineering applications including mine tailing and geotextile tube fills, though the consolidation process for such soils is highly nonlinear and requires the use of advanced numerical techniques to provide accurate predictions. Several commercially available finite element codes poses the ability to model soil consolidation, and it was the goal of this research to assess the ability of two of these codes, ABAQUS and PLAXIS, to model the large-strain, two-dimensional consolidation processes which occur in hydraulically deposited soils. A series of one- and two-dimensionally drained rectangular models were first created to assess the limitations of ABAQUS and PLAXIS when modeling consolidation of highly compressible soils. Then, geotextile tube and TSF models were created to represent actual scenarios which might be encountered in engineering practice. Several limitations were discovered, including the existence of a minimum preconsolidation stress below which numerical solutions become unstable.

The mathematical limits of genetic prediction for complex chronic disease.

PubMed

Keyes, Katherine M; Smith, George Davey; Koenen, Karestan C; Galea, Sandro

2015-06-01

Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Forecasting Western U.S. Snowpack

NASA Astrophysics Data System (ADS)

Kapnick, S. B.; Yang, X.; Vecchi, G. A.; Delworth, T. L.; Gudgel, R.; Malyshev, S.; Milly, C.; Shevliakova, E.; Underwood, S.; Margulis, S. A.

2017-12-01

Cold season mountain snow accumulation in the western United States plays a critical role in regional hydroclimate and water supply. While climate projections provide estimates of future snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions and hazards out to two weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), particularly beyond 6 months. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate our dynamical system's feasibility of seasonal snowpack predictions and quantify the limits of predictive skill more than 2 seasons in advance for snowpack—snow that accumulates on the ground in the mountains. Our ability to predict snowpack is reliant on both temperature and precipitation prediction skill modulating both the amount of frozen precipitation that falls and how much snow accumulates and stays on the ground throughout the season. We will quantify prediction skill and outline areas necessary for the future advancement of seasonal hydroclimate prediction.

A model for autumn pelagic distribution of adult female polar bears in the Chukchi Seas, 1987-1994

USGS Publications Warehouse

Durner, George M.; Douglas, David C.; Nielson, R.M.; Amstrup, Steven C.

2006-01-01

We made predictions of polar bear (Ursus maritimus) autumn distribution in the Chukchi Sea with a Resource Selection Function (RSF) developed from 1198 satellite radio-collar locations on 124 adult female polar bears, 1987 – 1994. The RSF was created to assist in an aerial survey design for polar bears proposed by the U.S. Fish and Wildlife Service. The RSF was based on bathymetry and daily sea ice covariates extracted from passive microwave satellite imagery within the pelagic region > 25 km from shore. The RSF indicated that polar bears selected habitats with intermediate amounts (~50%) of ice cover in close proximity to higher ice concentrations, and over relatively shallow waters. The RSF showed good predictive abilities for the years of its construct, worked best in October, and was robust to inter-annual variability. When evaluated with recent (1997 – 2005) data, the RSF performed well for October and November but poorly in September. This loss of predictive abilities appeared to be related to recent changes in habitat due to longer melt seasons and younger sea ice, and testing the retrospective model with a small sample of recent polar bears locations from a limited region of the Chukchi Sea. Contemporary applications of this RSF must consider three factors that could limit its utility: 1) 2 different sea ice phenology; 2) distributions of males and sub-adults; and 3) occupancy in nearshore habitats.

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.

Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face

PubMed Central

Engel, David; Woolley, Anita Williams; Jing, Lisa X.; Chabris, Christopher F.; Malone, Thomas W.

2014-01-01

Recent research with face-to-face groups found that a measure of general group effectiveness (called “collective intelligence”) predicted a group’s performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members’ ability to reason about the mental states of others (an ability called “Theory of Mind” or “ToM”). Since ToM was measured in this work by a test that requires participants to “read” the mental states of others from looking at their eyes (the “Reading the Mind in the Eyes” test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available. Here we find that: (1) a collective intelligence factor characterizes group performance approximately as well for online groups as for face-to-face groups; and (2) surprisingly, the ToM measure is equally predictive of collective intelligence in both face-to-face and online groups, even though the online groups communicate only via text and never see each other at all. This provides strong evidence that ToM abilities are just as important to group performance in online environments with limited nonverbal cues as they are face-to-face. It also suggests that the Reading the Mind in the Eyes test measures a deeper, domain-independent aspect of social reasoning, not merely the ability to recognize facial expressions of mental states. PMID:25514387

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.

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.

On Spatially Explicit Models of Epidemic and Endemic Cholera: The Haiti and Lake Kivu Case Studies.

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Finger, F.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.

2014-12-01

The first part of the Lecture deals with the predictive ability of mechanistic models for the Haitian cholera epidemic. Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. A formal model comparison framework provides a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels. Intensive computations and objective model comparisons show that parsimonious spatially explicit models accounting for spatial connections have superior explanatory power than spatially disconnected ones for short-to intermediate calibration windows. In general, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. The second part deals with approaches suitable to describe patterns of endemic cholera. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of lake Kivu. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multi-year dataset of reported cholera cases. Fourteen models, accounting for different environmental drivers, are selected in calibration. Among these, the one accounting for seasonality, El Nino Southern Oscillation, precipitation and human mobility outperforms the others in cross-validation.

Social network models predict movement and connectivity in ecological landscapes

USGS Publications Warehouse

Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients.

PubMed

Nayak, N M; Madhumitha, S; Annigeri, R A; Venkataraman, R; Balasubramaian, S; Seshadri, R; Vadamalai, V; Rao, B S; Kowdle, P C; Ramakrishnan, N; Mani, M K

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39-19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients

PubMed Central

Nayak, N. M.; Madhumitha, S.; Annigeri, R. A.; Venkataraman, R.; Balasubramaian, S.; Seshadri, R.; Vadamalai, V.; Rao, B. S.; Kowdle, P. C.; Ramakrishnan, N.; Mani, M. K.

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39–19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality. PMID:27051136

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/.

Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Cao, Jin; Jiang, Zhibin; Wang, Kangzhou

2017-07-01

Many nonlinear customer satisfaction-related factors significantly influence the future customer demand for service-oriented manufacturing (SOM). To address this issue and enhance the prediction accuracy, this article develops a novel customer demand prediction approach for SOM. The approach combines the phase space reconstruction (PSR) technique with the optimized least square support vector machine (LSSVM). First, the prediction sample space is reconstructed by the PSR to enrich the time-series dynamics of the limited data sample. Then, the generalization and learning ability of the LSSVM are improved by the hybrid polynomial and radial basis function kernel. Finally, the key parameters of the LSSVM are optimized by the particle swarm optimization algorithm. In a real case study, the customer demand prediction of an air conditioner compressor is implemented. Furthermore, the effectiveness and validity of the proposed approach are demonstrated by comparison with other classical predication approaches.

A phenomenological model for systematization and prediction of doping limits in II{endash}VI and I{endash}III{endash}VI{sub 2} compounds

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

Zhang, S.B.; Wei, S.; Zunger, A.

1998-03-01

Semiconductors differ widely in their ability to be doped. As their band gap increases, it is usually possible to dope them either n or p type, but not both. This asymmetry is documented here, and explained phenomenologically in terms of the {open_quotes}doping pinning rule.{close_quotes} {copyright} {ital 1998 American Institute of Physics.}

Genomic Prediction of Single Crosses in the Early Stages of a Maize Hybrid Breeding Pipeline.

PubMed

Kadam, Dnyaneshwar C; Potts, Sarah M; Bohn, Martin O; Lipka, Alexander E; Lorenz, Aaron J

2016-09-19

Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk Synthetic/Non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to re-design hybrid breeding and increase its efficiency. Copyright © 2016 Author et al.

Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling

NASA Astrophysics Data System (ADS)

Bond, Nick R.; Kennard, Mark J.

2017-11-01

Hydrologic variability is a fundamental driver of ecological processes and species distribution patterns within river systems, yet the paucity of gauges in many catchments means that streamflow data are often unavailable for ecological survey sites. Filling this data gap is an important challenge in hydroecological research. To address this gap, we first test the ability to spatially extrapolate hydrologic metrics calculated from gauged streamflow data to ungauged sites as a function of stream distance and catchment area. Second, we examine the ability of statistical models to predict flow regime metrics based on climate and catchment physiographic variables. Our assessment focused on Australia's largest catchment, the Murray-Darling Basin (MDB). We found that hydrologic metrics were predictable only between sites within ˜25 km of one another. Beyond this, correlations between sites declined quickly. We found less than 40% of fish survey sites from a recent basin-wide monitoring program (n = 777 sites) to fall within this 25 km range, thereby greatly limiting the ability to utilize gauge data for direct spatial transposition of hydrologic metrics to biological survey sites. In contrast, statistical model-based transposition proved effective in predicting ecologically relevant aspects of the flow regime (including metrics describing central tendency, high- and low-flows intermittency, seasonality, and variability) across the entire gauge network (median R2 ˜ 0.54, range 0.39-0.94). Modeled hydrologic metrics thus offer a useful alternative to empirical data when examining biological survey data from ungauged sites. More widespread use of these statistical tools and modeled metrics could expand our understanding of flow-ecology relationships.

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

How do temperate bryophytes face the challenge of a changing environment? Lessons from the past and predictions for the future.

PubMed

Désamoré, Aurélie; Laenen, Benjamin; Stech, Michael; Papp, Beata; Hedenäs, Lars; Mateo, Ruben G; Vanderpoorten, Alain

2012-09-01

Bryophytes are a group of early land plants, whose specific ecophysiological and biological features, including poikilohydry, sensitivity to moderately high temperature and high dispersal ability, make them ideal candidates for investigating the impact of climate changes. Employing a combined approach of species distribution modelling (SDM) and molecular phylogeography in the temperate moss Homalothecium sericeum, we explore the significance of the Mediterranean refugia, contrasting the southern and northern refugia hypotheses, determine the extent to which recolonization of previously glaciated areas has been facilitated by the high dispersal ability of the species and make predictions on the extent to which it will be impacted by ongoing climate change. The Mediterranean areas exhibit the highest nucleotidic diversities and host a mixture of ancestral, endemic and more recently derived haplotypes. Extra-Mediterranean areas exhibit low genetic diversities and Euro-Siberian populations display a significant signal of expansion that is identified to be of Euro-Siberian origin, pointing to the northern refugia hypothesis. The SDMs predict a global net increase in range size owing to ongoing climate change, but substantial range reductions in southern areas. Presence of a significant phylogeographical signal at different spatial scales suggests, however, that dispersal limitations might constitute, as opposed to the traditional view of spore-producing plants as efficient dispersers, a constraint for migration. This casts doubts about the ability of the species to face the massive extinctions predicted in the southern areas, threatening their status of reservoir of genetic diversity. © 2012 Blackwell Publishing Ltd.

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.

A Thermo-Poromechanics Finite Element Model for Predicting Arterial Tissue Fusion

NASA Astrophysics Data System (ADS)

Fankell, Douglas P.

This work provides modeling efforts and supplemental experimental work performed towards the ultimate goal of modeling heat transfer, mass transfer, and deformation occurring in biological tissue, in particular during arterial fusion and cutting. Developing accurate models of these processes accomplishes two goals. First, accurate models would enable engineers to design devices to be safer and less expensive. Second, the mechanisms behind tissue fusion and cutting are widely unknown; models with the ability to accurately predict physical phenomena occurring in the tissue will allow for insight into the underlying mechanisms of the processes. This work presents three aims and the efforts in achieving them, leading to an accurate model of tissue fusion and more broadly the thermo-poromechanics (TPM) occurring within biological tissue. Chapters 1 and 2 provide the motivation for developing accurate TPM models of biological tissue and an overview of previous modeling efforts. In Chapter 3, a coupled thermo-structural finite element (FE) model with the ability to predict arterial cutting is offered. From the work presented in Chapter 3, it became obvious a more detailed model was needed. Chapter 4 meets this need by presenting small strain TPM theory and its implementation in an FE code. The model is then used to simulate thermal tissue fusion. These simulations show the model's promise in predicting the water content and temperature of arterial wall tissue during the fusion process, but it is limited by its small deformation assumptions. Chapters 5-7 attempt to address this limitation by developing and implementing a large deformation TPM FE model. Chapters 5, 6, and 7 present a thermodynamically consistent, large deformation TPM FE model and its ability to simulate tissue fusion. Ultimately, this work provides several methods of simulating arterial tissue fusion and the thermo-poromechanics of biological tissue. It is the first work, to the author's knowledge, to simulate the fully coupled TPM of biological tissue and the first to present a fully coupled large deformation TPM FE model. In doing so, a stepping stone for more advanced modeling of biological tissue has been laid.

A Statistical Model of the International Spread of Wild Poliovirus in Africa Used to Predict and Prevent Outbreaks

PubMed Central

O'Reilly, Kathleen M.; Chauvin, Claire; Aylward, R. Bruce; Maher, Chris; Okiror, Sam; Wolff, Chris; Nshmirimana, Deo; Donnelly, Christl A.; Grassly, Nicholas C.

2011-01-01

Background Outbreaks of poliomyelitis in African countries that were previously free of wild-type poliovirus cost the Global Polio Eradication Initiative US$850 million during 2003–2009, and have limited the ability of the program to focus on endemic countries. A quantitative understanding of the factors that predict the distribution and timing of outbreaks will enable their prevention and facilitate the completion of global eradication. Methods and Findings Children with poliomyelitis in Africa from 1 January 2003 to 31 December 2010 were identified through routine surveillance of cases of acute flaccid paralysis, and separate outbreaks associated with importation of wild-type poliovirus were defined using the genetic relatedness of these viruses in the VP1/2A region. Potential explanatory variables were examined for their association with the number, size, and duration of poliomyelitis outbreaks in 6-mo periods using multivariable regression analysis. The predictive ability of 6-mo-ahead forecasts of poliomyelitis outbreaks in each country based on the regression model was assessed. A total of 142 genetically distinct outbreaks of poliomyelitis were recorded in 25 African countries, resulting in 1–228 cases (median of two cases). The estimated number of people arriving from infected countries and <5-y childhood mortality were independently associated with the number of outbreaks. Immunisation coverage based on the reported vaccination history of children with non-polio acute flaccid paralysis was associated with the duration and size of each outbreak, as well as the number of outbreaks. Six-month-ahead forecasts of the number of outbreaks in a country or region changed over time and had a predictive ability of 82%. Conclusions Outbreaks of poliomyelitis resulted primarily from continued transmission in Nigeria and the poor immunisation status of populations in neighbouring countries. From 1 January 2010 to 30 June 2011, reduced transmission in Nigeria and increased incidence in reinfected countries in west and central Africa have changed the geographical risk of polio outbreaks, and will require careful immunisation planning to limit onward spread. Please see later in the article for the Editors' Summary PMID:22028632

Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence.

PubMed

Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E

2016-11-22

Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.

Prediction of Phase Behavior of Spray-Dried Amorphous Solid Dispersions: Assessment of Thermodynamic Models, Standard Screening Methods and a Novel Atomization Screening Device with Regard to Prediction Accuracy

PubMed Central

Chavez, Pierre-François; Meeus, Joke; Robin, Florent; Schubert, Martin Alexander; Somville, Pascal

2018-01-01

The evaluation of drug–polymer miscibility in the early phase of drug development is essential to ensure successful amorphous solid dispersion (ASD) manufacturing. This work investigates the comparison of thermodynamic models, conventional experimental screening methods (solvent casting, quench cooling), and a novel atomization screening device based on their ability to predict drug–polymer miscibility, solid state properties (Tg value and width), and adequate polymer selection during the development of spray-dried amorphous solid dispersions (SDASDs). Binary ASDs of four drugs and seven polymers were produced at 20:80, 40:60, 60:40, and 80:20 (w/w). Samples were systematically analyzed using modulated differential scanning calorimetry (mDSC) and X-ray powder diffraction (XRPD). Principal component analysis (PCA) was used to qualitatively assess the predictability of screening methods with regards to SDASD development. Poor correlation was found between theoretical models and experimentally-obtained results. Additionally, the limited ability of usual screening methods to predict the miscibility of SDASDs did not guarantee the appropriate selection of lead excipient for the manufacturing of robust SDASDs. Contrary to standard approaches, our novel screening device allowed the selection of optimal polymer and drug loading and established insight into the final properties and performance of SDASDs at an early stage, therefore enabling the optimization of the scaled-up late-stage development. PMID:29518936

Damage and strength of composite materials: Trends, predictions, and challenges

NASA Technical Reports Server (NTRS)

Obrien, T. Kevin

1994-01-01

Research on damage mechanisms and ultimate strength of composite materials relevant to scaling issues will be addressed in this viewgraph presentation. The use of fracture mechanics and Weibull statistics to predict scaling effects for the onset of isolated damage mechanisms will be highlighted. The ability of simple fracture mechanics models to predict trends that are useful in parametric or preliminary designs studies will be reviewed. The limitations of these simple models for complex loading conditions will also be noted. The difficulty in developing generic criteria for the growth of these mechanisms needed in progressive damage models to predict strength will be addressed. A specific example for a problem where failure is a direct consequence of progressive delamination will be explored. A damage threshold/fail-safety concept for addressing composite damage tolerance will be discussed.

Verbal ability, social stress, and anxiety in children with autistic disorder.

PubMed

Lanni, Kimberly E; Schupp, Clayton W; Simon, David; Corbett, Blythe A

2012-03-01

The aims of this study were to evaluate the physiological stress and anxiety responses in children with autism following completion of a standardized, social-evaluative stressor (Trier Social Stress Test-Child version), document the relationship between verbal ability, stress, and anxiety, and determine the association between stress and anxiety in children with autism and typical development. Results demonstrated the Trier Social Stress Test-Child version to be a benign stressor for children with autism. Lower verbal ability in children with autism did not predict salivary cortisol or anxiety responses. There was a lack of association between stress and anxiety for both groups, highlighting the importance of considering these terms as separate constructs. Clinical implications and the limited utility of the Trier Social Stress Test-Child version in evaluating psychosocial stress in autism are discussed.

Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria.

PubMed

Odegård, J; Klemetsdal, G; Heringstad, B

2003-12-01

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.

Frequent long-distance plant colonization in the changing Arctic.

PubMed

Alsos, Inger Greve; Eidesen, Pernille Bronken; Ehrich, Dorothee; Skrede, Inger; Westergaard, Kristine; Jacobsen, Gro Hilde; Landvik, Jon Y; Taberlet, Pierre; Brochmann, Christian

2007-06-15

The ability of species to track their ecological niche after climate change is a major source of uncertainty in predicting their future distribution. By analyzing DNA fingerprinting (amplified fragment-length polymorphism) of nine plant species, we show that long-distance colonization of a remote arctic archipelago, Svalbard, has occurred repeatedly and from several source regions. Propagules are likely carried by wind and drifting sea ice. The genetic effect of restricted colonization was strongly correlated with the temperature requirements of the species, indicating that establishment limits distribution more than dispersal. Thus, it may be appropriate to assume unlimited dispersal when predicting long-term range shifts in the Arctic.

Graphics Processing Units (GPU) and the Goddard Earth Observing System atmospheric model (GEOS-5): Implementation and Potential Applications

NASA Technical Reports Server (NTRS)

Putnam, William M.

2011-01-01

Earth system models like the Goddard Earth Observing System model (GEOS-5) have been pushing the limits of large clusters of multi-core microprocessors, producing breath-taking fidelity in resolving cloud systems at a global scale. GPU computing presents an opportunity for improving the efficiency of these leading edge models. A GPU implementation of GEOS-5 will facilitate the use of cloud-system resolving resolutions in data assimilation and weather prediction, at resolutions near 3.5 km, improving our ability to extract detailed information from high-resolution satellite observations and ultimately produce better weather and climate predictions

Serpentinization as a reactive transport process: The brucite silicification reaction

NASA Astrophysics Data System (ADS)

Tutolo, Benjamin M.; Luhmann, Andrew J.; Tosca, Nicholas J.; Seyfried, William E.

2018-02-01

Serpentinization plays a fundamental role in the biogeochemical and tectonic evolution of the Earth and perhaps many other rocky planetary bodies. Yet, geochemical models still fail to produce accurate predictions of the various modes of serpentinization, which limits our ability to predict a variety of related geological phenomena over many spatial and temporal scales. Here, we use kinetic and reactive transport experiments to parameterize the brucite silicification reaction and provide fundamental constraints on SiO2 transport during serpentinization. We show that, at temperatures characteristic of the sub-seafloor at the serpentinite-hosted Lost City Hydrothermal Field (150 °C), the assembly of Si tetrahedra onto MgOH2 (i.e., brucite) surfaces is a rate-limiting elementary reaction in the production of serpentine and/or talc from olivine. Moreover, this reaction is exponentially dependent on the activity of aqueous silica (a SiO2 (aq)), such that it can be calculated according to the rate law:

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.

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.

Recent developments on SMA actuators: predicting the actuation fatigue life for variable loading schemes

NASA Astrophysics Data System (ADS)

Wheeler, Robert W.; Lagoudas, Dimitris C.

2017-04-01

Shape memory alloys (SMAs), due to their ability to repeatably recover substantial deformations under applied mechanical loading, have the potential to impact the aerospace, automotive, biomedical, and energy industries as weight and volume saving replacements for conventional actuators. While numerous applications of SMA actuators have been flight tested and can be found in industrial applications, these actuators are generally limited to non-critical components, are not widely implemented and frequently one-off designs, and are generally overdesigned due to a lack of understanding of the effect of the loading path on the fatigue life and the lack of an accurate method for predicting actuator lifetimes. In recent years, multiple research efforts have increased our understanding of the actuation fatigue process of SMAs. These advances can be utilized to predict the fatigue lives and failure loads in SMA actuators. Additionally, these prediction methods can be implemented in order to intelligently design actuators in accordance with their fatigue and failure limits. In the following paper, both simple and complex thermomechanical loading paths have been considered. Experimental data was utilized from two material systems: equiatomic Nickel-Titanium and Nickelrich Nickel-Titanium.

Predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review.

PubMed

Ryan, J E; Warrier, S K; Lynch, A C; Ramsay, R G; Phillips, W A; Heriot, A G

2016-03-01

Approximately 20% of patients treated with neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer achieve a pathological complete response (pCR) while the remainder derive the benefit of improved local control and downstaging and a small proportion show a minimal response. The ability to predict which patients will benefit would allow for improved patient stratification directing therapy to those who are likely to achieve a good response, thereby avoiding ineffective treatment in those unlikely to benefit. A systematic review of the English language literature was conducted to identify pathological factors, imaging modalities and molecular factors that predict pCR following chemoradiotherapy. PubMed, MEDLINE and Cochrane Database searches were conducted with the following keywords and MeSH search terms: 'rectal neoplasm', 'response', 'neoadjuvant', 'preoperative chemoradiation', 'tumor response'. After review of title and abstracts, 85 articles addressing the prediction of pCR were selected. Clear methods to predict pCR before chemoradiotherapy have not been defined. Clinical and radiological features of the primary cancer have limited ability to predict response. Molecular profiling holds the greatest potential to predict pCR but adoption of this technology will require greater concordance between cohorts for the biomarkers currently under investigation. At present no robust markers of the prediction of pCR have been identified and the topic remains an area for future research. This review critically evaluates existing literature providing an overview of the methods currently available to predict pCR to nCRT for locally advanced rectal cancer. The review also provides a comprehensive comparison of the accuracy of each modality. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School.

PubMed

Yates, Janet; James, David

2010-07-28

The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown.The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Data were available for 204/260 (78%) of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell'), (p = 0.005), and Verbal Reasoning predicted Theme C ('The Community') (p < 0.001), but otherwise the effects were slight or non-existent. This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment.The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.

Redefining plant functional types for forests based on plant traits

NASA Astrophysics Data System (ADS)

Wei, L.; Xu, C.; Christoffersen, B. O.; McDowell, N. G.; Zhou, H.

2016-12-01

Our ability to predict forest mortality is limited by the simple plant functional types (PFTs) in current generations of Earth System models (ESMs). For example, forests were formerly separated into PFTs only based on leaf form and phenology across different regions (arctic, temperate, and tropic areas) in the Community Earth System Model (CESM). This definition of PFTs ignored the large variation in vulnerability of species to drought and shade tolerance within each PFT. We redefined the PFTs for global forests based on plant traits including phenology, wood density, leaf mass per area, xylem-specific conductivity, and xylem pressure at 50% loss of conductivity. Species with similar survival strategies were grouped into the same PFT. New PFTs highlighted variation in vulnerability and physiological adaptation to drought and shade. New PFTs were better clustered than old ones in the two-dimensional plane of the first two principle components in a principle component analysis. We expect that the new PFTs will strengthen ESMs' ability on predicting drought-induced mortality in the future.

Detection and identification of extra virgin olive oil adulteration by GC-MS combined with chemometrics.

PubMed

Yang, Yang; Ferro, Miguel Duarte; Cavaco, Isabel; Liang, Yizeng

2013-04-17

In this study, an analytical method for the detection and identification of extra virgin olive oil adulteration with four types of oils (corn, peanut, rapeseed, and sunflower oils) was proposed. The variables under evaluation included 22 fatty acids and 6 other significant parameters (the ratio of linoleic/linolenic acid, oleic/linoleic acid, total saturated fatty acids (SFAs), polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs), MUFAs/PUFAs). Univariate analyses followed by multivariate analyses were applied to the adulteration investigation. As a result, the univariate analyses demonstrated that higher contents of eicosanoic acid, docosanoic acid, tetracosanoic acid, and SFAs were the peculiarities of peanut adulteration and higher levels of linolenic acid, 11-eicosenoic acid, erucic acid, and nervonic acid the characteristics of rapeseed adulteration. Then, PLS-LDA made the detection of adulteration effective with a 1% detection limit and 90% prediction ability; a Monte Carlo tree identified the type of adulteration with 85% prediction ability.

Validation of the Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) pulmonary hypertension prediction model in a unique population and utility in the prediction of long-term survival.

PubMed

Cogswell, Rebecca; Kobashigawa, Erin; McGlothlin, Dana; Shaw, Robin; De Marco, Teresa

2012-11-01

The Registry to Evaluate Early and Long-Term Pulmonary Arterial (PAH) Hypertension Disease Management (REVEAL) model was designed to predict 1-year survival in patients with PAH. Multivariate prediction models need to be evaluated in cohorts distinct from the derivation set to determine external validity. In addition, limited data exist on the utility of this model in the prediction of long-term survival. REVEAL model performance was assessed to predict 1-year and 5-year outcomes, defined as survival or composite survival or freedom from lung transplant, in 140 patients with PAH. The validation cohort had a higher proportion of human immunodeficiency virus (7.9% vs 1.9%, p < 0.0001), methamphetamine use (19.3% vs 4.9%, p < 0.0001), and portal hypertension PAH (16.4% vs 5.1%, p < 0.0001) compared with the development cohort. The C-index of the model to predict survival was 0.765 at 1 year and 0.712 at 5 years of follow-up. The C-index of the model to predict composite survival or freedom from lung transplant was 0.805 and 0.724 at 1 and 5 years of follow-up, respectively. Prediction by the model, however, was weakest among patients with intermediate-risk predicted survival. The REVEAL model had adequate discrimination to predict 1-year survival in this small but clinically distinct validation cohort. Although the model also had predictive ability out to 5 years, prediction was limited among patients of intermediate risk, suggesting our prediction methods can still be improved. Copyright © 2012. Published by Elsevier Inc.

Evaluation of the heat transfer module (FAHT) of Failure Analysis Nonlinear Thermal And Structural Integrated Code (FANTASTIC)

NASA Technical Reports Server (NTRS)

Keyhani, Majid

1989-01-01

The heat transfer module of FANTASTIC Code (FAHT) is studied and evaluated to the extend possible during the ten weeks duration of this project. A brief background of the previous studies is given and the governing equations as modeled in FAHT are discussed. FAHT's capabilities and limitations based on these equations and its coding methodology are explained in detail. It is established that with improper choice of element size and time step FAHT's temperature field prediction at some nodes will be below the initial condition. The source of this unrealistic temperature prediction is identified and a procedure is proposed for avoiding this phenomenon. It is further shown that the proposed procedure will converge to an accurate prediction upon mesh refinement. Unfortunately due to lack of time FAHT's ability to accurately account for pyrolysis and surface ablation has not been verified. Therefore, at the present time it can be stated with confidence that FAHT can accurately predict the temperature field for a transient multi-dimensional, orthotropic material with directional dependence, variable property, with nonlinear boundary condition. Such a prediction will provide an upper limit for the temperature field in an ablating decomposing nozzle liner. The pore pressure field, however, will not be known.

Multiple testing of food contact materials: a predictive algorithm for assessing the global migration from silicone moulds.

PubMed

Elskens, Marc; Vloeberghs, Daniel; Van Elsen, Liesbeth; Baeyens, Willy; Goeyens, Leo

2012-09-15

For reasons of food safety, packaging and food contact materials must be submitted to migration tests. Testing of silicone moulds is often very laborious, since three replicate tests are required to decide about their compliancy. This paper presents a general modelling framework to predict the sample's compliance or non-compliance using results of the first two migration tests. It compares the outcomes of models with multiple continuous predictors with a class of models involving latent and dummy variables. The model's prediction ability was tested using cross and external validations, i.e. model revalidation each time a new measurement set became available. At the overall migration limit of 10 mg dm(-2), the relative uncertainty on a prediction was estimated to be ~10%. Taking the default values for α and β equal to 0.05, the maximum value that can be predicted for sample compliance was therefore 7 mg dm(-2). Beyond this limit the risk for false compliant results increases significantly, and a third migration test should be performed. The result of this latter test defines the sample's compliance or non-compliance. Propositions for compliancy control inspired by the current dioxin control strategy are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

PubMed Central

Sun, Chuanyu; VanRaden, Paul M.; Cole, John B.; O'Connell, Jeffrey R.

2014-01-01

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield. PMID:25084281

An Ribonuclease T2 Family Protein Modulates Acinetobacter baumannii Abiotic Surface Colonization

PubMed Central

Jacobs, Anna C.; Blanchard, Catlyn E.; Catherman, Seana C.; Dunman, Paul M.; Murata, Yoshihiko

2014-01-01

Acinetobacter baumannii is an emerging bacterial pathogen of considerable medical concern. The organism's transmission and ability to cause disease has been associated with its propensity to colonize and form biofilms on abiotic surfaces in health care settings. To better understand the genetic determinants that affect biomaterial attachment, we performed a transposon mutagenesis analysis of abiotic surface-colonization using A. baumannii strain 98-37-09. Disruption of an RNase T2 family gene was found to limit the organism's ability to colonize polystyrene, polypropylene, glass, and stainless steel surfaces. DNA microarray analyses revealed that in comparison to wild type and complemented cells, the RNase T2 family mutant exhibited reduced expression of 29 genes, 15 of which are predicted to be associated with bacterial attachment and surface-associated motility. Motility assays confirmed that RNase T2 mutant displays a severe motility defect. Taken together, our results indicate that the RNase T2 family protein identified in this study is a positive regulator of A. baumannii's ability to colonize inanimate surfaces and motility. Moreover, the enzyme may be an effective target for the intervention of biomaterial colonization, and consequently limit the organism's transmission within the hospital setting. PMID:24489668

Sublethal salinity stress contributes to habitat limitation in an endangered estuarine fish.

PubMed

Komoroske, Lisa M; Jeffries, Ken M; Connon, Richard E; Dexter, Jason; Hasenbein, Matthias; Verhille, Christine; Fangue, Nann A

2016-09-01

As global change alters multiple environmental conditions, predicting species' responses can be challenging without understanding how each environmental factor influences organismal performance. Approaches quantifying mechanistic relationships can greatly complement correlative field data, strengthening our abilities to forecast global change impacts. Substantial salinity increases are projected in the San Francisco Estuary, California, due to anthropogenic water diversion and climatic changes, where the critically endangered delta smelt (Hypomesus transpacificus) largely occurs in a low-salinity zone (LSZ), despite their ability to tolerate a much broader salinity range. In this study, we combined molecular and organismal measures to quantify the physiological mechanisms and sublethal responses involved in coping with salinity changes. Delta smelt utilize a suite of conserved molecular mechanisms to rapidly adjust their osmoregulatory physiology in response to salinity changes in estuarine environments. However, these responses can be energetically expensive, and delta smelt body condition was reduced at high salinities. Thus, acclimating to salinities outside the LSZ could impose energetic costs that constrain delta smelt's ability to exploit these habitats. By integrating data across biological levels, we provide key insight into the mechanistic relationships contributing to phenotypic plasticity and distribution limitations and advance the understanding of the molecular osmoregulatory responses in nonmodel estuarine fishes.

Convolutional Neural Networks for 1-D Many-Channel Data

DTIC Science & Technology

Deep convolutional neural networks (CNNs) represent the state of the art in image recognition. The same properties that led to their success in that... crack detection ( 8,000 data points, 72 channels). Though the models predictive ability is limited to fitting the trend , its partial success suggests that...originally written to classify digits in the MNIST database (28 28 pixels, 1 channel), for use on 1-D acoustic data taken from experiments focused on

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…

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

PubMed Central

Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

2015-01-01

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

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

Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.

2018-01-01

A trade-off between competitive ability and stress tolerance has been hypothesized and empirically supported to explain the zonation of species across stress gradients for a number of systems. Since stress often reduces plant productivity, one might expect a pattern of decreasing productivity across the zones of the stress gradient. However, this pattern is often not observed in coastal wetlands that show patterns of zonation along a salinity gradient. To address the potentially complex relationship between stress, zonation, and productivity in coastal wetlands, we developed a model of plant biomass as a function of resource competition and salinity stress. Analysis of the model confirms the conventional wisdom that a trade-off between competitive ability and stress tolerance is a necessary condition for zonation. It also suggests that a negative relationship between salinity and production can be overcome if (1) the supply of the limiting resource increases with greater salinity stress or (2) nutrient use efficiency increases with increasing salinity. We fit the equilibrium solution of the dynamic model to data from Louisiana coastal wetlands to test its ability to explain patterns of production across the landscape gradient and derive predictions that could be tested with independent data. We found support for a number of the model predictions, including patterns of decreasing competitive ability and increasing nutrient use efficiency across a gradient from freshwater to saline wetlands. In addition to providing a quantitative framework to support the mechanistic hypotheses of zonation, these results suggest that this simple model is a useful platform to further build upon, simulate and test mechanistic hypotheses of more complex patterns and phenomena in coastal wetlands.

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…

Predicting soil formation on the basis of transport-limited chemical weathering

NASA Astrophysics Data System (ADS)

Yu, Fang; Hunt, Allen Gerhard

2018-01-01

Soil production is closely related to chemical weathering. It has been shown that, under the assumption that chemical weathering is limited by solute transport, the process of soil production is predictable. However, solute transport in soil cannot be described by Gaussian transport. In this paper, we propose an approach based on percolation theory describing non-Gaussian transport of solute to predict soil formation (the net production of soil) by considering both soil production from chemical weathering and removal of soil from erosion. Our prediction shows agreement with observed soil depths in the field. Theoretical soil formation rates are also compared with published rates predicted using soil age-profile thickness (SAST) method. Our formulation can be incorporated directly into landscape evolution models on a point-to-point basis as long as such models account for surface water routing associated with overland flow. Further, our treatment can be scaled-up to address complications associated with continental-scale applications, including those from climate change, such as changes in vegetation, or surface flow organization. The ability to predict soil formation rates has implications for understanding Earth's climate system on account of the relationship to chemical weathering of silicate minerals with the associated drawdown of atmospheric carbon, but it is also important in geomorphology for understanding landscape evolution, including for example, the shapes of hillslopes, and the net transport of sediments to sedimentary basins.

Terrestrial biogeochemical cycles: global interactions with the atmosphere and hydrology

NASA Astrophysics Data System (ADS)

Schimel, David S.; Kittel, Timothy G. F.; Parton, William J.

1991-08-01

Ecosystem scientists have developed a body of theory to predict the behaviour of biogeochemical cycles when exchanges with other ecosystems are small or prescribed. Recent environmental changes make it clear that linkages between ecosystems via atmospheric and hydrological transport have large effects on ecosystem dynamics when considered over time periods of a decade to a century, time scales relevant to contemporary humankind. Our ability to predict behaviour of ecosystems coupled by transport is limited by our ability (1) to extrapolate biotic function to large spatial scales and (2) to measure and model transport. We review developments in ecosystem theory, remote sensing, and geographical information systems (GIS) that support new efforts in spatial modeling. A paradigm has emerged to predict behaviour of ecosystems based on understanding responses to multiple resources (e.g., water, nutrients, light). Several ecosystem models couple primary production to decomposition and nutrient availability using the above paradigm. These models require a fairly small set of environmental variables to simulate spatial and temporal variation in rates of biogeochemical cycling. Simultaneously, techniques for inferring ecosystem behaviour from remotely measured canopy light interception are improving our ability to infer plant activity from satellite observations. Efforts have begun to couple models of transport in air and water to models of ecosystem function. Preliminary work indicates that coupling of transport and ecosystem processes alters the behaviour of earth system components (hydrology, terrestrial ecosystems, and the atmosphere) from that of an uncoupled mode.

The genome editing toolbox: a spectrum of approaches for targeted modification.

PubMed

Cheng, Joseph K; Alper, Hal S

2014-12-01

The increase in quality, quantity, and complexity of recombinant products heavily drives the need to predictably engineer model and complex (mammalian) cell systems. However, until recently, limited tools offered the ability to precisely manipulate their genomes, thus impeding the full potential of rational cell line development processes. Targeted genome editing can combine the advances in synthetic and systems biology with current cellular hosts to further push productivity and expand the product repertoire. This review highlights recent advances in targeted genome editing techniques, discussing some of their capabilities and limitations and their potential to aid advances in pharmaceutical biotechnology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Employment and Disability: Evidence From the 1996 Medical Expenditures Panel Survey

PubMed Central

Findley, Patricia A.; Sambamoorthi, Usha

2007-01-01

The relationship between employment and disability has gained national attention, as the ability to maintain employment is inconsistent among those with limitations. This cross-sectional study of employment among individuals (N = 1691, age 21–62 years) with self-reported limitations in the 1996 Medical Expenditures Panel Survey seeks to identify predictors of employment despite physical and/or cognitive limitations. Two predictive models of employment including 10 variables are explored; 1 included insurance (χ2 = 3856.85, p ≤ 0.00) and the other removed the insurance variable (χ2 = 280.21, p ≤ 0.00). Individuals with limitations who are employed are more likely to have a college-level education, have better physical and mental health perceptions and have private insurance. This analysis demonstrates that people do work despite reported activity, functional or sensory limitations and that socioeconomic factors are crucial in why someone is able to attain employment. PMID:15055500

Cortical Measures of Binaural Processing Predict Spatial Release from Masking Performance

PubMed Central

Papesh, Melissa A.; Folmer, Robert L.; Gallun, Frederick J.

2017-01-01

Binaural sensitivity is an important contributor to the ability to understand speech in adverse acoustical environments such as restaurants and other social gatherings. The ability to accurately report on binaural percepts is not commonly measured, however, as extensive training is required before reliable measures can be obtained. Here, we investigated the use of auditory evoked potentials (AEPs) as a rapid physiological indicator of detection of interaural phase differences (IPDs) by assessing cortical responses to 180° IPDs embedded in amplitude-modulated carrier tones. We predicted that decrements in encoding of IPDs would be evident in middle age, with further declines found with advancing age and hearing loss. Thus, participants in experiment #1 were young to middle-aged adults with relatively good hearing thresholds while participants in experiment #2 were older individuals with typical age-related hearing loss. Results revealed that while many of the participants in experiment #1 could encode IPDs in stimuli up to 1,000 Hz, few of the participants in experiment #2 had discernable responses to stimuli above 750 Hz. These results are consistent with previous studies that have found that aging and hearing loss impose frequency limits on the ability to encode interaural phase information present in the fine structure of auditory stimuli. We further hypothesized that AEP measures of binaural sensitivity would be predictive of participants' ability to benefit from spatial separation between sound sources, a phenomenon known as spatial release from masking (SRM) which depends upon binaural cues. Results indicate that not only were objective IPD measures well correlated with and predictive of behavioral SRM measures in both experiments, but that they provided much stronger predictive value than age or hearing loss. Overall, the present work shows that objective measures of the encoding of interaural phase information can be readily obtained using commonly available AEP equipment, allowing accurate determination of the degree to which binaural sensitivity has been reduced in individual listeners due to aging and/or hearing loss. In fact, objective AEP measures of interaural phase encoding are actually better predictors of SRM in speech-in-speech conditions than are age, hearing loss, or the combination of age and hearing loss. PMID:28377706

Cortical Measures of Binaural Processing Predict Spatial Release from Masking Performance.

PubMed

Papesh, Melissa A; Folmer, Robert L; Gallun, Frederick J

2017-01-01

Binaural sensitivity is an important contributor to the ability to understand speech in adverse acoustical environments such as restaurants and other social gatherings. The ability to accurately report on binaural percepts is not commonly measured, however, as extensive training is required before reliable measures can be obtained. Here, we investigated the use of auditory evoked potentials (AEPs) as a rapid physiological indicator of detection of interaural phase differences (IPDs) by assessing cortical responses to 180° IPDs embedded in amplitude-modulated carrier tones. We predicted that decrements in encoding of IPDs would be evident in middle age, with further declines found with advancing age and hearing loss. Thus, participants in experiment #1 were young to middle-aged adults with relatively good hearing thresholds while participants in experiment #2 were older individuals with typical age-related hearing loss. Results revealed that while many of the participants in experiment #1 could encode IPDs in stimuli up to 1,000 Hz, few of the participants in experiment #2 had discernable responses to stimuli above 750 Hz. These results are consistent with previous studies that have found that aging and hearing loss impose frequency limits on the ability to encode interaural phase information present in the fine structure of auditory stimuli. We further hypothesized that AEP measures of binaural sensitivity would be predictive of participants' ability to benefit from spatial separation between sound sources, a phenomenon known as spatial release from masking (SRM) which depends upon binaural cues. Results indicate that not only were objective IPD measures well correlated with and predictive of behavioral SRM measures in both experiments, but that they provided much stronger predictive value than age or hearing loss. Overall, the present work shows that objective measures of the encoding of interaural phase information can be readily obtained using commonly available AEP equipment, allowing accurate determination of the degree to which binaural sensitivity has been reduced in individual listeners due to aging and/or hearing loss. In fact, objective AEP measures of interaural phase encoding are actually better predictors of SRM in speech-in-speech conditions than are age, hearing loss, or the combination of age and hearing loss.

Predictive inference for best linear combination of biomarkers subject to limits of detection.

PubMed

Coolen-Maturi, Tahani

2017-08-15

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Predictive validity of the Work Ability Index and its individual items in the general population.

PubMed

Lundin, Andreas; Leijon, Ola; Vaez, Marjan; Hallgren, Mats; Torgén, Margareta

2017-06-01

This study assesses the predictive ability of the full Work Ability Index (WAI) as well as its individual items in the general population. The Work, Health and Retirement Study (WHRS) is a stratified random national sample of 25-75-year-olds living in Sweden in 2000 that received a postal questionnaire ( n = 6637, response rate = 53%). Current and subsequent sickness absence was obtained from registers. The ability of the WAI to predict long-term sickness absence (LTSA; ⩾ 90 consecutive days) during a period of four years was analysed by logistic regression, from which the Area Under the Receiver Operating Characteristic curve (AUC) was computed. There were 313 incident LTSA cases among 1786 employed individuals. The full WAI had acceptable ability to predict LTSA during the 4-year follow-up (AUC = 0.79; 95% CI 0.76 to 0.82). Individual items were less stable in their predictive ability. However, three of the individual items: current work ability compared with lifetime best, estimated work impairment due to diseases, and number of diagnosed current diseases, exceeded AUC > 0.70. Excluding the WAI item on number of days on sickness absence did not result in an inferior predictive ability of the WAI. The full WAI has acceptable predictive validity, and is superior to its individual items. For public health surveys, three items may be suitable proxies of the full WAI; current work ability compared with lifetime best, estimated work impairment due to diseases, and number of current diseases diagnosed by a physician.

Standoff Human Identification Using Body Shape

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

Matzner, Shari; Heredia-Langner, Alejandro; Amidan, Brett G.

2015-09-01

The ability to identify individuals is a key component of maintaining safety and security in public spaces and around critical infrastructure. Monitoring an open space is challenging because individuals must be identified and re-identified from a standoff distance nonintrusively, making methods like fingerprinting and even facial recognition impractical. We propose using body shape features as a means for identification from standoff sensing, either complementing other identifiers or as an alternative. An important challenge in monitoring open spaces is reconstructing identifying features when only a partial observation is available, because of the view-angle limitations and occlusion or subject pose changes. Tomore » address this challenge, we investigated the minimum number of features required for a high probability of correct identification, and we developed models for predicting a key body feature—height—from a limited set of observed features. We found that any set of nine randomly selected body measurements was sufficient to correctly identify an individual in a dataset of 4426 subjects. For predicting height, anthropometric measures were investigated for correlation with height. Their correlation coefficients and associated linear models were reported. These results—a sufficient number of features for identification and height prediction from a single feature—contribute to developing systems for standoff identification when views of a subject are limited.« less

Simulating Dissolution of Intravitreal Triamcinolone Acetonide Suspensions in an Anatomically Accurate Rabbit Eye Model

PubMed Central

Horner, Marc; Muralikrishnan, R.

2010-01-01

ABSTRACT Purpose A computational fluid dynamics (CFD) study examined the impact of particle size on dissolution rate and residence of intravitreal suspension depots of Triamcinolone Acetonide (TAC). Methods A model for the rabbit eye was constructed using insights from high-resolution NMR imaging studies (Sawada 2002). The current model was compared to other published simulations in its ability to predict clearance of various intravitreally injected materials. Suspension depots were constructed explicitly rendering individual particles in various configurations: 4 or 16 mg drug confined to a 100 μL spherical depot, or 4 mg exploded to fill the entire vitreous. Particle size was reduced systematically in each configuration. The convective diffusion/dissolution process was simulated using a multiphase model. Results Release rate became independent of particle diameter below a certain value. The size-independent limits occurred for particle diameters ranging from 77 to 428 μM depending upon the depot configuration. Residence time predicted for the spherical depots in the size-independent limit was comparable to that observed in vivo. Conclusions Since the size-independent limit was several-fold greater than the particle size of commercially available pharmaceutical TAC suspensions, differences in particle size amongst such products are predicted to be immaterial to their duration or performance. PMID:20467888

Modeling and predicting intertidal variations of the salinity field in the Bay/Delta

USGS Publications Warehouse

Knowles, Noah; Uncles, Reginald J.

1995-01-01

One approach to simulating daily to monthly variability in the bay is the development of intertidal model using tidally-averaged equations and a time step on the order of the day.  An intertidal numerical model of the bay's physics, capable of portraying seasonal and inter-annual variability, would have several uses.  Observations are limited in time and space, so simulation could help fill the gaps.  Also, the ability to simulate multi-year episodes (eg, an extended drought) could provide insight into the response of the ecosystem to such events.  Finally, such a model could be used in a forecast mode wherein predicted delta flow is used as model input, and predicted salinity distribution is output with estimates days and months in advance.  This note briefly introduces such a tidally-averaged model (Uncles and Peterson, in press) and a corresponding predictive scheme for baywide forecasting.

Identifying gnostic predictors of the vaccine response.

PubMed

Haining, W Nicholas; Pulendran, Bali

2012-06-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis of their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of vaccine prediction. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. Copyright © 2012 Elsevier Ltd. All rights reserved.

Forecasting seasonal outbreaks of influenza.

PubMed

Shaman, Jeffrey; Karspeck, Alicia

2012-12-11

Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.

Forecasting seasonal outbreaks of influenza

PubMed Central

Shaman, Jeffrey; Karspeck, Alicia

2012-01-01

Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003–2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza. PMID:23184969

Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724

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.

Expedited CT-Based Methods for Evaluating Fracture Severity to Assess Risk of Post-Traumatic Osteoarthritis After Articular Fractures.

PubMed

Anderson, Donald D; Kilburg, Anthony T; Thomas, Thaddeus P; Marsh, J Lawrence

2016-01-01

Post-traumatic osteoarthritis (PTOA) is common after intra-articular fractures of the tibial plafond. An objective CT-based measure of fracture severity was previously found to reliably predict whether PTOA developed following surgical treatment of such fractures. However, the extended time required obtaining the fracture energy metric and its reliance upon an intact contralateral limb CT limited its clinical applicability. The objective of this study was to establish an expedited fracture severity metric that provided comparable PTOA predictive ability without the prior limitations. An expedited fracture severity metric was computed from the CT scans of 30 tibial plafond fractures using textural analysis to quantify disorder in CT images. The expedited method utilized an intact surrogate model to enable severity assessment without requiring a contralateral limb CT. Agreement between the expedited fracture severity metric and the Kellgren-Lawrence (KL) radiographic OA score at two-year follow-up was assessed using concordance. The ability of the metric to differentiate between patients that did or did not develop PTOA was assessed using the Wilcoxon Ranked Sum test. The expedited severity metric agreed well (75.2% concordance) with the KL scores. The initial fracture severity of cases that developed PTOA differed significantly (p = 0.004) from those that did not. Receiver operating characteristic analysis showed that the expedited severity metric could accurately predict PTOA outcome in 80% of the cases. The time required to obtain the expedited severity metric averaged 14.9 minutes/ case, and the metric was obtained without using an intact contralateral CT. The expedited CT-based methods for fracture severity assessment present a solution to issues limiting the utility of prior methods. In a relatively short amount of time, the expedited methodology provided a severity score capable of predicting PTOA risk, without needing to have the intact contralateral limb included in the CT scan. The described methods provide surgeons an objective, quantitative representation of the severity of a fracture. Obtained prior to the surgery, it provides a reasonable alternative to current subjective classification systems. The expedited severity metric offers surgeons an objective means for factoring severity of joint insult into treatment decision-making.

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.

Modeling irrigation behavior in groundwater systems

NASA Astrophysics Data System (ADS)

Foster, Timothy; Brozović, Nicholas; Butler, Adrian P.

2014-08-01

Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.

Physiologically grounded metrics of model skill: a case study estimating heat stress in intertidal populations

PubMed Central

Kish, Nicole E.; Helmuth, Brian; Wethey, David S.

2016-01-01

Models of ecological responses to climate change fundamentally assume that predictor variables, which are often measured at large scales, are to some degree diagnostic of the smaller-scale biological processes that ultimately drive patterns of abundance and distribution. Given that organisms respond physiologically to stressors, such as temperature, in highly non-linear ways, small modelling errors in predictor variables can potentially result in failures to predict mortality or severe stress, especially if an organism exists near its physiological limits. As a result, a central challenge facing ecologists, particularly those attempting to forecast future responses to environmental change, is how to develop metrics of forecast model skill (the ability of a model to predict defined events) that are biologically meaningful and reflective of underlying processes. We quantified the skill of four simple models of body temperature (a primary determinant of physiological stress) of an intertidal mussel, Mytilus californianus, using common metrics of model performance, such as root mean square error, as well as forecast verification skill scores developed by the meteorological community. We used a physiologically grounded framework to assess each model's ability to predict optimal, sub-optimal, sub-lethal and lethal physiological responses. Models diverged in their ability to predict different levels of physiological stress when evaluated using skill scores, even though common metrics, such as root mean square error, indicated similar accuracy overall. Results from this study emphasize the importance of grounding assessments of model skill in the context of an organism's physiology and, especially, of considering the implications of false-positive and false-negative errors when forecasting the ecological effects of environmental change. PMID:27729979

Graphical tools for TV weather presentation

NASA Astrophysics Data System (ADS)

Najman, M.

2010-09-01

Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.

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.

Understanding Long-Term Variations in an Elephant Piosphere Effect to Manage Impacts

PubMed Central

Landman, Marietjie; Schoeman, David S.; Hall-Martin, Anthony J.; Kerley, Graham I. H.

2012-01-01

Surface water availability is a key driver of elephant impacts on biological diversity. Thus, understanding the spatio-temporal variations of these impacts in relation to water is critical to their management. However, elephant piosphere effects (i.e. the radial pattern of attenuating impact) are poorly described, with few long-term quantitative studies. Our understanding is further confounded by the complexity of systems with elephant (i.e. fenced, multiple water points, seasonal water availability, varying population densities) that likely limit the use of conceptual models to predict these impacts. Using 31 years of data on shrub structure in the succulent thickets of the Addo Elephant National Park, South Africa, we tested elephant effects at a single water point. Shrub structure showed a clear sigmoid response with distance from water, declining at both the upper and lower limits of sampling. Adjacent to water, this decline caused a roughly 300-m radial expansion of the grass-dominated habitats that replace shrub communities. Despite the clear relationship between shrub structure and ecological functioning in thicket, the extent of elephant effects varied between these features with distance from water. Moreover, these patterns co-varied with other confounding variables (e.g. the location of neighboring water points), which limits our ability to predict such effects in the absence of long-term data. We predict that elephant have the ability to cause severe transformation in succulent thicket habitats with abundant water supply and elevated elephant numbers. However, these piosphere effects are complex, suggesting that a more integrated understanding of elephant impacts on ecological heterogeneity may be required before water availability is used as a tool to manage impacts. We caution against the establishment of water points in novel succulent thicket habitats, and advocate a significant reduction in water provisioning at our study site, albeit with greater impacts at each water point. PMID:23028942

Understanding long-term variations in an elephant piosphere effect to manage impacts.

PubMed

Landman, Marietjie; Schoeman, David S; Hall-Martin, Anthony J; Kerley, Graham I H

2012-01-01

Surface water availability is a key driver of elephant impacts on biological diversity. Thus, understanding the spatio-temporal variations of these impacts in relation to water is critical to their management. However, elephant piosphere effects (i.e. the radial pattern of attenuating impact) are poorly described, with few long-term quantitative studies. Our understanding is further confounded by the complexity of systems with elephant (i.e. fenced, multiple water points, seasonal water availability, varying population densities) that likely limit the use of conceptual models to predict these impacts. Using 31 years of data on shrub structure in the succulent thickets of the Addo Elephant National Park, South Africa, we tested elephant effects at a single water point. Shrub structure showed a clear sigmoid response with distance from water, declining at both the upper and lower limits of sampling. Adjacent to water, this decline caused a roughly 300-m radial expansion of the grass-dominated habitats that replace shrub communities. Despite the clear relationship between shrub structure and ecological functioning in thicket, the extent of elephant effects varied between these features with distance from water. Moreover, these patterns co-varied with other confounding variables (e.g. the location of neighboring water points), which limits our ability to predict such effects in the absence of long-term data. We predict that elephant have the ability to cause severe transformation in succulent thicket habitats with abundant water supply and elevated elephant numbers. However, these piosphere effects are complex, suggesting that a more integrated understanding of elephant impacts on ecological heterogeneity may be required before water availability is used as a tool to manage impacts. We caution against the establishment of water points in novel succulent thicket habitats, and advocate a significant reduction in water provisioning at our study site, albeit with greater impacts at each water point.

Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)

NASA Astrophysics Data System (ADS)

Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.

2009-12-01

Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.

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.

Technical and physical determinants of soccer match-play performance in elite youth soccer players.

PubMed

Rowat, Owain; Fenner, Jonathan; Unnithan, Viswanath

2017-04-01

The aim of this study was to evaluate whether physical performance characteristics could be a better predictor than technical skills in determining the technical level of county soccer players in a match situation. With institutional ethics approval, 25 male youth soccer players aged 16-18.5 years from a professional soccer academy in South East Asia were selected and height and body mass were recorded. Players were tested for sexual maturity (pubertal development scale [PDS] self-assessment), aerobic capacity (yo-yo intermittent recovery test level 1 [YYIR1]), repeated sprint ability (7 x 35 m sprints) acceleration (15 m sprint) and four soccer skills tests (dribble with pass, dribbling speed, passing and shooting accuracy). Players' technical ability during match play was assessed in small-sided games of soccer (5 v 5) using a novel game technical scoring chart (scoring chart completed by coaches to assess technical performance in a match situation) developed from criteria (e.g., first touch, dribbling and two footedness) used by youth soccer coaches for talent identification. A Spearman's rank correlation showed the YYIR1 test and 15 m sprint test were limited in predicting technical match performance (r=0.03, P=0.88, r=-0.23, P=0.32 respectively). A Pearson product moment correlation showed that the repeated sprint test was also limited in predicting technical match performance (r=-0.34, P=0.14). A dribbling skill with a pass was found to be the best determinant of a player's technical ability in a match (r=-0.57, P=0.00). Talent identification and selection programs in Asian youth soccer should include a dribbling skill performed with a pass.

Biomedical systems analysis program

NASA Technical Reports Server (NTRS)

1979-01-01

Biomedical monitoring programs which were developed to provide a system analysis context for a unified hypothesis for adaptation to space flight are presented and discussed. A real-time system of data analysis and decision making to assure the greatest possible crew safety and mission success is described. Information about man's abilities, limitations, and characteristic reactions to weightless space flight was analyzed and simulation models were developed. The predictive capabilities of simulation models for fluid-electrolyte regulation, erythropoiesis regulation, and calcium regulation are discussed.

Reasoning, learning, and creativity: frontal lobe function and human decision-making.

PubMed

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

Modeling the compensatory response of an invasive tree to specialist insect herbivory

USGS Publications Warehouse

Zhang, Bo; Liu, Xin; DeAngelis, Donald L.; Zhai, Lu; Rayamajhi, Min B.; Ju, Shu

2018-01-01

The severity of the effects of herbivory on plant fitness can be moderated by the ability of plants to compensate for biomass loss. Compensation is an important component of the ecological fitness in many plants, and has been shown to reduce the effects of pests on agricultural plant yields. It can also reduce the effectiveness of biocontrol through introduced herbivores in controlling weedy invasive plants. This study used a modeling approach to predict the effect of different levels of foliage herbivory by biological control agents introduced to control the invasive tree Melaleuca quinquennervia (melaleuca) in Florida. It is assumed in the model that melaleuca can optimally change its carbon and nitrogen allocation strategies in order to compensate for the effects of herbivory. The model includes reallocation of more resources to production and maintenance of photosynthetic tissues at the expense of roots. This compensation is shown to buffer the severity of the defoliation effect, but the model predicts a limit on the maximum herbivory that melaleuca can tolerate and survive. The model also shows that the level of available limiting nutrient (e.g., soil nitrogen) may play an important role in a melaleuca’s ability to compensate for herbivory. This study has management implications for the best ways to maximize the level of damage using biological control or other means of defoliation.

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

PubMed Central

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

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…

Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Burley, Casey L.; Tinetti, Ana; Rawls, John W.

2008-01-01

This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

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

Reduced growth due to belowground sink limitation is not fully explained by reduced photosynthesis.

PubMed

Campany, Courtney E; Medlyn, Belinda E; Duursma, Remko A

2017-08-01

Sink limitation is known to reduce plant growth, but it is not known how plant carbon (C) balance is affected, limiting our ability to predict growth under sink-limited conditions. We manipulated soil volume to impose sink limitation of growth in Eucalyptus tereticornis Sm. seedlings. Seedlings were grown in the field in containers of different sizes and planted flush to the soil alongside freely rooted (Free) seedlings. Container volume negatively affected aboveground growth throughout the experiment, and light saturated rates of leaf photosynthesis were consistently lower in seedlings in containers (-26%) compared with Free seedlings. Significant reductions in photosynthetic capacity in containerized seedlings were related to both reduced leaf nitrogen content and starch accumulation, indicating direct effects of sink limitation on photosynthetic downregulation. After 120 days, harvested biomass of Free seedlings was on average 84% higher than seedlings in containers, but biomass distribution in leaves, stems and roots was not different. However, the reduction in net leaf photosynthesis over the growth period was insufficient to explain the reduction in growth, so that we also observed an apparent reduction in whole-plant C-use efficiency (CUE) between Free seedlings and seedlings in containers. Our results show that sink limitation affects plant growth through feedbacks to both photosynthesis and CUE. Mass balance approaches to predicting plant growth under sink-limited conditions need to incorporate both of these feedbacks. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Ability of the total strain version of strainrange partitioning to characterize thermomechanical fatigue behavior

NASA Technical Reports Server (NTRS)

Saltsman, James F.; Halford, Gary R.

1994-01-01

Strainrange partitioning (SRP) was originally developed on an inelastic strain basis for isothermal fatigue in the high-strain regime where the inelastic strainrange could be determined accurately. However, most power-generating equipment operates in the regime where the inelastic strains are small and difficult to determine with any degree of accuracy. This shortcoming led to the development of the total strain version of SRP (TS-SRP). Power-generating equipment seldom operates under isothermal conditions, and isothermal life prediction methods cannot be depended on to predict the lives of anisothermal cycles. To overcome this shortcoming, a method was proposed for extending TS-SRP to characterize anisothermal fatigue behavior and to predict the lives of thermomechanical fatigue (TMF) cycles using apppropriate anisothermal data. The viability of this method, referred to as TMF/TS-SRP, was demonstrated using TMF data for two high-temperature aerospace alloys. In this report, data from the literature are used to examine the ability of TMF/TS-SRP to characterize the failure and flow behavior of three low-strength, high-ductility alloys widely used for ground-based power-generating equipment. The three alloys are type 304 stainless steel, 1Cr-1Mo-0.25V steel, and 2.25Cr-1Mo steel. Because of the limited nature of the data, it was possible to evaluate the characterization, but not the predictive capability of TMF/TS-SRP.

Origins of magic: review of genetic and epigenetic effects.

PubMed

Ramagopalan, Sreeram V; Knight, Marian; Ebers, George C; Knight, Julian C

2007-12-22

To assess the evidence for a genetic basis to magic. Literature review. Harry Potter novels of J K Rowling. Muggles, witches, wizards, and squibs. Limited. Family and twin studies, magical ability, and specific magical skills. Magic shows strong evidence of heritability, with familial aggregation and concordance in twins. Evidence suggests magical ability to be a quantitative trait. Specific magical skills, notably being able to speak to snakes, predict the future, and change hair colour, all seem heritable. A multilocus model with a dominant gene for magic might exist, controlled epistatically by one or more loci, possibly recessive in nature. Magical enhancers regulating gene expressionmay be involved, combined with mutations at specific genes implicated in speech and hair colour such as FOXP2 and MCR1.

Elevated CO(2) and nitrogen effects on a dominant N(2)- fixing shrub

NASA Astrophysics Data System (ADS)

Wallace, Alison Marie

The responses of N2-fixing species to global change are likely to be an important component in predicting the existence and direction of feedbacks between carbon and nitrogen cycles, as both are radically changing at an unprecedented pace. Increased carbon storage may be more likely in ecosystems not limited by available nitrogen, such as those with abundant N2-fixing species. If elevated CO2 affects growth and N2-fixation of dominant N2-fixers, then non-fixers in the system may experience indirect effects through changes in competitive interactions and nitrogen availability. The goal of this research was to investigate these effects on the growth, competitive ability, leaf and litter chemistry, and litter decomposition of Lupinus arboreus, a N2-fixing evergreen shrub, and to test the central hypothesis that an increase in growth and competitive ability would occur at low nitrogen and high CO2. In a growth chamber experiment, three CO2 levels, 350, 500, and 650 ppm were crossed with two nitrogen levels. Lupins were grown alone or in competition with an introduced annual grass, Bromus diandrus. Contrary to findings from previous studies of positive growth and competition responses by N2-fixers, Lupinus seedlings demonstrated no significant responses to CO2. Nitrogen was far more important than CO2 in affecting relative competitive ability. Nitrogen, alkaloids, and C:N ratios in fresh foliage did not change with CO2 or nitrogen. Carbon and biomass increased slightly in lupins at 500 ppm only, suggesting an early but limited growth response. Nitrogen did decrease in lupin litter at elevated CO2, but there were no effects on litter decomposition rates in the field. Simulations by the CENTURY surface litter decomposition model predicted the litter decomposition rates of field-grown litter nearly perfectly, and predicted the general direction but underestimated the rate of litter from the greenhouse grown at different CO2 levels. Very low or high nitrogen decreased growth and competitive ability of lupin seedlings in an additional greenhouse experiment. Slight increases of nitrogen in the field did not affect lupin aboveground biomass. In conclusion, it is unlikely that Lupinus abundance or rate of its nitrogen inputs will be affected by elevated CO2 and/or changes in nitrogen availability.

B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies

PubMed Central

Sinner, Moritz F.; Stepas, Katherine A.; Moser, Carlee B.; Krijthe, Bouwe P.; Aspelund, Thor; Sotoodehnia, Nona; Fontes, João D.; Janssens, A. Cecile J.W.; Kronmal, Richard A.; Magnani, Jared W.; Witteman, Jacqueline C.; Chamberlain, Alanna M.; Lubitz, Steven A.; Schnabel, Renate B.; Vasan, Ramachandran S.; Wang, Thomas J.; Agarwal, Sunil K.; McManus, David D.; Franco, Oscar H.; Yin, Xiaoyan; Larson, Martin G.; Burke, Gregory L.; Launer, Lenore J.; Hofman, Albert; Levy, Daniel; Gottdiener, John S.; Kääb, Stefan; Couper, David; Harris, Tamara B.; Astor, Brad C.; Ballantyne, Christie M.; Hoogeveen, Ron C.; Arai, Andrew E.; Soliman, Elsayed Z.; Ellinor, Patrick T.; Stricker, Bruno H.C.; Gudnason, Vilmundur; Heckbert, Susan R.; Pencina, Michael J.; Benjamin, Emelia J.; Alonso, Alvaro

2014-01-01

Aims B-type natriuretic peptide (BNP) and C-reactive protein (CRP) predict atrial fibrillation (AF) risk. However, their risk stratification abilities in the broad community remain uncertain. We sought to improve risk stratification for AF using biomarker information. Methods and results We ascertained AF incidence in 18 556 Whites and African Americans from the Atherosclerosis Risk in Communities Study (ARIC, n=10 675), Cardiovascular Health Study (CHS, n = 5043), and Framingham Heart Study (FHS, n = 2838), followed for 5 years (prediction horizon). We added BNP (ARIC/CHS: N-terminal pro-B-type natriuretic peptide; FHS: BNP), CRP, or both to a previously reported AF risk score, and assessed model calibration and predictive ability [C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI)]. We replicated models in two independent European cohorts: Age, Gene/Environment Susceptibility Reykjavik Study (AGES), n = 4467; Rotterdam Study (RS), n = 3203. B-type natriuretic peptide and CRP were significantly associated with AF incidence (n = 1186): hazard ratio per 1-SD ln-transformed biomarker 1.66 [95% confidence interval (CI), 1.56–1.76], P < 0.0001 and 1.18 (95% CI, 1.11–1.25), P < 0.0001, respectively. Model calibration was sufficient (BNP, χ2 = 17.0; CRP, χ2 = 10.5; BNP and CRP, χ2 = 13.1). B-type natriuretic peptide improved the C-statistic from 0.765 to 0.790, yielded an IDI of 0.027 (95% CI, 0.022–0.032), a relative IDI of 41.5%, and a continuous NRI of 0.389 (95% CI, 0.322–0.455). The predictive ability of CRP was limited (C-statistic increment 0.003). B-type natriuretic peptide consistently improved prediction in AGES and RS. Conclusion B-type natriuretic peptide, not CRP, substantially improved AF risk prediction beyond clinical factors in an independently replicated, heterogeneous population. B-type natriuretic peptide may serve as a benchmark to evaluate novel putative AF risk biomarkers. PMID:25037055

Machine Learning for Flood Prediction in Google Earth Engine

NASA Astrophysics Data System (ADS)

Kuhn, C.; Tellman, B.; Max, S. A.; Schwarz, B.

2015-12-01

With the increasing availability of high-resolution satellite imagery, dynamic flood mapping in near real time is becoming a reachable goal for decision-makers. This talk describes a newly developed framework for predicting biophysical flood vulnerability using public data, cloud computing and machine learning. Our objective is to define an approach to flood inundation modeling using statistical learning methods deployed in a cloud-based computing platform. Traditionally, static flood extent maps grounded in physically based hydrologic models can require hours of human expertise to construct at significant financial cost. In addition, desktop modeling software and limited local server storage can impose restraints on the size and resolution of input datasets. Data-driven, cloud-based processing holds promise for predictive watershed modeling at a wide range of spatio-temporal scales. However, these benefits come with constraints. In particular, parallel computing limits a modeler's ability to simulate the flow of water across a landscape, rendering traditional routing algorithms unusable in this platform. Our project pushes these limits by testing the performance of two machine learning algorithms, Support Vector Machine (SVM) and Random Forests, at predicting flood extent. Constructed in Google Earth Engine, the model mines a suite of publicly available satellite imagery layers to use as algorithm inputs. Results are cross-validated using MODIS-based flood maps created using the Dartmouth Flood Observatory detection algorithm. Model uncertainty highlights the difficulty of deploying unbalanced training data sets based on rare extreme events.

Predictive models in cancer management: A guide for clinicians.

PubMed

Kazem, Mohammed Ali

2017-04-01

Predictive tools in cancer management are used to predict different outcomes including survival probability or risk of recurrence. The uptake of these tools by clinicians involved in cancer management has not been as common as other clinical tools, which may be due to the complexity of some of these tools or a lack of understanding of how they can aid decision-making in particular clinical situations. The aim of this article is to improve clinicians' knowledge and understanding of predictive tools used in cancer management, including how they are built, how they can be applied to medical practice, and what their limitations may be. Literature review was conducted to investigate the role of predictive tools in cancer management. All predictive models share similar characteristics, but depending on the type of the tool its ability to predict an outcome will differ. Each type has its own pros and cons, and its generalisability will depend on the cohort used to build the tool. These factors will affect the clinician's decision whether to apply the model to their cohort or not. Before a model is used in clinical practice, it is important to appreciate how the model is constructed, what its use may add over and above traditional decision-making tools, and what problems or limitations may be associated with it. Understanding all the above is an important step for any clinician who wants to decide whether or not use predictive tools in their practice. Copyright © 2016 Royal College of Surgeons of Edinburgh (Scottish charity number SC005317) and Royal College of Surgeons in Ireland. Published by Elsevier Ltd. All rights reserved.

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.

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.

Can we predict functional decline in hospitalized older people admitted through the emergency department? Reanalysis of a predictive tool ten years after its conception.

PubMed

De Brauwer, Isabelle; Cornette, Pascale; Boland, Benoît; Verschuren, Franck; D'Hoore, William

2017-05-12

In the Emergency Department (ED), early and rapid identification of older people at risk of adverse outcomes, who could best benefit from complex geriatric intervention, would avoid wasting time, especially in terms of prevention of adverse outcomes, and ensure optimal orientation of vulnerable patients. We wanted to test the predictive ability of a screening tool assessing risk of functional decline (FD), named SHERPA, 10 years after its conception, and to assess the added value of other clinical or biological factors associated with FD. A prospective cohort study of older patients (n = 305, ≥ 75 years) admitted through the emergency department, for at least 48 h in non-geriatric wards (mean age 82.5 ± 4.9, 55% women). SHERPA variables (i.e. age, pre-admission instrumental Activity of Daily Living (ADL) status, falls within a year, self-rated health and 21-point MMSE) were collected within 48 h of admission, along with socio-demographic, medical and biological data. Functional status was followed at 3 months by phone. FD was defined as a decrease at 3 months of at least one point in the pre-admission basic ADL score. Predictive ability of SHERPA was assessed using c-statistic, predictive values and likelihood ratios. Measures of discrimination improvement were Net Reclassification Improvement and Integrated Discrimination Improvement. One hundred and five patients (34%) developed 3-month FD. Predictive ability of SHERPA decreased dramatically over 10 years (c = 0.73 vs. 0.64). Only two of its constitutive variables, i.e. falls and instrumental ADL, were significant in logistic regression analysis for functional decline, while 21-point MMSE was kept in the model for clinical relevance. Demographic, comorbidity or laboratory data available upon admission did not improve the SHERPA predictive yield. Prediction of FD with SHERPA is difficult, but predictive factors, i.e. falls, pre-existing functional limitation and cognitive impairment, stay consistent across time and with literature. As accuracy of SHERPA and others existing screening tools for FD is moderate, using these predictors as flags instead of using composite scales can be a way to screen for high-risk patients.

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Predicting bioactive conformations and binding modes of macrocycles

NASA Astrophysics Data System (ADS)

Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen

2016-10-01

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Modeling Acceleration of a System of Two Objects Using the Concept of Limits

NASA Astrophysics Data System (ADS)

Sokolowski, Andrzej

2018-01-01

Traditional school laboratory exercises on a system of moving objects connected by strings involve deriving expressions for the system acceleration, a = (∑F )/m, and sketching a graph of acceleration vs. force. While being in the form of rational functions, these expressions present great opportunities for broadening the scope of the analysis by using a more sophisticated math apparatus—the concept of limits. Using the idea of limits allows for extending both predictions and explanations of this type of motion that are—according to Redish—essential goals of teaching physics. This type of analysis, known in physics as limiting case analysis, allows for generalizing inferences by evaluating or estimating values of algebraic functions based on its extreme inputs. In practice, such transition provides opportunities for deriving valid conclusions for cases when direct laboratory measurements are not possible. While using limits is common for scientists, the idea of applying limits in school practice is not visible, and testing students' ability in this area is also rare.

Improving prediction of fall risk among nursing home residents using electronic medical records.

PubMed

Marier, Allison; Olsho, Lauren E W; Rhodes, William; Spector, William D

2016-03-01

Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls. The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data. In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification. Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance.

PubMed

Verghese, Ashika; Garner, K G; Mattingley, Jason B; Dux, Paul E

2016-03-02

The ability to perform multiple, concurrent tasks efficiently is a much-desired cognitive skill, but one that remains elusive due to the brain's inherent information-processing limitations. Multitasking performance can, however, be greatly improved through cognitive training (Van Selst et al., 1999, Dux et al., 2009). Previous studies have examined how patterns of brain activity change following training (for review, see Kelly and Garavan, 2005). Here, in a large-scale human behavioral and imaging study of 100 healthy adults, we tested whether multitasking training benefits, assessed using a standard dual-task paradigm, are associated with variability in brain structure. We found that the volume of the rostral part of the left dorsolateral prefrontal cortex (DLPFC) predicted an individual's response to training. Critically, this association was observed exclusively in a task-specific training group, and not in an active-training control group. Our findings reveal a link between DLPFC structure and an individual's propensity to gain from training on a task that taps the limits of cognitive control. Cognitive "brain" training is a rapidly growing, multibillion dollar industry (Hayden, 2012) that has been touted as the panacea for a variety of disorders that result in cognitive decline. A key process targeted by such training is "cognitive control." Here, we combined an established cognitive control measure, multitasking ability, with structural brain imaging in a sample of 100 participants. Our goal was to determine whether individual differences in brain structure predict the extent to which people derive measurable benefits from a cognitive training regime. Ours is the first study to identify a structural brain marker-volume of left hemisphere dorsolateral prefrontal cortex-associated with the magnitude of multitasking performance benefits induced by training at an individual level. Copyright © 2016 the authors 0270-6474/16/362638-08$15.00/0.

The predictive validity of quality of evidence grades for the stability of effect estimates was low: a meta-epidemiological study.

PubMed

Gartlehner, Gerald; Dobrescu, Andreea; Evans, Tammeka Swinson; Bann, Carla; Robinson, Karen A; Reston, James; Thaler, Kylie; Skelly, Andrea; Glechner, Anna; Peterson, Kimberly; Kien, Christina; Lohr, Kathleen N

2016-02-01

To determine the predictive validity of the U.S. Evidence-based Practice Center (EPC) approach to GRADE (Grading of Recommendations Assessment, Development and Evaluation). Based on Cochrane reports with outcomes graded as high quality of evidence (QOE), we prepared 160 documents which represented different levels of QOE. Professional systematic reviewers dually graded the QOE. For each document, we determined whether estimates were concordant with high QOE estimates of the Cochrane reports. We compared the observed proportion of concordant estimates with the expected proportion from an international survey. To determine the predictive validity, we used the Hosmer-Lemeshow test to assess calibration and the C (concordance) index to assess discrimination. The predictive validity of the EPC approach to GRADE was limited. Estimates graded as high QOE were less likely, estimates graded as low or insufficient QOE more likely to remain stable than expected. The EPC approach to GRADE could not reliably predict the likelihood that individual bodies of evidence remain stable as new evidence becomes available. C-indices ranged between 0.56 (95% CI, 0.47 to 0.66) and 0.58 (95% CI, 0.50 to 0.67) indicating a low discriminatory ability. The limited predictive validity of the EPC approach to GRADE seems to reflect a mismatch between expected and observed changes in treatment effects as bodies of evidence advance from insufficient to high QOE. Copyright © 2016 Elsevier Inc. All rights reserved.

Medicine is not science: guessing the future, predicting the past.

PubMed

Miller, Clifford

2014-12-01

Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. Irregularity and its consequences for knowledge are considered. Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is outlined. Reducing irregularity and/or increasing regularity can increase the reliability of knowledge. Beyond long experience and specialization, improvements include implementing supporting knowledge systems of libraries of appropriately classified prior cases and clinical histories and education about expertise, intuition and professional judgement. A consequence of irregularity and complexity is that classical reductionist science cannot provide reliable predictions of the behaviour of complex systems found in nature, including of the human body. Expertise, expert judgement and their exercise appear overarching. Diagnosis involves predicting the past will recur in the current patient applying expertise and intuition from knowledge and experience of previous cases and probabilistic medical theory. Treatment decisions are an educated guess about the future (prognosis). Benefits of the improvements suggested here are likely in fields where paucity of feedback for practitioners limits development of reliable expert diagnostic intuition. Further analysis, definition and classification of irregularity is appropriate. Observing and recording irregularities are initial steps in developing irregularity theory to improve the reliability and extent of knowledge, albeit some forms of irregularity present inherent difficulties. © 2014 John Wiley & Sons, Ltd.

A decision-making tool for exchange transfusions in infants with severe hyperbilirubinemia in resource-limited settings.

PubMed

Olusanya, B O; Iskander, I F; Slusher, T M; Wennberg, R P

2016-05-01

Late presentation and ineffective phototherapy account for excessive rates of avoidable exchange transfusions (ETs) in many low- and middle-income countries. Several system-based constraints sometimes limit the ability to provide timely ETs for all infants at risk of kernicterus, thus necessitating a treatment triage to optimize available resources. This article proposes a practical priority-setting model for term and near-term infants requiring ET after the first 48 h of life. The proposed model combines plasma/serum bilirubin estimation, clinical signs of acute bilirubin encephalopathy and neurotoxicity risk factors for predicting the risk of kernicterus based on available evidence in the literature.

Mapping the dark space of chemical reactions with extended nanomole synthesis and MALDI-TOF MS.

PubMed

Lin, Shishi; Dikler, Sergei; Blincoe, William D; Ferguson, Ronald D; Sheridan, Robert P; Peng, Zhengwei; Conway, Donald V; Zawatzky, Kerstin; Wang, Heather; Cernak, Tim; Davies, Ian W; DiRocco, Daniel A; Sheng, Huaming; Welch, Christopher J; Dreher, Spencer D

2018-05-24

Understanding the practical limitations of chemical reactions is critically important for efficiently planning the synthesis of compounds in pharmaceutical, agrochemical and specialty chemical research and development. However, literature reports of the scope of new reactions are often cursory and biased toward successful results, severely limiting the ability to predict reaction outcomes for untested substrates. We herein illustrate strategies for carrying out large scale surveys of chemical reactivity using a material-sparing nanomole-scale automated synthesis platform with greatly expanded synthetic scope combined with ultra-high throughput (uHT) matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). Copyright © 2018, American Association for the Advancement of Science.

Does more mean less? The value of information for conservation planning under sea level rise.

PubMed

Runting, Rebecca K; Wilson, Kerrie A; Rhodes, Jonathan R

2013-02-01

Many studies have explored the benefits of adopting more sophisticated modelling techniques or spatial data in terms of our ability to accurately predict ecosystem responses to global change. However, we currently know little about whether the improved predictions will actually lead to better conservation outcomes once the costs of gaining improved models or data are accounted for. This severely limits our ability to make strategic decisions for adaptation to global pressures, particularly in landscapes subject to dynamic change such as the coastal zone. In such landscapes, the global phenomenon of sea level rise is a critical consideration for preserving biodiversity. Here, we address this issue in the context of making decisions about where to locate a reserve system to preserve coastal biodiversity with a limited budget. Specifically, we determined the cost-effectiveness of investing in high-resolution elevation data and process-based models for predicting wetland shifts in a coastal region of South East Queensland, Australia. We evaluated the resulting priority areas for reserve selection to quantify the cost-effectiveness of investment in better quantifying biological and physical processes. We show that, in this case, it is considerably more cost effective to use a process-based model and high-resolution elevation data, even if this requires a substantial proportion of the project budget to be expended (up to 99% in one instance). The less accurate model and data set failed to identify areas of high conservation value, reducing the cost-effectiveness of the resultant conservation plan. This suggests that when developing conservation plans in areas where sea level rise threatens biodiversity, investing in high-resolution elevation data and process-based models to predict shifts in coastal ecosystems may be highly cost effective. A future research priority is to determine how this cost-effectiveness varies among different regions across the globe. © 2012 Blackwell Publishing Ltd.

Summer microhabitat use of fluvial bull trout in Eastern Oregon streams

USGS Publications Warehouse

Al-Chokhachy, R.; Budy, P.

2007-01-01

The management and recovery of populations of bull trout Salvelinus confluentus requires a comprehensive understanding of habitat use across different systems, life stages, and life history forms. To address these needs, we collected microhabitat use and availability data in three fluvial populations of bull trout in eastern Oregon. We evaluated diel differences in microhabitat use, the consistency of microhabitat use across systems and size-classes based on preference, and our ability to predict bull trout microhabitat use. Diel comparisons suggested bull trout continue to use deeper microhabitats with cover but shift into significantly slower habitats during nighttime periods; however, we observed no discrete differences in substrate use patterns across diel periods. Across life stages, we found that both juvenile and adult bull trout used slow-velocity microhabitats with cover, but the use of specific types varied. Both logistic regression and habitat preference analyses suggested that adult bull trout used deeper habitats than juveniles. Habitat preference analyses suggested that bull trout habitat use was consistent across all three systems, as chi-square tests rejected the null hypotheses that microhabitats were used in proportion to those available (P < 0.0001). Validation analyses indicated that the logistic regression models (juvenile and adult) were effective at predicting bull trout absence across all tests (specificity values = 100%); however, our ability to accurately predict bull trout absence was limited (sensitivity values = 0% across all tests). Our results highlight the limitations of the models used to predict microhabitat use for fish species like bull trout, which occur at naturally low densities. However, our results also demonstrate that bull trout microhabitat use patterns are generally consistent across systems, a pattern that parallels observations at both similar and larger scales and across life history forms. Thus, our results, in combination with previous bull trout habitat studies, provide managers with benchmarks for restoration in highly degraded systems.

Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

PubMed

Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

2017-11-21

Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Summer drought predictability over Europe: empirical versus dynamical forecasts

NASA Astrophysics Data System (ADS)

Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

2017-08-01

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

INTEGRATED CHEMICAL INFORMATION TECHNOLOGIES ...

EPA Pesticide Factsheets

A central regulatory mandate of the Environmental Protection Agency, spanning many Program Offices and issues, is to assess the potential health and environmental risks of large numbers of chemicals released into the environment, often in the absence of relevant test data. Models for predicting potential adverse effects of chemicals based primarily on chemical structure play a central role in prioritization and screening strategies yet are highly dependent and conditional upon the data used for developing such models. Hence, limits on data quantity, quality, and availability are considered by many to be the largest hurdles to improving prediction models in diverse areas of toxicology. Generation of new toxicity data for additional chemicals and endpoints, development of new high-throughput, mechanistically relevant bioassays, and increased generation of genomics and proteomics data that can clarify relevant mechanisms will all play important roles in improving future SAR prediction models. The potential for much greater immediate gains, across large domains of chemical and toxicity space, comes from maximizing the ability to mine and model useful information from existing toxicity data, data that represent huge past investment in research and testing expenditures. In addition, the ability to place newer “omics” data, data that potentially span many possible domains of toxicological effects, in the broader context of historical data is the means for opti

An appraisal of the psychometric properties of the Clinician version of the Apathy Evaluation Scale (AES-C).

PubMed

Clarke, Diana E; Van Reekum, Robert; Patel, Jigisha; Simard, Martine; Gomez, Everlyne; Streiner, David L

2007-01-01

This article examines the psychometric properties of the clinician version of the Apathy Evaluation Scale (AES-C) to determine its ability to characterize, quantify and differentiate apathy. Critical appraisals of the item-reduction processes, effectiveness of the administration, coding and scoring procedures, and the reliability and validity of the scale were carried out. For training, administration and rating of the AES-C, clearer guidelines, including a more standardized list of verbal and non-verbal apathetic cues, are needed. There is evidence of high internal consistency for the scale across studies. In addition, the original study reported good test-retest and inter-rater reliability coefficients. However, there is a lack of replication on these more stable and informative measures of reliability and as such they warrant further investigation. The research evidence confirms that the AES-C shows good discriminant, convergent and criterion validity. However, evidence of its predictive validity is limited. As this aspect of validity refers to the scale's ability to predict future outcomes, which is important for treatment and rehabilitation planning, further assessment of the predictive validity of the AES-C is needed. In conclusion, the AES-C is a reliable and valid measure for the characterization and quantification of apathy. Copyright (c) 2007 John Wiley & Sons, Ltd.

The nucleation rate surfaces design over diagram of phase equilibria and their applications for computational chemistry

NASA Astrophysics Data System (ADS)

Anisimov, M. P.

2016-12-01

One can find in scientific literature a pretty fresh idea of the nucleation rate surfaces design over the diagrams of phase equilibria. That idea looks like profitable for the nucleation theory development and for various practical applications where predictions of theory have no high enough accuracy for today. The common thermodynamics has no real ability to predict parameters of the first order phase transition. Nucleation experiment can be provided in very local nucleation conditions even the nucleation takes place from the critical line (in two-component case) down to the absolute zero temperature limit and from zero nucleation rates at phase equilibria up to the spinodal conditions. Theory predictions have low reliability as a rule. The computational chemistry has chance to make solution of that problem easier when a set of the used axiomatic statements will adapt enough progressive assumptions [1]. Semiempirical design of the nucleation rate surfaces over diagrams of phase equilibria have a potential ability to provide a reasonable quality information on nucleation rate for each channel of nucleation. Consideration and using of the nucleation rate surface topologies to optimize synthesis of a given phase of the target material can be available when data base on nucleation rates over diagrams of phase equilibria will be created.

Outcome Prediction in Mathematical Models of Immune Response to Infection.

PubMed

Mai, Manuel; Wang, Kun; Huber, Greg; Kirby, Michael; Shattuck, Mark D; O'Hern, Corey S

2015-01-01

Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs) that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.

PubMed

Canela-Xandri, Oriol; Rawlik, Konrad; Woolliams, John A; Tenesa, Albert

2016-01-01

Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models.

Sea otter research methods and tools

USGS Publications Warehouse

Bodkin, James L.; Maldini, Daniela; Calkins, Donald; Atkinson, Shannon; Meehan, Rosa

2004-01-01

Sea otters possess physical characteristics and life history attributes that provide both opportunity and constraint to their study. Because of their relatively limited diving ability they occur in nearshore marine habitats that are usually viewable from shore, allowing direct observation of most behaviors. Because sea otters live nearshore and forage on benthic invertebrates, foraging success and diet are easily measured. Because they rely almost exclusively on their pelage for insulation, which requires frequent grooming, successful application of external tags or instruments has been limited to attachments in the interdigital webbing of the hind flippers. Techniques to surgically implant instruments into the intraperitoneal cavity are well developed and routinely applied. Because they have relatively small home ranges and rest in predictable areas, they can be recaptured with some predictability using closed-circuit scuba diving technology. The purpose of this summary is to identify some of the approaches, methods, and tools that are currently engaged for the study of sea otters, and to suggest potential avenues for applying advancing technologies.

Spatial complementarity and the coexistence of species.

PubMed

Velázquez, Jorge; Garrahan, Juan P; Eichhorn, Markus P

2014-01-01

Coexistence of apparently similar species remains an enduring paradox in ecology. Spatial structure has been predicted to enable coexistence even when population-level models predict competitive exclusion if it causes each species to limit its own population more than that of its competitor. Nevertheless, existing hypotheses conflict with regard to whether clustering favours or precludes coexistence. The spatial segregation hypothesis predicts that in clustered populations the frequency of intra-specific interactions will be increased, causing each species to be self-limiting. Alternatively, individuals of the same species might compete over greater distances, known as heteromyopia, breaking down clusters and opening space for a second species to invade. In this study we create an individual-based model in homogeneous two-dimensional space for two putative sessile species differing only in their demographic rates and the range and strength of their competitive interactions. We fully characterise the parameter space within which coexistence occurs beyond population-level predictions, thereby revealing a region of coexistence generated by a previously-unrecognised process which we term the triadic mechanism. Here coexistence occurs due to the ability of a second generation of offspring of the rarer species to escape competition from their ancestors. We diagnose the conditions under which each of three spatial coexistence mechanisms operates and their characteristic spatial signatures. Deriving insights from a novel metric - ecological pressure - we demonstrate that coexistence is not solely determined by features of the numerically-dominant species. This results in a common framework for predicting, given any pair of species and knowledge of the relevant parameters, whether they will coexist, the mechanism by which they will do so, and the resultant spatial pattern of the community. Spatial coexistence arises from complementary combinations of traits in each species rather than solely through self-limitation.

Spatial Complementarity and the Coexistence of Species

PubMed Central

Velázquez, Jorge; Garrahan, Juan P.; Eichhorn, Markus P.

2014-01-01

Coexistence of apparently similar species remains an enduring paradox in ecology. Spatial structure has been predicted to enable coexistence even when population-level models predict competitive exclusion if it causes each species to limit its own population more than that of its competitor. Nevertheless, existing hypotheses conflict with regard to whether clustering favours or precludes coexistence. The spatial segregation hypothesis predicts that in clustered populations the frequency of intra-specific interactions will be increased, causing each species to be self-limiting. Alternatively, individuals of the same species might compete over greater distances, known as heteromyopia, breaking down clusters and opening space for a second species to invade. In this study we create an individual-based model in homogeneous two-dimensional space for two putative sessile species differing only in their demographic rates and the range and strength of their competitive interactions. We fully characterise the parameter space within which coexistence occurs beyond population-level predictions, thereby revealing a region of coexistence generated by a previously-unrecognised process which we term the triadic mechanism. Here coexistence occurs due to the ability of a second generation of offspring of the rarer species to escape competition from their ancestors. We diagnose the conditions under which each of three spatial coexistence mechanisms operates and their characteristic spatial signatures. Deriving insights from a novel metric — ecological pressure — we demonstrate that coexistence is not solely determined by features of the numerically-dominant species. This results in a common framework for predicting, given any pair of species and knowledge of the relevant parameters, whether they will coexist, the mechanism by which they will do so, and the resultant spatial pattern of the community. Spatial coexistence arises from complementary combinations of traits in each species rather than solely through self-limitation. PMID:25532018

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

Developing predictive models for return to work using the Military Power, Performance and Prevention (MP3) musculoskeletal injury risk algorithm: a study protocol for an injury risk assessment programme.

PubMed

Rhon, Daniel I; Teyhen, Deydre S; Shaffer, Scott W; Goffar, Stephen L; Kiesel, Kyle; Plisky, Phil P

2018-02-01

Musculoskeletal injuries are a primary source of disability in the US Military, and low back pain and lower extremity injuries account for over 44% of limited work days annually. History of prior musculoskeletal injury increases the risk for future injury. This study aims to determine the risk of injury after returning to work from a previous injury. The objective is to identify criteria that can help predict likelihood for future injury or re-injury. There will be 480 active duty soldiers recruited from across four medical centres. These will be patients who have sustained a musculoskeletal injury in the lower extremity or lumbar/thoracic spine, and have now been cleared to return back to work without any limitations. Subjects will undergo a battery of physical performance tests and fill out sociodemographic surveys. They will be followed for a year to identify any musculoskeletal injuries that occur. Prediction algorithms will be derived using regression analysis from performance and sociodemographic variables found to be significantly different between injured and non-injured subjects. Due to the high rates of injuries, injury prevention and prediction initiatives are growing. This is the first study looking at predicting re-injury rates after an initial musculoskeletal injury. In addition, multivariate prediction models appear to have move value than models based on only one variable. This approach aims to validate a multivariate model used in healthy non-injured individuals to help improve variables that best predict the ability to return to work with lower risk of injury, after a recent musculoskeletal injury. NCT02776930. 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/.

Modelling approaches for pipe inclination effect on deposition limit velocity of settling slurry flow

NASA Astrophysics Data System (ADS)

Matoušek, Václav; Kesely, Mikoláš; Vlasák, Pavel

2018-06-01

The deposition velocity is an important operation parameter in hydraulic transport of solid particles in pipelines. It represents flow velocity at which transported particles start to settle out at the bottom of the pipe and are no longer transported. A number of predictive models has been developed to determine this threshold velocity for slurry flows of different solids fractions (fractions of different grain size and density). Most of the models consider flow in a horizontal pipe only, modelling approaches for inclined flows are extremely scarce due partially to a lack of experimental information about the effect of pipe inclination on the slurry flow pattern and behaviour. We survey different approaches to modelling of particle deposition in flowing slurry and discuss mechanisms on which deposition-limit models are based. Furthermore, we analyse possibilities to incorporate the effect of flow inclination into the predictive models and select the most appropriate ones based on their ability to modify the modelled deposition mechanisms to conditions associated with the flow inclination. A usefulness of the selected modelling approaches and their modifications are demonstrated by comparing model predictions with experimental results for inclined slurry flows from our own laboratory and from the literature.

Competitive and demographic leverage points of community shifts under climate warming

PubMed Central

Sorte, Cascade J. B.; White, J. Wilson

2013-01-01

Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns. PMID:23658199

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…

Risk prediction model for knee pain in the Nottingham community: a Bayesian modelling approach.

PubMed

Fernandes, G S; Bhattacharya, A; McWilliams, D F; Ingham, S L; Doherty, M; Zhang, W

2017-03-20

Twenty-five percent of the British population over the age of 50 years experiences knee pain. Knee pain can limit physical ability and cause distress and bears significant socioeconomic costs. The objectives of this study were to develop and validate the first risk prediction model for incident knee pain in the Nottingham community and validate this internally within the Nottingham cohort and externally within the Osteoarthritis Initiative (OAI) cohort. A total of 1822 participants from the Nottingham community who were at risk for knee pain were followed for 12 years. Of this cohort, two-thirds (n = 1203) were used to develop the risk prediction model, and one-third (n = 619) were used to validate the model. Incident knee pain was defined as pain on most days for at least 1 month in the past 12 months. Predictors were age, sex, body mass index, pain elsewhere, prior knee injury and knee alignment. A Bayesian logistic regression model was used to determine the probability of an OR >1. The Hosmer-Lemeshow χ 2 statistic (HLS) was used for calibration, and ROC curve analysis was used for discrimination. The OAI cohort from the United States was also used to examine the performance of the model. A risk prediction model for knee pain incidence was developed using a Bayesian approach. The model had good calibration, with an HLS of 7.17 (p = 0.52) and moderate discriminative ability (ROC 0.70) in the community. Individual scenarios are given using the model. However, the model had poor calibration (HLS 5866.28, p < 0.01) and poor discriminative ability (ROC 0.54) in the OAI cohort. To our knowledge, this is the first risk prediction model for knee pain, regardless of underlying structural changes of knee osteoarthritis, in the community using a Bayesian modelling approach. The model appears to work well in a community-based population but not in individuals with a higher risk for knee osteoarthritis, and it may provide a convenient tool for use in primary care to predict the risk of knee pain in the general population.

Using self-organizing maps to determine observation threshold limit predictions in highly variant data

USGS Publications Warehouse

Paganoni, C.A.; Chang, K.C.; Robblee, M.B.

2006-01-01

A significant data quality challenge for highly variant systems surrounds the limited ability to quantify operationally reasonable limits on the data elements being collected and provide reasonable threshold predictions. In many instances, the number of influences that drive a resulting value or operational range is too large to enable physical sampling for each influencer, or is too complicated to accurately model in an explicit simulation. An alternative method to determine reasonable observation thresholds is to employ an automation algorithm that would emulate a human analyst visually inspecting data for limits. Using the visualization technique of self-organizing maps (SOM) on data having poorly understood relationships, a methodology for determining threshold limits was developed. To illustrate this approach, analysis of environmental influences that drive the abundance of a target indicator species (the pink shrimp, Farfantepenaeus duorarum) provided a real example of applicability. The relationship between salinity and temperature and abundance of F. duorarum is well documented, but the effect of changes in water quality upstream on pink shrimp abundance is not well understood. The highly variant nature surrounding catch of a specific number of organisms in the wild, and the data available from up-stream hydrology measures for salinity and temperature, made this an ideal candidate for the approach to provide a determination about the influence of changes in hydrology on populations of organisms.

Using self-organizing maps to determine observation threshold limit predictions in highly variant data

NASA Astrophysics Data System (ADS)

Paganoni, Christopher A.; Chang, K. C.; Robblee, Michael B.

2006-05-01

A significant data quality challenge for highly variant systems surrounds the limited ability to quantify operationally reasonable limits on the data elements being collected and provide reasonable threshold predictions. In many instances, the number of influences that drive a resulting value or operational range is too large to enable physical sampling for each influencer, or is too complicated to accurately model in an explicit simulation. An alternative method to determine reasonable observation thresholds is to employ an automation algorithm that would emulate a human analyst visually inspecting data for limits. Using the visualization technique of self-organizing maps (SOM) on data having poorly understood relationships, a methodology for determining threshold limits was developed. To illustrate this approach, analysis of environmental influences that drive the abundance of a target indicator species (the pink shrimp, Farfantepenaeus duorarum) provided a real example of applicability. The relationship between salinity and temperature and abundance of F. duorarum is well documented, but the effect of changes in water quality upstream on pink shrimp abundance is not well understood. The highly variant nature surrounding catch of a specific number of organisms in the wild, and the data available from up-stream hydrology measures for salinity and temperature, made this an ideal candidate for the approach to provide a determination about the influence of changes in hydrology on populations of organisms.

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

PubMed

Correa, John B; Apolzan, John W; Shepard, Desti N; Heil, Daniel P; Rood, Jennifer C; Martin, Corby K

2016-07-01

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity.

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure

PubMed Central

Correa, John B.; Apolzan, John W.; Shepard, Desti N.; Heil, Daniel P.; Rood, Jennifer C.; Martin, Corby K.

2016-01-01

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland–Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity. PMID:27270210

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

PubMed Central

Cordero, David; Riccadonna, Samantha; Solé, Xavier; Crous-Bou, Marta; Guinó, Elisabet; Sanjuan, Xavier; Biondo, Sebastiano; Soriano, Antonio; Jurman, Giuseppe; Capella, Gabriel; Furlanello, Cesare; Moreno, Victor

2012-01-01

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. PMID:23145004

Predictability and Prediction of Low-Frequency Rainfall Over the Lower Reaches of the Yangtze River Valley on the Time Scale of 20 to 30 days

NASA Astrophysics Data System (ADS)

Yang, Qiuming

2018-01-01

This paper presents a predictability study of the 20-30-day low-frequency rainfall over the lower reaches of the Yangtze River valley (LYRV). This study relies on an extended complex autoregressive (ECAR) model method, which is based on the principal components of the global 850 hPa low-frequency meridional wind. ECAR is a recently advanced climate forecast method, based on data-driven models. It not only reflects the lagged variations information between the leading low-frequency components of the global circulation and rainfall in a complex space, but also displays the ability to describe the synergy variations of low-frequency components of a climate system in a low dimensional space. A 6-year forecast experiment is conducted on the low-frequency rainfall over the LYRV for the extended-range daily forecasts during 2009-2014, based on the time-varying high-order ECAR. These experimental results demonstrate that the useful skills of the real-time forecasts are achieved for an extended lead-time up to 28 days with a fifth-order model, and are also shown to be 27-day lead for forecasts which are initiated from weak intraseasonal oscillation (ISO). This high-order ECAR displays the ability to significantly improve the predictions of the ISO. The analysis of the 20-30-day ISO predictability reveals a predictability limit of about 28-40 days. Therefore, the forecast framework used in this study is determined to have the potential to assist in improving the real-time forecasts for the 20-30-day oscillations related to the heavy rainfall over the LYRV in summer.

Vulnerability to climate warming of Liolaemus pictus (Squamata, Liolaemidae), a lizard from the cold temperate climate in Patagonia, Argentina.

PubMed

Kubisch, Erika Leticia; Fernández, Jimena Beatriz; Ibargüengoytía, Nora Ruth

2016-02-01

The vulnerability of populations and species to global warming depends not only on the environmental temperatures, but also on the behavioral and physiological abilities to respond to these changes. In this sense, the knowledge of an organism's sensitivity to temperature variation is essential to predict potential responses to climate warming. In particular, it is interesting to know how close species are to their thermal limits in nature and whether physiological plasticity is a potential short-term response to warming climates. We exposed Liolaemus pictus lizards, from northern Patagonia, to either 21 or 31 °C for 30 days to compare the effects of these treatments on thermal sensitivity in 1 and 0.2 m runs, preferred body temperature (T pref), panting threshold (T pant), and critical minimum temperature (CTMin). Furthermore, we measured the availability of thermal microenvironments (operative temperatures; T e) to measure how close L. pictus is, in nature, to its optimal locomotor performance (T o) and thermal limits. L. pictus showed limited physiological plasticity, since the acclimation temperature (21 and 31 °C) did not affect the locomotor performance nor did it affect T pref, the T pant, or the CTMin. The mean T e was close to T o and was 17 °C lower than the CTMax. The results suggest that L. pictus, in a climate change scenario, could be vulnerable to the predicted temperature increment, as this species currently lives in an environment with temperatures close to their highest locomotor temperature threshold, and because they showed limited acclimation capacity to adjust to new thermal conditions by physiological plasticity. Nevertheless, L. pictus can run at 80 % or faster of its maximum speed across a wide range of temperatures near T o, an ability which would attenuate the impact of global warming.

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth's carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O'Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

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).

Predictors of short-term outcome to exercise and manual therapy for people with hip osteoarthritis.

PubMed

French, Helen P; Galvin, Rose; Cusack, Tara; McCarthy, Geraldine M

2014-01-01

Physical therapy for hip osteoarthritis (OA) has shown short-term effects but limited long-term benefit. There has been limited research, with inconsistent results, in identifying prognostic factors associated with a positive response to physical therapy. The purpose of this study was to identify potential predictors of response to physical therapy (exercise therapy [ET] with or without adjunctive manual therapy [MT]) for hip OA based on baseline patient-specific and clinical characteristics. A prognostic study was conducted. Secondary analysis of data from a multicenter randomized controlled trial (RCT) (N=131) that evaluated the effectiveness of ET and ET+MT for hip OA was undertaken. Treatment response was defined using OMERACT/OARSI responder criteria. Ten baseline measures were used as predictor variables. Regression analyses were undertaken to identify predictors of outcome. Discriminative ability (sensitivity, specificity, and likelihood ratios) of significant variables was calculated. The RCT results showed no significant difference in most outcomes between ET and ET+MT at 9 and 18 weeks posttreatment. Forty-six patients were classified as responders at 9 weeks, and 36 patients were classified as responders at 18 weeks. Four baseline variables were predictive of a positive outcome at 9 weeks: male sex, pain with activity (<6/10), Western Ontario and McMaster Universities Osteoarthritis Index physical function subscale score (<34/68), and psychological health (Hospital Anxiety and Depression Scale score <9/42). No predictor variables were identified at the 18-week follow-up. Prognostic accuracy was fair for all 4 variables (sensitivity=0.5-0.58, specificity=0.57-0.72, likelihood ratios=1.25-1.77), indicating fair discriminative ability at predicting treatment response. The short-term follow-up limits the interpretation of results, and the low number of identified responders may have resulted in possible overfitting of the predictor model. The authors were unable to identify baseline variables in patients with hip OA that indicate those most likely to respond to treatment due to low discriminative ability. Further validation studies are needed to definitively define the best predictors of response to physical therapy in people with hip OA.

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.

Current State and Future Perspectives in QSAR Models to Predict Blood- Brain Barrier Penetration in Central Nervous System Drug R&D.

PubMed

Morales, Juan F; Montoto, Sebastian Scioli; Fagiolino, Pietro; Ruiz, Maria E

2017-01-01

The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery and development, since neurotherapeutic agents with molecular targets in the CNS should be able to cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse effects. In this review we examine and discuss QSAR approaches and current availability of experimental data for the construction of BBB permeability predictive models, focusing on the modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on two possible strategies to overcome the current limitations of in silico models: considering the prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through accurate and standardized experimental techniques.

Predicting New Materials for Hydrogen Storage Application

PubMed Central

Vajeeston, Ponniah; Ravindran, Ponniah; Fjellvåg, Helmer

2009-01-01

Knowledge about the ground-state crystal structure is a prerequisite for the rational understanding of solid-state properties of new materials. To act as an efficient energy carrier, hydrogen should be absorbed and desorbed in materials easily and in high quantities. Owing to the complexity in structural arrangements and difficulties involved in establishing hydrogen positions by x-ray diffraction methods, the structural information of hydrides are very limited compared to other classes of materials (like oxides, intermetallics, etc.). This can be overcome by conducting computational simulations combined with selected experimental study which can save environment, money, and man power. The predicting capability of first-principles density functional theory (DFT) is already well recognized and in many cases structural and thermodynamic properties of single/multi component system are predicted. This review will focus on possible new classes of materials those have high hydrogen content, demonstrate the ability of DFT to predict crystal structure, and search for potential meta-stable phases. Stabilization of such meta-stable phases is also discussed.

Exploring predictive performance: A reanalysis of the geospace model transition challenge

NASA Astrophysics Data System (ADS)

Welling, D. T.; Anderson, B. J.; Crowley, G.; Pulkkinen, A. A.; Rastätter, L.

2017-01-01

The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict surface dB/dt as a function of upstream solar drivers. This was an important step in the assessment of research models for predicting and ultimately preventing the damaging effects of geomagnetically induced currents. Many questions remain concerning the capabilities of these models. This study presents a reanalysis of the Pulkkinen et al. (2013) results in an attempt to better understand the models' performance. The range of validity of the models is determined by examining the conditions corresponding to the empirical input data. It is found that the empirical conductance models on which global magnetohydrodynamic models rely are frequently used outside the limits of their input data. The prediction error for the models is sorted as a function of solar driving and geomagnetic activity. It is found that all models show a bias toward underprediction, especially during active times. These results have implications for future research aimed at improving operational forecast models.

When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation

PubMed Central

Lee, Jurim; Park, Nuri; Choo, Jaegul; Kim, Jong-Hyun; Kim, Chang Hun

2017-01-01

Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016. PMID:28498843

When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation.

PubMed

Kim, Young Bin; Lee, Jurim; Park, Nuri; Choo, Jaegul; Kim, Jong-Hyun; Kim, Chang Hun

2017-01-01

Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016.

Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated ‘Omics Approach

PubMed Central

Lindemann, Stephen R.; Mobberley, Jennifer M.; Cole, Jessica K.; Markillie, L. M.; Taylor, Ronald C.; Huang, Eric; Chrisler, William B.; Wiley, H. S.; Lipton, Mary S.; Nelson, William C.; Fredrickson, James K.; Romine, Margaret F.

2017-01-01

The principles governing acquisition and interspecies exchange of nutrients in microbial communities and how those exchanges impact community productivity are poorly understood. Here, we examine energy and macronutrient acquisition in unicyanobacterial consortia for which species-resolved genome information exists for all members, allowing us to use multi-omic approaches to predict species’ abilities to acquire resources and examine expression of resource-acquisition genes during succession. Metabolic reconstruction indicated that a majority of heterotrophic community members lacked the genes required to directly acquire the inorganic nutrients provided in culture medium, suggesting high metabolic interdependency. The sole primary producer in consortium UCC-O, cyanobacterium Phormidium sp. OSCR, displayed declining expression of energy harvest, carbon fixation, and nitrate and sulfate reduction proteins but sharply increasing phosphate transporter expression over 28 days. Most heterotrophic members likewise exhibited signs of phosphorus starvation during succession. Though similar in their responses to phosphorus limitation, heterotrophs displayed species-specific expression of nitrogen acquisition genes. These results suggest niche partitioning around nitrogen sources may structure the community when organisms directly compete for limited phosphate. Such niche complementarity around nitrogen sources may increase community diversity and productivity in phosphate-limited phototrophic communities. PMID:28659875

Patterns and Limitations of Urban Human Mobility Resilience under the Influence of Multiple Types of Natural Disaster

PubMed Central

Wang, Qi; Taylor, John E.

2016-01-01

Natural disasters pose serious threats to large urban areas, therefore understanding and predicting human movements is critical for evaluating a population’s vulnerability and resilience and developing plans for disaster evacuation, response and relief. However, only limited research has been conducted into the effect of natural disasters on human mobility. This study examines how natural disasters influence human mobility patterns in urban populations using individuals’ movement data collected from Twitter. We selected fifteen destructive cases across five types of natural disaster and analyzed the human movement data before, during, and after each event, comparing the perturbed and steady state movement data. The results suggest that the power-law can describe human mobility in most cases and that human mobility patterns observed in steady states are often correlated with those in perturbed states, highlighting their inherent resilience. However, the quantitative analysis shows that this resilience has its limits and can fail in more powerful natural disasters. The findings from this study will deepen our understanding of the interaction between urban dwellers and civil infrastructure, improve our ability to predict human movement patterns during natural disasters, and facilitate contingency planning by policymakers. PMID:26820404

Prediction of the thermal imaging minimum resolvable (circle) temperature difference with neural network application.

PubMed

Fang, Yi-Chin; Wu, Bo-Wen

2008-12-01

Thermal imaging is an important technology in both national defense and the private sector. An advantage of thermal imaging is its ability to be deployed while fully engaged in duties, not limited by weather or the brightness of indoor or outdoor conditions. However, in an outdoor environment, many factors, including atmospheric decay, target shape, great distance, fog, temperature out of range and diffraction limits can lead to bad image formation, which directly affects the accuracy of object recognition. The visual characteristics of the human eye mean that it has a much better capacity for picture recognition under normal conditions than artificial intelligence does. However, conditions of interference significantly reduce this capacity for picture recognition for instance, fatigue impairs human eyesight. Hence, psychological and physiological factors can affect the result when the human eye is adopted to measure MRTD (minimum resolvable temperature difference) and MRCTD (minimum resolvable circle temperature difference). This study explores thermal imaging recognition, and presents a method for effectively choosing the characteristic values and processing the images fully. Neural network technology is successfully applied to recognize thermal imaging and predict MRTD and MRCTD (Appendix A), exceeding thermal imaging recognition under fatigue and the limits of the human eye.

Dispersal similarly shapes both population genetics and community patterns in the marine realm

NASA Astrophysics Data System (ADS)

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-06-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

Patterns and Limitations of Urban Human Mobility Resilience under the Influence of Multiple Types of Natural Disaster.

PubMed

Wang, Qi; Taylor, John E

2016-01-01

Natural disasters pose serious threats to large urban areas, therefore understanding and predicting human movements is critical for evaluating a population's vulnerability and resilience and developing plans for disaster evacuation, response and relief. However, only limited research has been conducted into the effect of natural disasters on human mobility. This study examines how natural disasters influence human mobility patterns in urban populations using individuals' movement data collected from Twitter. We selected fifteen destructive cases across five types of natural disaster and analyzed the human movement data before, during, and after each event, comparing the perturbed and steady state movement data. The results suggest that the power-law can describe human mobility in most cases and that human mobility patterns observed in steady states are often correlated with those in perturbed states, highlighting their inherent resilience. However, the quantitative analysis shows that this resilience has its limits and can fail in more powerful natural disasters. The findings from this study will deepen our understanding of the interaction between urban dwellers and civil infrastructure, improve our ability to predict human movement patterns during natural disasters, and facilitate contingency planning by policymakers.

Does activity limitation predict discharge destination for postacute care patients?

PubMed

Chang, Feng-Hang; Ni, Pengsheng; Jette, Alan M

2014-09-01

This study aimed to examine the ability of different domains of activity limitation to predict discharge destination (home vs. nonhome settings) 1 mo after hospital discharge for postacute rehabilitation patients. A secondary analysis was conducted using a data set of 518 adults with neurologic, lower extremity orthopedic, and complex medical conditions followed after discharge from a hospital into postacute care. Variables collected at baseline include activity limitations (basic mobility, daily activity, and applied cognitive function, measured by the Activity Measure for Post-Acute Care), demographics, diagnosis, and cognitive status. The discharge destination was recorded at 1 mo after being discharged from the hospital. Correlational analyses revealed that the 1-mo discharge destination was correlated with two domains of activity (basic mobility and daily activity) and cognitive status. However, multiple logistic regression and receiver operating characteristic curve analyses showed that basic mobility functioning performed the best in discriminating home vs. nonhome living. This study supported the evidence that basic mobility functioning is a critical determinant of discharge home for postacute rehabilitation patients. The Activity Measure for Post-Acute Care-basic mobility showed good usability in discriminating home vs. nonhome living. The findings shed light on the importance of basic mobility functioning in the discharge planning process.

Species' Traits as Predictors of Range Shifts Under Contemporary Climate Change: A Meta-analysis

NASA Astrophysics Data System (ADS)

MacLean, S. A.; Beissinger, S. R.

2016-12-01

A growing body of literature seeks to explain variation in range shifts using species' ecological and life history traits, with expectations that shifts should be greater in species with greater dispersal ability, reproductive potential, and ecological generalization. If trait-based arguments, hold, then traits would provide valuable evidence-based tools for conservation and management that could increase the accuracy of future range projections, vulnerability assessments, and predictions of novel community assemblages. However, empirical support is limited in extent and consensus, and trait-based relationships remain largely unvalidated. We conducted a comprehensive literature review of species' traits as predictors of range shifts, collecting results from over 11,000 species' responses across multiple taxa from studies that directly compared 20th century and contemporary distributions for multispecies assemblages. We then performed a meta-analysis to calculate the mean study-level effects of body size, fecundity, diet breadth, habitat breadth, and historic range limit, while directly controlling for ecological and methodological heterogeneity across studies that could bias reported effect sizes. We show that ecological and life history traits have had limited success in accounting for variation among species in range shifts over the past century. Of the five traits analyzed, only habitat breadth and historic range limit consistently supported range shift predictions across multiple studies. Fecundity, body size, and diet breadth showed no clear relationship with range shifts, and some traits identified in our literature review (e.g. migratory ecology) have consistently contradicted range shift predictions. Current understanding of species' traits as predictors of range shifts is limited, and standardized study is needed before traits can be reliably incorporated into projections of climate change impacts.

Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.

2017-01-01

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Improved regulatory element prediction based on tissue-specific local epigenomic signatures

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

He, Yupeng; Gorkin, David U.; Dickel, Diane E.

Accurate enhancer identification is critical for understanding the spatiotemporal transcriptional regulation during development as well as the functional impact of disease-related noncoding genetic variants. Computational methods have been developed to predict the genomic locations of active enhancers based on histone modifications, but the accuracy and resolution of these methods remain limited. Here, we present an algorithm, regulator y element prediction based on tissue-specific local epigenetic marks (REPTILE), which integrates histone modification and whole-genome cytosine DNA methylation profiles to identify the precise location of enhancers. We tested the ability of REPTILE to identify enhancers previously validated in reporter assays. Compared withmore » existing methods, REPTILE shows consistently superior performance across diverse cell and tissue types, and the enhancer locations are significantly more refined. We show that, by incorporating base-resolution methylation data, REPTILE greatly improves upon current methods for annotation of enhancers across a variety of cell and tissue types.« less

Implications of the difference between true and predicted breeding values for the study of natural selection and micro-evolution.

PubMed

Postma, E

2006-03-01

The ability to predict individual breeding values in natural populations with known pedigrees has provided a powerful tool to separate phenotypic values into their genetic and environmental components in a nonexperimental setting. This has allowed sophisticated analyses of selection, as well as powerful tests of evolutionary change and differentiation. To date, there has, however, been no evaluation of the reliability or potential limitations of the approach. In this article, I address these gaps. In particular, I emphasize the differences between true and predicted breeding values (PBVs), which as yet have largely been ignored. These differences do, however, have important implications for the interpretation of, firstly, the relationship between PBVs and fitness, and secondly, patterns in PBVs over time. I subsequently present guidelines I believe to be essential in the formulation of the questions addressed in studies using PBVs, and I discuss possibilities for future research.

Landscape capability predicts upland game bird abundance and occurrence

USGS Publications Warehouse

Loman, Zachary G.; Blomberg, Erik J.; DeLuca, William; Harrison, Daniel J.; Loftin, Cyndy; Wood, Petra B.

2017-01-01

Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances. 

Flow in a centrifugal fan impeller at off-design conditions

NASA Astrophysics Data System (ADS)

Wright, T.; Tzou, K. T. S.; Madhavan, S.

1984-06-01

A fully three-dimensional finite element analysis of inviscid, incompressible blade channel flow is the basis of the present study of both predicted and measured surface velocity and pressure distributions in the internal flow channels of a centrifugal fan impeller, for volume flow rates of 80-125 percent the design flow rate. The experimental results made extensive use of blade and sidewall surface pressure taps installed in a scale model of an airfoil-bladed centrifugal fan impeller. The results obtained illustrate the ability of both flow analyses to predict the dominant features of the impeller flow field, including peak blade surface velocities and adverse gradients at flows far from the design point. Insight is also gained into the limiting channel diffusion values for typical centrifugal cascade performance, together with the influence of viscous effects, as seen in deviations from ideal flow predictions.

Estimating the Reliability of Electronic Parts in High Radiation Fields

NASA Technical Reports Server (NTRS)

Everline, Chester; Clark, Karla; Man, Guy; Rasmussen, Robert; Johnston, Allan; Kohlhase, Charles; Paulos, Todd

2008-01-01

Radiation effects on materials and electronic parts constrain the lifetime of flight systems visiting Europa. Understanding mission lifetime limits is critical to the design and planning of such a mission. Therefore, the operational aspects of radiation dose are a mission success issue. To predict and manage mission lifetime in a high radiation environment, system engineers need capable tools to trade radiation design choices against system design and reliability, and science achievements. Conventional tools and approaches provided past missions with conservative designs without the ability to predict their lifetime beyond the baseline mission.This paper describes a more systematic approach to understanding spacecraft design margin, allowing better prediction of spacecraft lifetime. This is possible because of newly available electronic parts radiation effects statistics and an enhanced spacecraft system reliability methodology. This new approach can be used in conjunction with traditional approaches for mission design. This paper describes the fundamentals of the new methodology.

Working memory capacity as controlled attention in tactical decision making.

PubMed

Furley, Philip A; Memmert, Daniel

2012-06-01

The controlled attention theory of working memory capacity (WMC, Engle 2002) suggests that WMC represents a domain free limitation in the ability to control attention and is predictive of an individual's capability of staying focused, avoiding distraction and impulsive errors. In the present paper we test the predictive power of WMC in computer-based sport decision-making tasks. Experiment 1 demonstrated that high-WMC athletes were better able at focusing their attention on tactical decision making while blocking out irrelevant auditory distraction. Experiment 2 showed that high-WMC athletes were more successful at adapting their tactical decision making according to the situation instead of relying on prepotent inappropriate decisions. The present results provide additional but also unique support for the controlled attention theory of WMC by demonstrating that WMC is predictive of controlling attention in complex settings among different modalities and highlight the importance of working memory in tactical decision making.

Identifying gnostic predictors of the vaccine response

PubMed Central

Haining, W. Nicholas; Pulendran, Bali

2012-01-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis for their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of outcome classification. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. PMID:22633886

Improved regulatory element prediction based on tissue-specific local epigenomic signatures

DOE PAGES

He, Yupeng; Gorkin, David U.; Dickel, Diane E.; ...

2017-02-13

Accurate enhancer identification is critical for understanding the spatiotemporal transcriptional regulation during development as well as the functional impact of disease-related noncoding genetic variants. Computational methods have been developed to predict the genomic locations of active enhancers based on histone modifications, but the accuracy and resolution of these methods remain limited. Here, we present an algorithm, regulator y element prediction based on tissue-specific local epigenetic marks (REPTILE), which integrates histone modification and whole-genome cytosine DNA methylation profiles to identify the precise location of enhancers. We tested the ability of REPTILE to identify enhancers previously validated in reporter assays. Compared withmore » existing methods, REPTILE shows consistently superior performance across diverse cell and tissue types, and the enhancer locations are significantly more refined. We show that, by incorporating base-resolution methylation data, REPTILE greatly improves upon current methods for annotation of enhancers across a variety of cell and tissue types.« less

Predicting adverse hemodynamic events in critically ill patients.

PubMed

Yoon, Joo H; Pinsky, Michael R

2018-06-01

The art of predicting future hemodynamic instability in the critically ill has rapidly become a science with the advent of advanced analytical processed based on computer-driven machine learning techniques. How these methods have progressed beyond severity scoring systems to interface with decision-support is summarized. Data mining of large multidimensional clinical time-series databases using a variety of machine learning tools has led to our ability to identify alert artifact and filter it from bedside alarms, display real-time risk stratification at the bedside to aid in clinical decision-making and predict the subsequent development of cardiorespiratory insufficiency hours before these events occur. This fast evolving filed is primarily limited by linkage of high-quality granular to physiologic rationale across heterogeneous clinical care domains. Using advanced analytic tools to glean knowledge from clinical data streams is rapidly becoming a reality whose clinical impact potential is great.

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts.

PubMed

Bokhorst, Stef; Pedersen, Stine Højlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W; Brown, Ross D; Ehrich, Dorothee; Essery, Richard L H; Heilig, Achim; Ingvander, Susanne; Johansson, Cecilia; Johansson, Margareta; Jónsdóttir, Ingibjörg Svala; Inga, Niila; Luojus, Kari; Macelloni, Giovanni; Mariash, Heather; McLennan, Donald; Rosqvist, Gunhild Ninis; Sato, Atsushi; Savela, Hannele; Schneebeli, Martin; Sokolov, Aleksandr; Sokratov, Sergey A; Terzago, Silvia; Vikhamar-Schuler, Dagrun; Williamson, Scott; Qiu, Yubao; Callaghan, Terry V

2016-09-01

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

NASA Technical Reports Server (NTRS)

Bokhorst, Stef; Pedersen, Stine Hojlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W.; Brown, Ross D.; Ehrich, Dorothee; Essery, Richard L. H.; Heilig, Achim; Ingvander, Susanne;

Method for evaluation of predictive models of microwave ablation via post-procedural clinical imaging

NASA Astrophysics Data System (ADS)

Collins, Jarrod A.; Brown, Daniel; Kingham, T. Peter; Jarnagin, William R.; Miga, Michael I.; Clements, Logan W.

2015-03-01

Development of a clinically accurate predictive model of microwave ablation (MWA) procedures would represent a significant advancement and facilitate an implementation of patient-specific treatment planning to achieve optimal probe placement and ablation outcomes. While studies have been performed to evaluate predictive models of MWA, the ability to quantify the performance of predictive models via clinical data has been limited to comparing geometric measurements of the predicted and actual ablation zones. The accuracy of placement, as determined by the degree of spatial overlap between ablation zones, has not been achieved. In order to overcome this limitation, a method of evaluation is proposed where the actual location of the MWA antenna is tracked and recorded during the procedure via a surgical navigation system. Predictive models of the MWA are then computed using the known position of the antenna within the preoperative image space. Two different predictive MWA models were used for the preliminary evaluation of the proposed method: (1) a geometric model based on the labeling associated with the ablation antenna and (2) a 3-D finite element method based computational model of MWA using COMSOL. Given the follow-up tomographic images that are acquired at approximately 30 days after the procedure, a 3-D surface model of the necrotic zone was generated to represent the true ablation zone. A quantification of the overlap between the predicted ablation zones and the true ablation zone was performed after a rigid registration was computed between the pre- and post-procedural tomograms. While both model show significant overlap with the true ablation zone, these preliminary results suggest a slightly higher degree of overlap with the geometric model.

Computed tomography screening for lung cancer: results of ten years of annual screening and validation of cosmos prediction model.

PubMed

Veronesi, G; Maisonneuve, P; Rampinelli, C; Bertolotti, R; Petrella, F; Spaggiari, L; Bellomi, M

2013-12-01

It is unclear how long low-dose computed tomographic (LDCT) screening should continue in populations at high risk of lung cancer. We assessed outcomes and the predictive ability of the COSMOS prediction model in volunteers screened for 10 years. Smokers and former smokers (>20 pack-years), >50 years, were enrolled over one year (2000-2001), receiving annual LDCT for 10 years. The frequency of screening-detected lung cancers was compared with COSMOS and Bach risk model estimates. Among 1035 recruited volunteers (71% men, mean age 58 years) compliance was 65% at study end. Seventy-one (6.95%) lung cancers were diagnosed, 12 at baseline. Disease stage was: IA in 48 (66.6%); IB in 6; IIA in 5; IIB in 2; IIIA in 5; IIIB in 1; IV in 5; and limited small cell cancer in 3. Five- and ten-year survival were 64% and 57%, respectively, 84% and 65% for stage I. Ten (12.1%) received surgery for a benign lesion. The number of lung cancers detected during the first two screening rounds was close to that predicted by the COSMOS model, while the Bach model accurately predicted frequency from the third year on. Neither cancer frequency nor proportion at stage I decreased over 10 years, indicating that screening should not be discontinued. Most cancers were early stage, and overall survival was high. Only a limited number of invasive procedures for benign disease were performed. The Bach model - designed to predict symptomatic cancers - accurately predicted cancer frequency from the third year, suggesting that overdiagnosis is a minor problem in lung cancer screening. The COSMOS model - designed to estimate screening-detected lung cancers - accurately predicted cancer frequency at baseline and second screening round. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Electrical Resistance Technique to Monitor SiC Composite Detection

NASA Technical Reports Server (NTRS)

Smith, Craig; Morscher, Gregory; Xia, Zhenhai

2008-01-01

Ceramic matrix composites are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems. The employment of these materials in such applications is limited by the ability to process components reliable and to accurately monitor and predict damage evolution that leads to failure under stressed-oxidation conditions. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. Electrical resistance of SiC/SiC composites is one technique that shows special promise towards this end. Since both the matrix and the fibers are conductive, changes in matrix or fiber properties should relate to changes in electrical conductivity along the length of a specimen or part. The effect of matrix cracking on electrical resistivity for several composite systems will be presented and some initial measurements performed at elevated temperatures under stress-rupture conditions. The implications towards electrical resistance as a technique applied to composite processing, damage detection (health monitoring), and life-modeling will be discussed.

Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

NASA Astrophysics Data System (ADS)

Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

2016-06-01

The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

Can purchasing information be used to predict adherence to cardiovascular medications? An analysis of linked retail pharmacy and insurance claims data.

PubMed

Krumme, Alexis A; Sanfélix-Gimeno, Gabriel; Franklin, Jessica M; Isaman, Danielle L; Mahesri, Mufaddal; Matlin, Olga S; Shrank, William H; Brennan, Troyen A; Brill, Gregory; Choudhry, Niteesh K

2016-11-09

The use of retail purchasing data may improve adherence prediction over approaches using healthcare insurance claims alone. Retrospective. A cohort of patients who received prescription medication benefits through CVS Caremark, used a CVS Pharmacy ExtraCare Health Care (ECHC) loyalty card, and initiated a statin medication in 2011. We evaluated associations between retail purchasing patterns and optimal adherence to statins in the 12 subsequent months. Among 11 010 statin initiators, 43% were optimally adherent at 12 months of follow-up. Greater numbers of store visits per month and dollar amount per visit were positively associated with optimal adherence, as was making a purchase on the same day as filling a prescription (p<0.0001 for all). Models to predict adherence using retail purchase variables had low discriminative ability (C-statistic: 0.563), while models with both clinical and retail purchase variables achieved a C-statistic of 0.617. While the use of retail purchases may improve the discriminative ability of claims-based approaches, these data alone appear inadequate for adherence prediction, even with the addition of more complex analytical approaches. Nevertheless, associations between retail purchasing behaviours and adherence could inform the development of quality improvement interventions. 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/.

Farm elders define health as the ability to work.

PubMed

Reed, Deborah B; Rayens, Mary Kay; Conley, Christina K; Westneat, Susan; Adkins, Sarah M

2012-08-01

Thirty percent of America's 2.2 million farms are operated by individuals older than 65 years. This study examined how older farmers define health and determined whether demographic characteristics, farm work, and physical and mental health status predict health definition. Data were collected via telephone and mailed surveys during the baseline wave of data collection in a longitudinal study of family farmers residing in two southern states (n=1,288). Nearly 42% defined health as the "ability to work" compared to a physical health-related definition. Predictors of defining health as the ability to work included being White, performing more farm tasks in the past week, taking prescription medications daily, and having minimal health-related limitations to farm work. Health behaviors are centered on the individual's perception of health. Understanding the defining attributes of health can support better approaches to health care and health promotion, particularly among rural subcultures such as farmers, whose identity is rooted in their work. Copyright 2012, SLACK Incorporated.

Numerical Investigation of the Ability of Salt Tracers to Represent the Residence Time Distribution of Fluidized Catalytic Cracking Particles

DOE PAGES

Lu, Liqiang; Gao, Xi; Li, Tingwen; ...

2017-11-02

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models tomore » predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.« less

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

The ability of 'non-cognitive' traits to predict undergraduate performance in medical schools: a national linkage study.

PubMed

Finn, Gabrielle M; Mwandigha, Lazaro; Paton, Lewis W; Tiffin, Paul A

2018-05-03

In addition to the evaluation of educational attainment and intellectual ability there has been interest in the potential to select medical school applicants on non-academic qualities. Consequently, a battery of self-report measures concerned with assessing 'non-cognitive' traits was piloted as part of the UK Clinical Aptitude Test (UKCAT) administration to evaluate their potential to be used in selection. The four non-cognitive instruments piloted were: 1) the Libertarian-communitarian scale, (2) The NACE (narcissism, aloofness, confidence and empathy, (3) the MEARS (Managing emotions and resilience scale; self-esteem, optimism, control, self-discipline, emotional-nondefensiveness and faking, and (4) an abridged version of instruments (1) and (2) combined. Non-cognitive scores and sociodemographic characteristics were available for 14,387 applicants. A series of univariable and multivariable analyses were conducted in order to assess the ability of the non-cognitive scores to predict knowledge and skills-based performance, as well as the odds of passing each academic year at first attempt. Non-cognitive scores and medical performance were standardised within cohorts. The scores on the non-cognitive scales showed only very small (magnitude of standardised betas< 0.2), though sometimes statistically significant (p < 0.01) univariable associations with subsequent performance on knowledge or skills-based assessments. The only statistically significant association between the non-cognitive scores and the probability of passing an academic year at first attempt was the narcissism score from one the abridged tests (OR 0.84,95% confidence intervals 0.71 to 0.97, p = 0.02). Our findings are consistent with previously published research. The tests had a very limited ability to predict undergraduate academic performance, though further research on identifying narcissism in medical students may be warranted. However, the validity of such self-report tools in high-stakes settings may be affected, making such instruments unlikely to add value within the selection process.

Predictors of functional independence, quality of life, and return to work in patients with burn injuries in mainland China.

PubMed

Tang, Dan; Li-Tsang, Cecilia W P; Au, Ricky K C; Shen, Xia; Li, Kui-Cheng; Yi, Xian-Feng; Liao, Lin-Rong; Cao, Hai-Yan; Feng, Ya-Nan; Liu, Chuan-Shun

2016-01-01

Burn injury may be associated with long-term rehabilitation and disability, while research studies on the functional performance after injuries, quality of life (QOL), and abilities to return to work of burn patients are limited. These outcomes are related not just to the degree and nature of injuries, but also to the socio-economical background of the society. This study aimed to identify the factors which might affect burn patients' abilities to reintegrate back to the society based on a sample in mainland China. A retrospective study was conducted to collect data of demographic characteristics, medical data about burn injuries, physical and psychological status, and self-perceived QOL at the initial phase and upon discharge from a rehabilitation hospital, timing of rehabilitation, and duration of rehabilitation intervention. Four hundred fifteen patients with burn injuries were recruited in the study. Multiple linear regression and logistic regression were used to obtain a model to predict the functional abilities and the perceived QOL at discharge and their changes during rehabilitation, as well as the post-injury work status within 6 months after discharge. The functional performance at discharge and its change were significantly predicted by the functional abilities and QOL at the admission, duration of treatment, timing of rehabilitation, payer source, and total body surface area burned. The perceived QOL at discharge and its change were significantly predicted by the baseline QOL at admission and duration of treatment. The significant predictors of work status within 6 months post-discharge included age, education, payer source, total body surface area burned, perceived QOL, and bodily pain at admission. The present study identified a number of factors affecting the rehabilitation outcomes of people with burn injuries. Identification of these predictors may help clinicians assess the rehabilitation potential of burn survivors and assist in resource allocation. Policy makers should ensure that resources are adequate to improve the outcomes based on these factors.

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.

Competitive ability, stress tolerance and plant interactions along stress gradients.

PubMed

Qi, Man; Sun, Tao; Xue, SuFeng; Yang, Wei; Shao, DongDong; Martínez-López, Javier

2018-04-01

Exceptions to the generality of the stress-gradient hypothesis (SGH) may be reconciled by considering species-specific traits and stress tolerance strategies. Studies have tested stress tolerance and competitive ability in mediating interaction outcomes, but few have incorporated this to predict how species interactions shift between competition and facilitation along stress gradients. We used field surveys, salt tolerance and competition experiments to develop a predictive model interspecific interaction shifts across salinity stress gradients. Field survey and greenhouse tolerance tests revealed tradeoffs between stress tolerance and competitive ability. Modeling showed that along salinity gradients, (1) plant interactions shifted from competition to facilitation at high salinities within the physiological limits of salt-intolerant plants, (2) facilitation collapsed when salinity stress exceeded the physiological tolerance of salt-intolerant plants, and (3) neighbor removal experiments overestimate interspecific facilitation by including intraspecific effects. A community-level field experiment, suggested that (1) species interactions are competitive in benign and, facilitative in harsh condition, but fuzzy under medium environmental stress due to niche differences of species and weak stress amelioration, and (2) the SGH works on strong but not weak stress gradients, so SGH confusion arises when it is applied across questionable stress gradients. Our study clarifies how species interactions vary along stress gradients. Moving forward, focusing on SGH applications rather than exceptions on weak or nonexistent gradients would be most productive. © 2018 by the Ecological Society of America.

Driving simulation for evaluation and rehabilitation of driving after stroke.

PubMed

Akinwuntan, Abiodun Emmanuel; Wachtel, Jerry; Rosen, Peter Newman

2012-08-01

Driving is an important activity of daily living. Loss of driving privileges can lead to depression, decreased access to medical care, and increased healthcare costs. The ability to drive is often affected after stroke. In approximately 30% of stroke survivors, it is clear from the onset that driving will no longer be possible. Approximately 33% of survivors will be able to return to driving with little or no retraining, and 35% will require driving-related rehabilitation before they can resume safe driving again. The ability to drive is not routinely evaluated after stroke, and there is no established rehabilitation program for poststroke driving. When driving evaluation does occur, it is not always clear which tests are the most salient for accurately assessing poststroke driving ability. Investigators have examined the efficacy of various methodologies to predict driving performance after stroke and have found mixed results, with each method having unique weaknesses, including poor predictive ability, poor face validity, poor sensitivity or specificity, and limited reliability. Here we review common models of driving to gain insight into why single-construct visual or cognitive off-road measures are inadequate for evaluating driving, a complex and dynamic activity that involves timely interaction of multiple motor, visual, cognitive, and perceptual skills. We also examine the potential for driving simulators to overcome the problems currently faced in the evaluation and rehabilitation of driving after stroke. Finally, we offer suggestions for the future direction of simulator-based poststroke driving evaluation and training. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.

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

Link Prediction in Evolving Networks Based on Popularity of Nodes.

PubMed

Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

2017-08-02

Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

Development of polyparameter linear free energy relationship models for octanol-air partition coefficients of diverse chemicals.

PubMed

Jin, Xiaochen; Fu, Zhiqiang; Li, Xuehua; Chen, Jingwen

2017-03-22

The octanol-air partition coefficient (K OA ) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of K OA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for K OA . In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting K OA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log K OA values for 367 chemicals at different temperatures (263.15-323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15-323.15 K).

The utility of kindergarten teacher ratings for predicting low academic achievement in first grade.

PubMed

Teisl, J T; Mazzocco, M M; Myers, G F

2001-01-01

The purpose of this study was to assess the predictive value of kindergarten teachers' ratings of pupils for later first-grade academic achievement. Kindergarten students were rated by their teachers on a variety of variables, including math and reading performance, teacher concerns, and amount of learning relative to peers. These variables were then analyzed with respect to outcome measures for math and reading ability administered in the first grade. The teachers' ratings of academic performance were significantly correlated with scores on the outcome measures. Analyses were also carried out to determine sensitivity, specificity, and predictive values of the different teacher ratings. The results indicated high overall accuracy, sensitivity, specificity, and negative predictive value for the ratings. Positive predictive value tended to be lower. A recommendation to follow from these results is that teacher ratings of this sort be used to determine which children should receive cognitive screening measures to further enhance identification of children at risk for learning disability. However, this recommendation is limited by the lack of empirically supported screening measures for math disability versus well-supported screening tools for reading disability.

The Edinburgh Social Cognition Test (ESCoT): Examining the effects of age on a new measure of theory of mind and social norm understanding

PubMed Central

Abrahams, Sharon; Auyeung, Bonnie; MacPherson, Sarah E.

2018-01-01

Current measures of social cognition have shown inconsistent findings regarding the effects of healthy aging. Moreover, no tests are currently available that allow clinicians and researchers to examine cognitive and affective theory of mind (ToM) and understanding of social norms within the same test. To address these limitations, we present the Edinburgh Social Cognition Test (ESCoT) which assesses cognitive and affective ToM and inter- and intrapersonal understanding of social norms. We examined the effects of age, measures of intelligence and the Broader Autism Phenotype (BAP) on the ESCoT and established tests of social cognition. Additionally, we investigated the convergent validity of the ESCoT based on traditional social cognition measures. The ESCoT was administered alongside Reading the Mind in Films (RMF), Reading the Mind in Eyes (RME), Judgement of Preference and Social Norm Questionnaire to 91 participants (30 aged 18–35 years, 30 aged 45–60 years and 31 aged 65–85 years). Poorer performance on the cognitive and affective ToM ESCoT subtests were predicted by increasing age. The affective ToM ESCoT subtest and RMF were predicted by gender, where being female predicted better performance. Unlike the ESCoT, better performance on the RMF was predicted by higher verbal comprehension and perceptual reasoning abilities, while better performance on the RME was predicted by higher verbal comprehension scores. Lower scores on inter-and intrapersonal understanding of social norms were both predicted by the presence of more autism-like traits while poorer interpersonal understanding of social norms performance was predicted by increasing age. These findings show that the ESCoT is a useful measure of social cognition and, unlike established tests of social cognition, performance is not predicted by measures of verbal comprehension and perceptual reasoning. This is particularly valuable to obtain an accurate assessment of the influence of age on our social cognitive abilities. PMID:29664917

The Edinburgh Social Cognition Test (ESCoT): Examining the effects of age on a new measure of theory of mind and social norm understanding.

PubMed

Baksh, R Asaad; Abrahams, Sharon; Auyeung, Bonnie; MacPherson, Sarah E

2018-01-01

Current measures of social cognition have shown inconsistent findings regarding the effects of healthy aging. Moreover, no tests are currently available that allow clinicians and researchers to examine cognitive and affective theory of mind (ToM) and understanding of social norms within the same test. To address these limitations, we present the Edinburgh Social Cognition Test (ESCoT) which assesses cognitive and affective ToM and inter- and intrapersonal understanding of social norms. We examined the effects of age, measures of intelligence and the Broader Autism Phenotype (BAP) on the ESCoT and established tests of social cognition. Additionally, we investigated the convergent validity of the ESCoT based on traditional social cognition measures. The ESCoT was administered alongside Reading the Mind in Films (RMF), Reading the Mind in Eyes (RME), Judgement of Preference and Social Norm Questionnaire to 91 participants (30 aged 18-35 years, 30 aged 45-60 years and 31 aged 65-85 years). Poorer performance on the cognitive and affective ToM ESCoT subtests were predicted by increasing age. The affective ToM ESCoT subtest and RMF were predicted by gender, where being female predicted better performance. Unlike the ESCoT, better performance on the RMF was predicted by higher verbal comprehension and perceptual reasoning abilities, while better performance on the RME was predicted by higher verbal comprehension scores. Lower scores on inter-and intrapersonal understanding of social norms were both predicted by the presence of more autism-like traits while poorer interpersonal understanding of social norms performance was predicted by increasing age. These findings show that the ESCoT is a useful measure of social cognition and, unlike established tests of social cognition, performance is not predicted by measures of verbal comprehension and perceptual reasoning. This is particularly valuable to obtain an accurate assessment of the influence of age on our social cognitive abilities.

Predicting perturbation patterns from the topology of biological networks.

PubMed

Santolini, Marc; Barabási, Albert-László

2018-06-20

High-throughput technologies, offering an unprecedented wealth of quantitative data underlying the makeup of living systems, are changing biology. Notably, the systematic mapping of the relationships between biochemical entities has fueled the rapid development of network biology, offering a suitable framework to describe disease phenotypes and predict potential drug targets. However, our ability to develop accurate dynamical models remains limited, due in part to the limited knowledge of the kinetic parameters underlying these interactions. Here, we explore the degree to which we can make reasonably accurate predictions in the absence of the kinetic parameters. We find that simple dynamically agnostic models are sufficient to recover the strength and sign of the biochemical perturbation patterns observed in 87 biological models for which the underlying kinetics are known. Surprisingly, a simple distance-based model achieves 65% accuracy. We show that this predictive power is robust to topological and kinetic parameter perturbations, and we identify key network properties that can increase up to 80% the recovery rate of the true perturbation patterns. We validate our approach using experimental data on the chemotactic pathway in bacteria, finding that a network model of perturbation spreading predicts with ∼80% accuracy the directionality of gene expression and phenotype changes in knock-out and overproduction experiments. These findings show that the steady advances in mapping out the topology of biochemical interaction networks opens avenues for accurate perturbation spread modeling, with direct implications for medicine and drug development.

Anaerobic metabolism at thermal extremes: a metabolomic test of the oxygen limitation hypothesis in an aquatic insect.

PubMed

Verberk, W C E P; Sommer, U; Davidson, R L; Viant, M R

2013-10-01

Thermal limits in ectotherms may arise through a mismatch between supply and demand of oxygen. At higher temperatures, the ability of their cardiac and ventilatory activities to supply oxygen becomes insufficient to meet their elevated oxygen demand. Consequently, higher levels of oxygen in the environment are predicted to enhance tolerance of heat, whereas reductions in oxygen are expected to reduce thermal limits. Here, we extend previous research on thermal limits and oxygen limitation in aquatic insect larvae and directly test the hypothesis of increased anaerobic metabolism and lower energy status at thermal extremes. We quantified metabolite profiles in stonefly nymphs under varying temperatures and oxygen levels. Under normoxia, the concept of oxygen limitation applies to the insects studied. Shifts in the metabolome of heat-stressed stonefly nymphs clearly indicate the onset of anaerobic metabolism (e.g., accumulation of lactate, acetate, and alanine), a perturbation of the tricarboxylic acid cycle (e.g., accumulation of succinate and malate), and a decrease in energy status (e.g., ATP), with corresponding decreases in their ability to survive heat stress. These shifts were more pronounced under hypoxic conditions, and negated by hyperoxia, which also improved heat tolerance. Perturbations of metabolic pathways in response to either heat stress or hypoxia were found to be somewhat similar but not identical. Under hypoxia, energy status was greatly compromised at thermal extremes, but energy shortage and anaerobic metabolism could not be conclusively identified as the sole cause underlying thermal limits under hyperoxia. Metabolomics proved useful for suggesting a range of possible mechanisms to explore in future investigations, such as the involvement of leaking membranes or free radicals. In doing so, metabolomics provided a more complete picture of changes in metabolism under hypoxia and heat stress.

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

Salivary mRNA markers having the potential to detect oral squamous cell carcinoma segregated from oral leukoplakia with dysplasia.

PubMed

Michailidou, Evangelia; Tzimagiorgis, Georgios; Chatzopoulou, Fani; Vahtsevanos, Konstantinos; Antoniadis, Konstantinos; Kouidou, Sofia; Markopoulos, Anastasios; Antoniades, Dimitrios

2016-08-01

In the current study the presence of extracellular IL-1B, IL-8, OAZ and SAT mRNAs in the saliva was evaluated as a tool in the early detection of oral squamous cell carcinoma. 34 patients with primary oral squamous cell carcinoma stage T1N0M0/T2N0M0, 20 patients with oral leukoplakia and dysplasia (15 patients with mild dysplasia and 5 with severe dysplasia/in situ carcinoma) and 31 matched healthy-control subjects were included in the study. The presence of IL-1B, IL-8, OAZ and SAT mRNA was evaluated in extracellular RNA isolated from saliva samples using sequence-specific primers and real-time RT-PCR. ROC curve analysis was used to estimate the ability of the biomarkers to detect oral squamous cell carcinoma patients. The data reveal that the combination of these four biomarkers provides a good predictive probability of up to 80% (AUC=0.799, p=0.002) for patients with oral squamous cell carcinoma but not patients suffering from oral leukoplakia with dysplasia. Moreover, the combination of only the two biomarkers (SAT and IL-8) also raises a high predictive ability of 75.5% (AUC=0.755, p=0.007) approximately equal to the four biomarkers suggesting the use of the two biomarkers only in the prediction model for oral squamous cell carcinoma patients limiting the economic and health cost in half. SAT and IL-8 mRNAs are present in the saliva in high quality and quantity, with a good discriminatory ability for oral squamous cell carcinoma patients only but not for patients with oral leukoplakia and dysplasia an oral potentially malignant disorder. Copyright © 2016. Published by Elsevier Ltd.

Longitudinal changes in young children’s 0–100 to 0–1000 number-line error signatures

PubMed Central

Reeve, Robert A.; Paul, Jacob M.; Butterworth, Brian

2015-01-01

We use a latent difference score (LDS) model to examine changes in young children’s number-line (NL) error signatures (errors marking numbers on a NL) over 18 months. A LDS model (1) overcomes some of the inference limitations of analytic models used in previous research, and in particular (2) provides a more reliable test of hypotheses about the meaning and significance of changes in NL error signatures over time and task. The NL error signatures of 217 6-year-olds’ (on test occasion one) were assessed three times over 18 months, along with their math ability on two occasions. On the first occasion (T1) children completed a 0–100 NL task; on the second (T2) a 0–100 NL and a 0–1000 NL task; on the third (T3) occasion a 0–1000 NL task. On the third and fourth occasions (T3 and T4), children completed mental calculation tasks. Although NL error signatures changed over time, these were predictable from other NL task error signatures, and predicted calculation accuracy at T3, as well as changes in calculation between T3 and T4. Multiple indirect effects (change parameters) showed that associations between initial NL error signatures (0–100 NL) and later mental calculation ability were mediated by error signatures on the 0–1000 NL task. The pattern of findings from the LDS model highlight the value of identifying direct and indirect effects in characterizing changing relationships in cognitive representations over task and time. Substantively, they support the claim that children’s NL error signatures generalize over task and time and thus can be used to predict math ability. PMID:26029152

Single-leg lateral, horizontal, and vertical jump assessment: reliability, interrelationships, and ability to predict sprint and change-of-direction performance.

PubMed

Meylan, Cesar; McMaster, Travis; Cronin, John; Mohammad, Nur Ikhwan; Rogers, Cailyn; Deklerk, Melissa

2009-07-01

The purposes of this study were to determine the reliability of unilateral vertical, horizontal, and lateral countermovement jump assessments, the interrelationship between these tests, and their usefulness as predictors of sprint (10 m) and change-of-direction (COD) performance for 80 men and women physical education students. Jump performance was assessed on a contact mat and sprint, and COD performances were assessed using timing lights. With regard to the reliability statistics, the largest coefficient of variation (CV) was observed for the vertical jump (CV = 6.7-7.2%) of both genders, whereas the sprint and COD assessments had smallest variability (CV = 0.8 to 2.8%). All intraclass correlation coefficients (ICC) were greater than 0.85, except for the men's COD assessment with the alternate leg. The shared variance between the single-leg vertical, horizontal, and lateral jumps for men and women was less than 50%, indicating that the jumps are relatively independent of one another and represent different leg strength/power qualities. The ability of the jumps to predict sprint and COD performance was limited (R2 < 43%). It would seem that the ability to change direction with 1 leg is relatively independent of a COD with the other leg, especially in the women (R < 30%) of this study. However, if 1 jump assessment were selected to predict sprint and COD performance in a test battery, the single-leg horizontal countermovement jump would seem the logical choice, given the results of this study. Many of the findings in this study have interesting diagnostic and training implications for the strength and conditioning coach.

Spatial and Visual Reasoning: Do These Abilities Improve in First-Year Veterinary Medical Students Exposed to an Integrated Curriculum?

PubMed

Gutierrez, J Claudio; Chigerwe, Munashe; Ilkiw, Jan E; Youngblood, Patricia; Holladay, Steven D; Srivastava, Sakti

Spatial visualization ability refers to the human cognitive ability to form, retrieve, and manipulate mental models of spatial nature. Visual reasoning ability has been linked to spatial ability. There is currently limited information about how entry-level spatial and visual reasoning abilities may predict veterinary anatomy performance or may be enhanced with progression through the veterinary anatomy content in an integrated curriculum. The present study made use of two tests that measure spatial ability and one test that measures visual reasoning ability in veterinary students: Guay's Visualization of Views Test, adapted version (GVVT), the Mental Rotations Test (MRT), and Raven's Advanced Progressive Matrices Test, short form (RavenT). The tests were given to the entering class of veterinary students during their orientation week and at week 32 in the veterinary medical curriculum. Mean score on the MRT significantly increased from 15.2 to 20.1, and on the RavenT significantly increased from 7.5 to 8.8. When females only were evaluated, results were similar to the total class outcome; however, all three tests showed significant increases in mean scores. A positive correlation between the pre- and post-test scores was found for all three tests. The present results should be considered preliminary at best for associating anatomic learning in an integrated curriculum with spatial and visual reasoning abilities. Other components of the curriculum, for instance histology or physiology, could also influence the improved spatial visualization and visual reasoning test scores at week 32.

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.

Horizontal cosmic ray muon radiography for imaging nuclear threats

NASA Astrophysics Data System (ADS)

Morris, Christopher L.; Bacon, Jeffrey; Borozdin, Konstantin; Fabritius, Joseph; Miyadera, Haruo; Perry, John; Sugita, Tsukasa

2014-07-01

Muon tomography is a technique that uses information contained in the Coulomb scattering of cosmic ray muons to generate three dimension images of volumes between tracking detectors. Advantages of this technique are the muons ability to penetrate significant overburden and the absence of any additional dose beyond the natural cosmic ray flux. Disadvantages include the long exposure times and limited resolution because of the low flux. Here we compare the times needed to image objects using both vertically and horizontally mounted tracking detectors and we develop a predictive model for other geometries.

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

Wosnik, Martin; Bachant, Pete; Neary, Vincent Sinclair

CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements inmore » a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.« less

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

Public understanding of chemistry research in print news

NASA Astrophysics Data System (ADS)

Hands, Michael D., Jr.

Despite numerous calls for improving scientific literacy, many American adults show a lack of understanding of experiments, scientific study, and scientific inquiry. News media is one important avenue for science learning, but previous research investigating health and/or environmental science news has shown that it is inconsistent in the presentation of scientific research limitations, potentially impacting reader understanding. In the first phase of this dissertation, seventeen news articles reporting on a single chemistry research article, along with associated press releases and research articles, were analyzed using move analysis to determine the structure of each type of text. It was found that the overall structure of each text genre was similar, with the main difference being that research articles start by presenting background information, while the others lead with highlighting overall research outcomes. Analysis of the steps revealed that, as seen for health and environmental science news articles, descriptions of the study limitations and methods were generally omitted in the news articles. Using these findings, a pilot study was conducted where study limitations were added to a chemistry research news article and the effect of its presence on staff members employed at a large Midwestern university (n=12) and science faculty employed at the same institution (n=6) was explored. Interviews with the participants revealed that including limitations enhanced readers' ability to identify conclusions and evaluate claims, but decreased their trust in the information. In the final part of this study, the trends seen in the previous phase were explored to determine their generalizability. Members of the public (n=232) and science faculty (n=191) read a randomly assigned news article either presenting or omitting the study limitations and research methods. Participants reading articles presenting limitations were able to evaluate the reasonableness of claims based on the article better than those who read the article omitting limitations when accounting for their views on the tentativeness of science (ToS). Presenting limitations was important in identifying unreasonable claims for both public and science faculty, while ToS views predicted ability to identify reasonable claims for the public. Including limitations also decreased readers' trust in the conclusions of the research. However, it did not impact their ability to determine the conclusions of the research and including methods did not have any effect on the measured outcomes.

Predicting rheological behavior and baking quality of wheat flour using a GlutoPeak test.

PubMed

Rakita, Slađana; Dokić, Ljubica; Dapčević Hadnađev, Tamara; Hadnađev, Miroslav; Torbica, Aleksandra

2018-06-01

The purpose of this research was to gain an insight into the ability of the GlutoPeak instrument to predict flour functionality for bread making, as well as to determine which of the GlutoPeak parameters show the best potential in predicting dough rheological behavior and baking performance. Obtained results showed that GlutoPeak parameters correlated better with the indices of extensional rheological tests which consider constant dough hydration than with those which were performed at constant dough consistency. The GlutoPeak test showed that it is suitable for discriminating wheat varieties of good quality from those of poor quality, while the most discriminating index was maximum torque (MT). Moreover, MT value of 50 BU and aggregation energy value of 1,300 GPU were set as limits of wheat flour quality. The backward stepwise regression analysis revealed that a high-level prediction of indices which are highly affected by protein content (gluten content, flour water absorption, and dough tenacity) was achieved by using the GlutoPeak indices. Concerning bread quality, a moderate prediction of specific loaf volume and an intense level prediction of breadcrumb textural properties were accomplished by using the GlutoPeak parameters. The presented results indicated that the application of this quick test in wheat transformation chain for the assessment of baking quality would be useful. Baking test is considered as the most reliable method for assessing wheat-baking quality. However, baking test requires trained stuff, time, and large sample amount. These disadvantages have led to a growing demand to develop new rapid tests which would enable prediction of baked product quality with a limited flour size. Therefore, we tested the possibility of using a GlutoPeak tester to predict loaf volume and breadcrumb textural properties. Discrimination of wheat varieties according to quality with a restricted flour amount was also examined. Furthermore, we proposed the limit values of GlutoPeak parameters which would be highly beneficial for millers and bakers when determine suitability of flour for end-use. © 2017 Wiley Periodicals, Inc.

Predictive power of the DASA-IV: Variations in rating method and timescales.

PubMed

Nqwaku, Mphindisi; Draycott, Simon; Aldridge-Waddon, Luke; Bush, Emma-Louise; Tsirimokou, Alexandra; Jones, Dominic; Puzzo, Ignazio

2018-05-10

This project evaluated the predictive validity of the Dynamic Appraisal of Situational Aggression - Inpatient Version (DASA-IV) in a high-secure psychiatric hospital in the UK over 24 hours and over a single nursing shift. DASA-IV scores from three sequential nursing shifts over a 24-hour period were compared with the mean (average of three scores across the 24-hour period) and peak (highest of the three scores across the 24-hour period) scores across these shifts. In addition, scores from a single nursing shift were used to predict aggressive incidents over each of the following three shifts. The DASA-IV was completed by nursing staff during handover meetings, rating 43 male psychiatric inpatients over a period of 6 months. Data were compared to incident reports recorded over the same period. Receiver operating characteristic (ROC) curves and generalized estimating equations assessed the predictive ability of various DASA-IV scores over 24-hour and single-shift timescales. Scores from the DASA-IV based on a single shift had moderate predictive ability for aggressive incidents occurring the next calendar day, whereas scores based on all three shifts had excellent predictive ability. DASA-IV scores from a single shift showed moderate predictive ability for each of the following three shifts. The DASA-IV has excellent predictive ability for aggressive incidents within a secure setting when data are summarized over a 24-hour period, as opposed to when a single rating is taken. In addition, it has moderate value for predicting incidents over even shorter timescales. © 2018 Australian College of Mental Health Nurses Inc.

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.

The relationship between walking, manual dexterity, cognition and activity/participation in persons with multiple sclerosis.

PubMed

Kierkegaard, Marie; Einarsson, Ulrika; Gottberg, Kristina; von Koch, Lena; Holmqvist, Lotta Widén

2012-05-01

Multiple sclerosis has a vast impact on health, but the relationship between walking, manual dexterity, cognition and activity/participation is unclear. The specific aims were to explore the discriminative ability of measures of walking, manual dexterity and cognition, and to identify cut-off values in these measures, for prediction of independence in personal and instrumental activities of daily living (ADL) and activity/participation in social and lifestyle activities. Data from 164 persons with multiple sclerosis were collected during home visits with the following measures: the 2 × 5 m walk test, the Nine-hole Peg Test, the Symbol Digit Modalities Test, the Katz Personal and Instrumental ADL Indexes, and the Frenchay Activities Index (measuring frequency in social and lifestyle activities). The 2 × 5 m walk test and the Nine-hole Peg Test had high and better discriminative and predictive ability than the Symbol Digit Modalities Test. Cut-off values were identified. The accuracy of predictions was increased above all by combining the 2 × 5 m walk test and the Nine-hole Peg Test. The proposed cut-off values in the 2 × 5 m walk test and the Nine-hole Peg Test may be used as indicators of functioning and to identify persons risking activity limitations and participation restrictions. However, further studies are needed to confirm the usefulness in clinical practice.

A model for estimating passive integrated transponder (PIT) tag antenna efficiencies for interval-specific emigration rates

USGS Publications Warehouse

Horton, G.E.; Dubreuil, T.L.; Letcher, B.H.

2007-01-01

Our goal was to understand movement and its interaction with survival for populations of stream salmonids at long-term study sites in the northeastern United States by employing passive integrated transponder (PIT) tags and associated technology. Although our PIT tag antenna arrays spanned the stream channel (at most flows) and were continuously operated, we are aware that aspects of fish behavior, environmental characteristics, and electronic limitations influenced our ability to detect 100% of the emigration from our stream site. Therefore, we required antenna efficiency estimates to adjust observed emigration rates. We obtained such estimates by testing a full-scale physical model of our PIT tag antenna array in a laboratory setting. From the physical model, we developed a statistical model that we used to predict efficiency in the field. The factors most important for predicting efficiency were external radio frequency signal and tag type. For most sampling intervals, there was concordance between the predicted and observed efficiencies, which allowed us to estimate the true emigration rate for our field populations of tagged salmonids. One caveat is that the model's utility may depend on its ability to characterize external radio frequency signals accurately. Another important consideration is the trade-off between the volume of data necessary to model efficiency accurately and the difficulty of storing and manipulating large amounts of data.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Driving improvements in emerging disease surveillance through locally relevant capacity strengthening.

PubMed

Halliday, Jo E B; Hampson, Katie; Hanley, Nick; Lembo, Tiziana; Sharp, Joanne P; Haydon, Daniel T; Cleaveland, Sarah

2017-07-14

Emerging infectious diseases (EIDs) threaten the health of people, animals, and crops globally, but our ability to predict their occurrence is limited. Current public health capacity and ability to detect and respond to EIDs is typically weakest in low- and middle-income countries (LMICs). Many known drivers of EID emergence also converge in LMICs. Strengthening capacity for surveillance of diseases of relevance to local populations can provide a mechanism for building the cross-cutting and flexible capacities needed to tackle both the burden of existing diseases and EID threats. A focus on locally relevant diseases in LMICs and the economic, social, and cultural contexts of surveillance can help address existing inequalities in health systems, improve the capacity to detect and contain EIDs, and contribute to broader global goals for development. Copyright © 2017, American Association for the Advancement of Science.

Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways.

PubMed

Libis, Vincent; Delépine, Baudoin; Faulon, Jean-Loup

2016-10-21

Detection of chemical signals is critical for cells in nature as well as in synthetic biology, where they serve as inputs for designer circuits. Important progress has been made in the design of signal processing circuits triggering complex biological behaviors, but the range of small molecules recognized by sensors as inputs is limited. The ability to detect new molecules will increase the number of synthetic biology applications, but direct engineering of tailor-made sensors takes time. Here we describe a way to immediately expand the range of biologically detectable molecules by systematically designing metabolic pathways that transform nondetectable molecules into molecules for which sensors already exist. We leveraged computer-aided design to predict such sensing-enabling metabolic pathways, and we built several new whole-cell biosensors for molecules such as cocaine, parathion, hippuric acid, and nitroglycerin.

Bioprinting towards Physiologically Relevant Tissue Models for Pharmaceutics.

PubMed

Peng, Weijie; Unutmaz, Derya; Ozbolat, Ibrahim T

2016-09-01

Improving the ability to predict the efficacy and toxicity of drug candidates earlier in the drug discovery process will speed up the introduction of new drugs into clinics. 3D in vitro systems have significantly advanced the drug screening process as 3D tissue models can closely mimic native tissues and, in some cases, the physiological response to drugs. Among various in vitro systems, bioprinting is a highly promising technology possessing several advantages such as tailored microarchitecture, high-throughput capability, coculture ability, and low risk of cross-contamination. In this opinion article, we discuss the currently available tissue models in pharmaceutics along with their limitations and highlight the possibilities of bioprinting physiologically relevant tissue models, which hold great potential in drug testing, high-throughput screening, and disease modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Predictability of Road Traffic and Congestion in Urban Areas

PubMed Central

Wang, Jingyuan; Mao, Yu; Li, Jing; Xiong, Zhang; Wang, Wen-Xu

2015-01-01

Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion. PMID:25849534

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

PubMed

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

2016-10-05

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

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…

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…

Transient finite element analysis of electric double layer using Nernst-Planck-Poisson equations with a modified Stern layer.

PubMed

Lim, Jongil; Whitcomb, John; Boyd, James; Varghese, Julian

2007-01-01

A finite element implementation of the transient nonlinear Nernst-Planck-Poisson (NPP) and Nernst-Planck-Poisson-modified Stern (NPPMS) models is presented. The NPPMS model uses multipoint constraints to account for finite ion size, resulting in realistic ion concentrations even at high surface potential. The Poisson-Boltzmann equation is used to provide a limited check of the transient models for low surface potential and dilute bulk solutions. The effects of the surface potential and bulk molarity on the electric potential and ion concentrations as functions of space and time are studied. The ability of the models to predict realistic energy storage capacity is investigated. The predicted energy is much more sensitive to surface potential than to bulk solution molarity.

The interactional significance of formulas in autistic language.

PubMed

Dobbinson, Sushie; Perkins, Mick; Boucher, Jill

2003-01-01

The phenomenon of echolalia in autistic language is well documented. Whilst much early research dismissed echolalia as merely an indicator of cognitive limitation, later work identified particular discourse functions of echolalic utterances. The work reported here extends the study of the interactional significance of echolalia to formulaic utterances. Audio and video recordings of conversations between the first author and two research participants were transcribed and analysed according to a Conversation Analysis framework and a multi-layered linguistic framework. Formulaic language was found to have predictable interactional significance within the language of an individual with autism, and the generic phenomenon of formulaicity in company with predictable discourse function was seen to hold across the research participants, regardless of cognitive ability. The implications of formulaicity in autistic language for acquisition and processing mechanisms are discussed.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, J.; Busalacchi, A.; Murtugudde, R.

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, Joaquim; Busalacchi, Antonio J.; Murtugudde, Ragu

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

PubMed

Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

2015-07-05

Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

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.

Organic Ion Transporters and Statin Drug Interactions.

PubMed

Kellick, Kenneth

2017-11-25

Statin drug-drug interactions (DDIs) are both troublesome to patients as well as costly to medical resources. The ability to predict and avoid these events could lead to improved outcomes as well as patient satisfaction. This review will explore efforts to better understand and predict these interactions specifically related to one drug transport system, the organic anion-transporting polypeptides (OATPs) specifically OATP1B1 and OATP1B3. Since the publication of the discovery of OATPs, there have been various pharmacokinetic models that have been proposed to explain the variation in pharmacokinetic and clinical effects related to the OATPs. The effects in transport activity appear to be partially related to the individual polymorphisms studied. Drug-drug interactions can occur when other drugs compete for the metabolic site on the OATPs. Various medications are identified as substrates and/or inhibitors of the OATPs, thereby complicating the ability to fully predict the impact on levels and effects. All of the models reviewed claim successes but show limited clinical utility. There are specific populations that have been identified, predominately various Asian descendants that require lower doses of statins to avoid adverse events. The concept of attributing these actions to the OATPs has been explored, but current models cannot accurately predict statin blood levels or elimination constants. The current research only points to the differences in the human genome and the single-nucleotide polymorphisms that exist between us. Based upon the currently available studies, there is beginning to be a glimmer in the understanding how different populations respond to statin transport and elimination. Additionally and unfortunately, there are other enzymes to be studied to better predict patient differences. Clearly, there has been much work completed, yet many more questions require answering to better understand these transport proteins.

Evaluation of the Ability of S2S and NMME Models to Predict Heat Waves Following Drought Events in the United States

NASA Astrophysics Data System (ADS)

Ford, T.; Dirmeyer, P.

2016-12-01

The influence of antecedent drought conditions on the onset of heat waves in North America is important as the establishment of past heat wave events has been connected to both advection of warm, dry air and limitation of local moisture recycling due to dry soils. The strong connection between the land surface and subsequent extreme heat offers promise that realistic soil moisture initialization could improve model forecast skill. However, there is still a lack of consensus about the (1) the role of antecedent drought conditions in forcing heat waves over North America and (2) the ability of numerical forecast models to predict extreme heat events at sub-seasonal to seasonal time scales. For this project, we use atmospheric reanalysis datasets to establish the connection between drought and subsequent extreme heat events. The Standardized Precipitation Index (SPI), computed over 30-, 60-, and 90-day intervals, is used to identify drought events, while the excess heat factor defines subsequent heat wave events. We focus on heat waves immediately following drought periods, including events coinciding with but not beginning prior to the start of drought, as well as heat wave events beginning no more than 3 days after the demise of a drought event. Hindcasts from individual model ensemble members of the Sub-seasonal to Seasonal Prediction (S2S) Project and the Phase II of the North American Multi-Model Ensemble (NMME) are assessed with regard to heat wave prediction. Each individual S2S and NMME ensemble member is evaluated to determine if their respective hindcasts are able to capture/predict heat wave events identified in the reanalysis products.

A predictive model of inflammatory markers and patient-reported symptoms for cachexia in newly diagnosed pancreatic cancer patients.

PubMed

Fogelman, David R; Morris, J; Xiao, L; Hassan, M; Vadhan, S; Overman, M; Javle, S; Shroff, R; Varadhachary, G; Wolff, R; Vence, L; Maitra, A; Cleeland, C; Wang, X S

2017-06-01

Cachexia is a frequent manifestation of pancreatic cancer, can limit a patient's ability to take chemotherapy, and is associated with shortened survival. We developed a model to predict the early onset of cachexia in advanced pancreatic cancer patients. Patients with newly diagnosed, untreated metastatic or locally advanced pancreatic cancer were included. Serum cytokines were drawn prior to therapy. Patient symptoms were recorded using the M.D. Anderson Symptom Inventory (MDASI). Our primary endpoint was either 10% weight loss or death within 60 days of the start of therapy. Twenty-seven of 89 patients met the primary endpoint (either having lost 10% of body weight or having died within 60 days of the start of treatment). In a univariate analysis, smoking, history symptoms of pain and difficulty swallowing, high levels of MK, CXCL-16, IL-6, TNF-a, and low IL-1b all correlated with this endpoint. We used recursive partition to fit a regression tree model, selecting four of 26 variables (CXCL-16, IL-1b, pain, swallowing difficulty) as important in predicting cachexia. From these, a model of two cytokines (CXCL-16 > 5.135 ng/ml and IL-1b < 0.08 ng/ml) demonstrated a better sensitivity and specificity for this outcome (0.70 and 0.86, respectively) than any individual cytokine or tumor marker. Cachexia is frequent in pancreatic cancer; one in three patients met our endpoint of 10% weight loss or death within 60 days. Inflammatory cytokines are better than conventional tumor markers at predicting this outcome. Recursive partitioning analysis suggests that a model of CXCL-16 and IL-1B may offer a better ability than individual cytokines to predict this outcome.

What Analytic Method Should Clinicians Use to Derive Spine T-scores and Predict Incident Fractures in Men? Results from the MrOS study

PubMed Central

Hansen, Karen E; Blank, Robert D; Palermo, Lisa; Fink, Howard A; Orwoll, Eric S

2014-01-01

Summary In this study, the area under the curve was highest when using the lowest vertebral body T-score to diagnose osteoporosis. In men for whom hip imaging is not possible, the lowest vertebral body T-score improves ability to diagnose osteoporosis in men who are likely to have an incident fragility fracture. Purpose Spine T-scores have limited ability to predict fragility fracture. We hypothesized that using lowest vertebral body T-score to diagnose osteoporosis would better predict fracture. Methods Among men enrolled in the Osteoporotic Fractures in Men Study, we identified cases with incident clinical fracture (n=484) and controls without fracture (n=1,516). We analyzed the lumbar spine BMD in cases and controls (n=2,000) to record the L1-L4 (referent), the lowest vertebral body and ISCD-determined T-scores using a male normative database, and the L1-L4 T-score using a female normative database. We compared the ability of method to diagnose osteoporosis and therefore predict incident clinical fragility fracture, using area under the receiver operator curves (AUC) and the net reclassification index (NCI) as measures of diagnostic accuracy. ISCD-determined T-scores were determined in only 60% of participants (n=1205). Results Among 1,205 men, the AUC to predict incident clinical fracture was 0.546 for L1-L4 male, 0.542 for the L1-L4 female, 0.585 for lowest vertebral body and 0.559 for ISCD-determined T-score. The lowest vertebral body AUC was the only method significantly different from the referent method (p=0.002). Likewise, a diagnosis of osteoporosis based on the lowest vertebral body T-score demonstrated a significantly better NRI than the referent method (net NRI +0.077, p=0.005). By contrast, the net NRI for other methods of analysis did not differ from the referent method. Conclusion Our study suggests that in men, the lowest vertebral body T-score is an acceptable method by which to estimate fracture risk. PMID:24850381

Musculoskeletal pain and limitations in work ability in Swedish marines: a cross-sectional survey of prevalence and associated factors

PubMed Central

Monnier, Andreas; Larsson, Helena; Djupsjöbacka, Mats; Brodin, Lars-Åke; Äng, Björn O

2015-01-01

Objectives To estimate the prevalence of self-rated musculoskeletal pain and pain limiting work ability in Swedish Armed Forces (SAF) marines, and to study factors potentially associated with pain limiting work ability for the most prevalent pain regions reported. Design Population-based, cross-sectional survey. Participants There were 272 SAF marines from the main marine battalion in Sweden included in the study. Outcomes Self-assessed musculoskeletal pain and pain limiting the marines' work ability within a 6-month period, as obtained from structured questionnaires. The association of individual, health and work-related factors with musculoskeletal pain limiting work ability was systematically regressed with multiple logistic models, estimating OR and 95% CI. Results Musculoskeletal pain and pain limiting work ability were most common in the back, at 46% and 20%, and lower extremities at 51% and 29%, respectively. Physical training ≤1 day/week (OR 5.3, 95% CI 1.7 to 16.8); body height ≤1.80 m (OR 5.0, 95% CI 1.6 to 15.1) and ≥1.86 m (OR 4.4, 95% CI 1.4 to 14.1); computer work 1/4 of the working day (OR 3.2, 95% CI 1.0 to 10.0) and ≥1/2 (OR 3.3, 95% CI 1.1 to 10.1) of the working day were independently associated with back pain limiting work ability. None of the studied variables emerged significantly associated with such pain for the lower extremities. Conclusions Our findings show that musculoskeletal pain and resultant limitations in work ability are common in SAF marines. Low frequency of physical training emerged independently associated with back pain limiting work ability. This suggests that marines performing physical training 1 day per week or less are suitable candidates for further medical evaluation and secondary preventive actions. While also associated, body height and computer work need further exploration as underlying mechanisms for back pain limiting work ability. Further prospective studies are necessary to clarify the direction of causality. PMID:26443649

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.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems.

PubMed

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-28

We report a new limitation on the ability of physical systems to perform computation-one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system-such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Maintenance of Ecosystem Nitrogen Limitation by Ephemeral Forest Disturbance: An Assessment using MODIS, Hyperion, and Landsat ETM+

NASA Technical Reports Server (NTRS)

McNeil, Brenden E.; deBeurs, Kirsten M.; Eshleman, Keith N.; Foster, Jane R.; Townsend, Philip A.

2007-01-01

Ephemeral disturbances, such as non-lethal insect defoliations and crown damage from meteorological events, can significantly affect the delivery of ecosystem services by helping maintain nitrogen (N) limitation in temperate forest ecosystems. However, the impacts of these disturbances are difficult to observe across the broad-scales at which they affect ecosystem function. Using remotely sensed measures and field data, we find support for the hypothesis that ephemeral disturbances help maintain landscape-wide ecosystem N limitation. Specifically, a phenology-based defoliation index derived from daily MODIS satellite imagery predicts three ecosystem responses from oak-dominated forested watersheds: elevated stream water N export (R(exp 2) = 0.48), decreased foliar N (R(exp 2) = 0.69, assessed with Hyperion imagery), and reduced vegetation growth vigor (R(exp 2) = 0.49, assessed with Landsat ETM+ imagery). The results indicate that ephemeral disturbances and other forest stressors may sustain N limitation by reducing the ability of trees to compete for--and retain--soil available N.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems

NASA Astrophysics Data System (ADS)

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-01

We report a new limitation on the ability of physical systems to perform computation—one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system—such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Influential Cognitive Processes on Framing Biases in Aging

PubMed Central

Perez, Alison M.; Spence, Jeffrey Scott; Kiel, L. D.; Venza, Erin E.; Chapman, Sandra B.

2018-01-01

Factors that contribute to overcoming decision-making biases in later life pose an important investigational question given the increasing older adult population. Limited empirical evidence exists and the literature remains equivocal of whether increasing age is associated with elevated susceptibility to decision-making biases such as framing effects. Research into the individual differences contributing to decision-making ability may offer better understanding of the influence of age in decision-making ability. Changes in cognition underlying decision-making have been shown with increased age and may contribute to individual variability in decision-making abilities. This study had three aims; (1) to understand the influence of age on susceptibility to decision-making biases as measured by framing effects across a large, continuous age range; (2) to examine influence of cognitive abilities that change with age; and (3) to understand the influence of individual factors such as gender and education on susceptibility to framing effects. 200 individuals (28–79 years of age) were tested on a large battery of cognitive measures in the domains of executive function, memory and complex attention. Findings from this study demonstrated that cognitive abilities such as strategic control and delayed memory better predicted susceptibility to framing biases than age. The current findings demonstrate that age may not be as influential a factor in decision-making as cognitive ability and cognitive reserve. These findings motivate future studies to better characterize cognitive ability to determine decision-making susceptibilities in aging populations. PMID:29867641

Influential Cognitive Processes on Framing Biases in Aging.

PubMed

Perez, Alison M; Spence, Jeffrey Scott; Kiel, L D; Venza, Erin E; Chapman, Sandra B

2018-01-01

Factors that contribute to overcoming decision-making biases in later life pose an important investigational question given the increasing older adult population. Limited empirical evidence exists and the literature remains equivocal of whether increasing age is associated with elevated susceptibility to decision-making biases such as framing effects. Research into the individual differences contributing to decision-making ability may offer better understanding of the influence of age in decision-making ability. Changes in cognition underlying decision-making have been shown with increased age and may contribute to individual variability in decision-making abilities. This study had three aims; (1) to understand the influence of age on susceptibility to decision-making biases as measured by framing effects across a large, continuous age range; (2) to examine influence of cognitive abilities that change with age; and (3) to understand the influence of individual factors such as gender and education on susceptibility to framing effects. 200 individuals (28-79 years of age) were tested on a large battery of cognitive measures in the domains of executive function, memory and complex attention. Findings from this study demonstrated that cognitive abilities such as strategic control and delayed memory better predicted susceptibility to framing biases than age. The current findings demonstrate that age may not be as influential a factor in decision-making as cognitive ability and cognitive reserve. These findings motivate future studies to better characterize cognitive ability to determine decision-making susceptibilities in aging populations.

Effect of Tutorial Giving on The Topic of Special Theory of Relativity in Modern Physics Course Towards Students’ Problem-Solving Ability

NASA Astrophysics Data System (ADS)

Hartatiek; Yudyanto; Haryoto, Dwi

2017-05-01

A Special Theory of Relativity handbook has been successfully arranged to guide students tutorial activity in the Modern Physics course. The low of students’ problem-solving ability was overcome by giving the tutorial in addition to the lecture class. It was done due to the limited time in the class during the course to have students do some exercises for their problem-solving ability. The explicit problem-solving based tutorial handbook was written by emphasizing to this 5 problem-solving strategies: (1) focus on the problem, (2) picture the physical facts, (3) plan the solution, (4) solve the problem, and (5) check the result. This research and development (R&D) consisted of 3 main steps: (1) preliminary study, (2) draft I. product development, and (3) product validation. The developed draft product was validated by experts to measure the feasibility of the material and predict the effect of the tutorial giving by means of questionnaires with scale 1 to 4. The students problem-solving ability in Special Theory of Relativity showed very good qualification. It implied that the tutorial giving with the help of tutorial handbook increased students problem-solving ability. The empirical test revealed that the developed handbook was significantly affected in improving students’ mastery concept and problem-solving ability. Both students’ mastery concept and problem-solving ability were in middle category with gain of 0.31 and 0.41, respectively.

Emotional intelligence and depressive symptoms in Spanish institutionalized elders: does emotional self-efficacy act as a mediator?

PubMed Central

2016-01-01

Background. This work examines the relationship between emotional intelligence (EI) and depressive symptomatology in institutionalized older adults, delving into the mechanisms underlying this relationship. Considering that previous evidence of the variation of the EI-depression relationship depending on whether the emotional ability or the perception of that ability is evaluated, a model of multiple mediation was tested in which the dimensions of emotional self-efficacy (ESE) act as mediators in the relationship between ability EI and depressive symptomatology. Methods. The sample consisted of 115 institutionalized older adults (47.82% women; 80.3 ± 7.9 years of age) from the province of Jaén (Spain) who completed a test of ESE, a measure of ability EI, and a self-administered questionnaire of depressive symptoms. Results. The results showed a positive association between older adults’ emotional performance and depressive symptomatology, finding stronger associations with ESE than with EI abilities. In addition, multiple mediation analyses showed that two of the four dimensions of ESE fully mediated the relationship between ability EI and depressive symptoms. Discussion. These findings suggest that older adults’ high levels of emotional competence generate a feeling of ESE which can protect them against depressive symptoms. This work supports the predictive validity of emotional abilities and ESE for the mental health of a group that is particularly vulnerable to depression, institutionalized older adults. The limitations of the work are discussed, and future lines of research were considered. PMID:27547553

Goal neglect, fluid intelligence and processing speed: Manipulating instruction load and inter-stimulus interval.

PubMed

Iveson, Matthew H; Della Sala, Sergio; Anderson, Mike; MacPherson, Sarah E

2017-05-01

Goal maintenance is the process where task rules and instructions are kept active to exert their control on behavior. When this process fails, an individual may ignore a rule while performing the task, despite being able to describe it after task completion. Previous research has suggested that the goal maintenance system is limited by the number of concurrent rules which can be maintained during a task, and that this limit is dependent on an individual's level of fluid intelligence. However, the speed at which an individual can process information may also limit their ability to use task rules when the task demands them. In the present study, four experiments manipulated the number of instructions to be maintained by younger and older adults and examined whether performance on a rapid letter-monitoring task was predicted by individual differences in fluid intelligence or processing speed. Fluid intelligence played little role in determining how frequently rules were ignored during the task, regardless of the number of rules to be maintained. In contrast, processing speed predicted the rate of goal neglect in older adults, where increasing the presentation rate of the letter-monitoring task increased goal neglect. These findings suggest that goal maintenance may be limited by the speed at which it can operate. Copyright © 2017. Published by Elsevier B.V.

Longitudinal change in the BODE index predicts mortality in severe emphysema.

PubMed

Martinez, Fernando J; Han, Meilan K; Andrei, Adin-Cristian; Wise, Robert; Murray, Susan; Curtis, Jeffrey L; Sternberg, Alice; Criner, Gerard; Gay, Steven E; Reilly, John; Make, Barry; Ries, Andrew L; Sciurba, Frank; Weinmann, Gail; Mosenifar, Zab; DeCamp, Malcolm; Fishman, Alfred P; Celli, Bartolome R

2008-09-01

The predictive value of longitudinal change in BODE (Body mass index, airflow Obstruction, Dyspnea, and Exercise capacity) index has received limited attention. We hypothesized that decrease in a modified BODE (mBODE) would predict survival in National Emphysema Treatment Trial (NETT) patients. To determine how the mBODE score changes in patients with lung volume reduction surgery versus medical therapy and correlations with survival. Clinical data were recorded using standardized instruments. The mBODE was calculated and patient-specific mBODE trajectories during 6, 12, and 24 months of follow-up were estimated using separate regressions for each patient. Patients were classified as having decreasing, stable, increasing, or missing mBODE based on their absolute change from baseline. The predictive ability of mBODE change on survival was assessed using multivariate Cox regression models. The index of concordance was used to directly compare the predictive ability of mBODE and its separate components. The entire cohort (610 treated medically and 608 treated surgically) was characterized by severe airflow obstruction, moderate breathlessness, and increased mBODE at baseline. A wide distribution of change in mBODE was seen at follow-up. An increase in mBODE of more than 1 point was associated with increased mortality in surgically and medically treated patients. Surgically treated patients were less likely to experience death or an increase greater than 1 in mBODE. Indices of concordance showed that mBODE change predicted survival better than its separate components. The mBODE demonstrates short- and intermediate-term responsiveness to intervention in severe chronic obstructive pulmonary disease. Increase in mBODE of more than 1 point from baseline to 6, 12, and 24 months of follow-up was predictive of subsequent mortality. Change in mBODE may prove a good surrogate measure of survival in therapeutic trials in severe chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00000606).

Forests and Soil Erosion across Europe

NASA Astrophysics Data System (ADS)

Bathurst, J. C.

2012-04-01

Land use and climate change threaten the ability of Europe's forests to provide a vital service in limiting soil erosion, e.g. from forest fires and landslides. However, our ability to define the threat and to propose mitigation measures suffers from two deficiencies concerning the forest/erosion interface: 1) While there have been a considerable number of field studies of the relationship between forest cover and erosion in different parts of Europe, the data sets are scattered among research groups and a range of literature outlets. There is no comprehensive overview of the forest/erosion interface at the European scale, essential for considering regional variations and investigating the effects of future changes in land use and climate. 2) Compared with forest/water studies, we have a poorer quantitative appreciation of forest/erosion interactions. In the forest/water area it is possible to make quantitative statements such as that a 20% change in forest cover across a river catchment is needed for the effect on annual water yield to be measurable or that a forested catchment in upland UK has an annual water yield around 15% lower than an otherwise comparable grassland catchment. Comparable statements are not yet possible for forest/erosion interactions and there are uncertainties in the mathematical representation of forest/erosion interactions which limit our ability to make predictions, for example of the impact of forest loss in a given area. This presentation therefore considers the next step in improving our predictive capability. It proposes the integration of existing research and data to construct the "big picture" across Europe, i.e. erosion rates and sediment yields associated with forest cover and its loss in a range of erosion regimes (e.g. post-forest fire erosion or post-logging landslides). This would provide a basis for generalizations at the European scale. However, such an overview would not form a predictive capability. Therefore it is also necessary to identify a range of predictive methods, from empirical guidelines to computer models, which can be recommended for applications such as extrapolating from the local to the regional scale and for planning mitigation strategies. Such developments could help improve efficiency in the integrated management of forest, soil and water resources, benefit local engineering projects ranging from hazard mitigation plans to road culvert design, contribute to the implementation of the EU Water Framework Development, form a more objective basis for cost/benefit analysis of proposed management actions and help in putting a value on forest services.

Stability analysis of electrical powered wheelchair-mounted robotic-assisted transfer device.

PubMed

Wang, Hongwu; Tsai, Chung-Ying; Jeannis, Hervens; Chung, Cheng-Shiu; Kelleher, Annmarie; Grindle, Garrett G; Cooper, Rory A

2014-01-01

The ability of people with disabilities to live in their homes and communities with maximal independence often hinges, at least in part, on their ability to transfer or be transferred by an assistant. Because of limited resources and the expense of personal care, robotic transfer assistance devices will likely be in great demand. An easy-to-use system for assisting with transfers, attachable to electrical powered wheelchairs (EPWs) and readily transportable, could have a significant positive effect on the quality of life of people with disabilities. We investigated the stability of our newly developed Strong Arm, which is attached and integrated with an EPW to assist with transfers. The stability of the system was analyzed and verified by experiments applying different loads and using different system configurations. The model predicted the distributions of the system's center of mass very well compared with the experimental results. When real transfers were conducted with 50 and 75 kg loads and an 83.25 kg dummy, the current Strong Arm could transfer all weights safely without tip-over. Our modeling accurately predicts the stability of the system and is suitable for developing better control algorithms to enhance the safety of the device.

Connectotyping: Model Based Fingerprinting of the Functional Connectome

PubMed Central

Miranda-Dominguez, Oscar; Mills, Brian D.; Carpenter, Samuel D.; Grant, Kathleen A.; Kroenke, Christopher D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

A better characterization of how an individual’s brain is functionally organized will likely bring dramatic advances to many fields of study. Here we show a model-based approach toward characterizing resting state functional connectivity MRI (rs-fcMRI) that is capable of identifying a so-called “connectotype”, or functional fingerprint in individual participants. The approach rests on a simple linear model that proposes the activity of a given brain region can be described by the weighted sum of its functional neighboring regions. The resulting coefficients correspond to a personalized model-based connectivity matrix that is capable of predicting the timeseries of each subject. Importantly, the model itself is subject specific and has the ability to predict an individual at a later date using a limited number of non-sequential frames. While we show that there is a significant amount of shared variance between models across subjects, the model’s ability to discriminate an individual is driven by unique connections in higher order control regions in frontal and parietal cortices. Furthermore, we show that the connectotype is present in non-human primates as well, highlighting the translational potential of the approach. PMID:25386919

Family characteristics have limited ability to predict weight status of young children.

PubMed

Gray, Virginia B; Byrd, Sylvia H; Cossman, Jeralynn S; Chromiak, Joseph; Cheek, Wanda K; Jackson, Gary B

2007-07-01

The ability of (a) family characteristics (marital status, income, race, and education), (b) parental control over child's food intake, and (c) parental belief in causes of overweight to predict weight status of children was assessed. Parents/caretakers of elementary school-aged children were surveyed to determine attitudes related to childhood nutrition and overweight. Anthropometric measurements were obtained from children to determine weight status (n=169 matched surveys and measurements). chi(2) tests and nested logistic regression models were used to determine relationships between children's weight status and family characteristics, parental control, and parental belief in the primary cause of overweight. Low household income was an important predictor of overweight; marital status and race added no further explanatory power to the model. Parental control was not a significant predictor of overweight. Parental belief in the primary cause of overweight in children (diet vs physical activity) was significantly related to children's weight; however, it was not significant after controlling for income. Low household income relates strongly to increased childhood weight status; therefore, school and government policies should promote an environment that supports affordable, safe, and feasible opportunities for healthful nutrition and physical activity, particularly for low-income audiences.

Inattentional Blindness and Individual Differences in Cognitive Abilities.

PubMed

Kreitz, Carina; Furley, Philip; Memmert, Daniel; Simons, Daniel J

2015-01-01

People sometimes fail to notice salient unexpected objects when their attention is otherwise occupied, a phenomenon known as inattentional blindness. To explore individual differences in inattentional blindness, we employed both static and dynamic tasks that either presented the unexpected object away from the focus of attention (spatial) or near the focus of attention (central). We hypothesized that noticing in central tasks might be driven by the availability of cognitive resources like working memory, and that noticing in spatial tasks might be driven by the limits on spatial attention like attention breadth. However, none of the cognitive measures predicted noticing in the dynamic central task or in either the static or dynamic spatial task. Only in the central static task did working memory capacity predict noticing, and that relationship was fairly weak. Furthermore, whether or not participants noticed an unexpected object in a static task was only weakly associated with their odds of noticing an unexpected object in a dynamic task. Taken together, our results are largely consistent with the notion that noticing unexpected objects is driven more by stochastic processes common to all people than by stable individual differences in cognitive abilities.

Inattentional Blindness and Individual Differences in Cognitive Abilities

PubMed Central

Kreitz, Carina; Furley, Philip; Memmert, Daniel; Simons, Daniel J.

2015-01-01

People sometimes fail to notice salient unexpected objects when their attention is otherwise occupied, a phenomenon known as inattentional blindness. To explore individual differences in inattentional blindness, we employed both static and dynamic tasks that either presented the unexpected object away from the focus of attention (spatial) or near the focus of attention (central). We hypothesized that noticing in central tasks might be driven by the availability of cognitive resources like working memory, and that noticing in spatial tasks might be driven by the limits on spatial attention like attention breadth. However, none of the cognitive measures predicted noticing in the dynamic central task or in either the static or dynamic spatial task. Only in the central static task did working memory capacity predict noticing, and that relationship was fairly weak. Furthermore, whether or not participants noticed an unexpected object in a static task was only weakly associated with their odds of noticing an unexpected object in a dynamic task. Taken together, our results are largely consistent with the notion that noticing unexpected objects is driven more by stochastic processes common to all people than by stable individual differences in cognitive abilities. PMID:26258545

Choosing to regulate: does choice enhance craving regulation?

PubMed Central

Mobasser, Arian; Zeithamova, Dagmar; Pfeifer, Jennifer H

2018-01-01

Abstract Goal-directed behavior and lifelong well-being often depend on the ability to control appetitive motivations, such as cravings. Cognitive reappraisal is an effective way to modulate emotional states, including cravings, but is often studied under explicit instruction to regulate. Despite the strong prediction from Self-Determination Theory that choice should enhance task engagement and regulation success, little is known empirically about whether and how regulation is different when participants choose (vs are told) to exert control. To investigate how choice affects neural activity and regulation success, participants reappraised their responses to images of personally-craved foods while undergoing functional neuroimaging. Participants were either instructed to view or reappraise (‘no-choice’) or chose freely to view or reappraise (‘yes-choice’). Choice increased activity in the frontoparietal control network. We expected this activity would be associated with increased task engagement, resulting in better regulation success. However, contrary to this prediction, choice slightly reduced regulation success. Follow-up multivariate functional neuroimaging analyses indicated that choice likely disrupted allocation of limited cognitive resources during reappraisal. While unexpected, these results highlight the importance of studying upstream processes such as regulation choice, as they may affect the ability to regulate cravings and other emotional states. PMID:29462475

Short-term predicted extinction of Andean populations of the lizard Stenocercus guentheri (Iguanidae: Tropidurinae).

PubMed

Andrango, María Belén; Sette, Carla; Torres-Carvajal, Omar

2016-12-01

We studied the thermal physiology of the Andean lizard Stenocercus guentheri in order to evaluate the possible effects of global warming on this species. We determined the preferred body temperature (T pref ), critical thermals (CTmin, CTmax), and hours of restriction and activity. T pref was 32.14±1.83°C; CTmin was 8.31°C in adults and 9.14°C in juveniles, whereas CTmax was 43.28°C in adults and 41.68°C in juveniles. To assess extinction risk, we used the model created by Sinervo et al. (2010) and predicted that 16.7% of populations will have a high risk of extinction by 2020, with an increase to 26.7% by 2050. These results suggest that this species, despite being able to maintain its T pref through behavioral thermoregulation and habitat selection, could be physiologically sensitive to climate warming; thus, the potential for local adaptation may be limited under a warmer climate. Further studies focusing on the ability of S. guentheri to evolve higher T pref and thermal tolerances are needed to understand the ability of this species to respond to climate change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Limited evidence of individual differences in holistic processing in different versions of the part-whole paradigm.

PubMed

Sunday, Mackenzie A; Richler, Jennifer J; Gauthier, Isabel

2017-07-01

The part-whole paradigm was one of the first measures of holistic processing and it has been used to address several topics in face recognition, including its development, other-race effects, and more recently, whether holistic processing is correlated with face recognition ability. However the task was not designed to measure individual differences and it has produced measurements with low reliability. We created a new holistic processing test designed to measure individual differences based on the part-whole paradigm, the Vanderbilt Part Whole Test (VPWT). Measurements in the part and whole conditions were reliable, but, surprisingly, there was no evidence for reliable individual differences in the part-whole index (how well a person can take advantage of a face part presented within a whole face context compared to the part presented without a whole face) because part and whole conditions were strongly correlated. The same result was obtained in a version of the original part-whole task that was modified to increase its reliability. Controlling for object recognition ability, we found that variance in the whole condition does not predict any additional variance in face recognition over what is already predicted by performance in the part condition.

Scoring Systems for Estimating the Risk of Anticoagulant-Associated Bleeding.

PubMed

Parks, Anna L; Fang, Margaret C

2017-07-01

Anticoagulant medications are frequently used to prevent and treat thromboembolic disease. However, the benefits of anticoagulants must be balanced with a careful assessment of the risk of bleeding complications that can ensue from their use. Several bleeding risk scores are available, including the Outpatient Bleeding Risk Index, HAS-BLED, ATRIA, and HEMORR 2 HAGES risk assessment tools, and can be used to help estimate patients' risk for bleeding on anticoagulants. These tools vary by their individual risk components and in how they define and weigh clinical factors. However, it is not yet clear how best to integrate bleeding risk tools into clinical practice. Current bleeding risk scores generally have modest predictive ability and limited ability to predict the most devastating complication of anticoagulation, intracranial hemorrhage. In clinical practice, bleeding risk tools should be paired with a formal determination of thrombosis risk, as their results may be most influential for patients at the lower end of thrombosis risk, as well as for highlighting potentially modifiable risk factors for bleeding. Use of bleeding risk scores may assist clinicians and patients in making informed and individualized anticoagulation decisions. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

PLESA: Program for Persons of Limited English-Speaking Ability. Ten Case Studies.

ERIC Educational Resources Information Center

Reynolds, Jack; And Others

These ten case studies of the Program for Persons of Limited English-Speaking Ability (PLESA) report different approaches to providing training and employment assistance to unemployed persons of limited English-speaking ability. (A summary report of forty-seven projects is available separately. See Note.) The first four describe projects conducted…

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.

Pretreatment Acoustic Predictors of Gender, Femininity, and Naturalness Ratings in Individuals With Male-to-Female Gender Identity.

PubMed

Hardy, Teresa L D; Boliek, Carol A; Wells, Kristopher; Dearden, Carol; Zalmanowitz, Connie; Rieger, Jana M

2016-05-01

The purpose of this study was to describe the pretreatment acoustic characteristics of individuals with male-to-female gender identity (IMtFGI) and investigate the ability of the acoustic measures to predict ratings of gender, femininity, and vocal naturalness. This retrospective descriptive study included 2 groups of participants. Speakers were IMtFGI who had not previously received communication feminization treatment (N = 25). Listeners were members of the lay community (N = 30). Acoustic data were retrospectively obtained from pretreatment recordings, and pretreatment recordings also served as stimuli for 3 perceptual rating tasks (completed by listeners). Acoustic data generally were within normal limits for male speakers. All but 2 speakers were perceived to be male, limiting information about the relationship between acoustic measures and gender perception. Fundamental frequency (reading) significantly predicted femininity ratings (p = .000). A total of 3 stepwise regression models indicated that minimum frequency (range task), second vowel formant (sustained vowel), and shimmer percentage (sustained vowel) together significantly predicted naturalness ratings (p = .005, p = .003, and p = .002, respectively). Study aims were achieved with the exception of acoustic predictors of gender perception, which could be described for only 2 speakers. Future research should investigate measures of prosody, voice quality, and other aspects of communication as predictors of gender, femininity, and naturalness.

TRAC-PF1/MOD1 pretest predictions of MIST experiments

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

Boyack, B.E.; Steiner, J.L.; Siebe, D.A.

Los Alamos National Laboratory is a participant in the Integral System Test (IST) program initiated in June 1983 to provide integral system test data on specific issues and phenomena relevant to post small-break loss-of-coolant accidents (SBLOCAs) in Babcock and Wilcox plant designs. The Multi-Loop Integral System Test (MIST) facility is the largest single component in the IST program. During Fiscal Year 1986, Los Alamos performed five MIST pretest analyses. The five experiments were chosen on the basis of their potential either to approach the facility limits or to challenge the predictive capability of the TRAC-PF1/MOD1 code. Three SBLOCA tests weremore » examined which included nominal test conditions, throttled auxiliary feedwater and asymmetric steam-generator cooldown, and reduced high-pressure-injection (HPI) capacity, respectively. Also analyzed were two ''feed-and-bleed'' cooling tests with reduced HPI and delayed HPI initiation. Results of the tests showed that the MIST facility limits would not be approached in the five tests considered. Early comparisons with preliminary test data indicate that the TRAC-PF1/MOD1 code is correctly calculating the dominant phenomena occurring in the MIST facility during the tests. Posttest analyses are planned to provide a quantitative assessment of the code's ability to predict MIST transients.« less

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Seed dispersal and seedling establishment of Sarracenia purpurea (Sarraceniaceae).

PubMed

Ellison, Aaron M; Parker, Jerelyn N

2002-06-01

Plant ecologists continue to grapple with Reid's paradox, the observation that dispersal distances of most herbs and trees are too limited to account for their recolonization of northern latitudes following glacial recession. As global climate changes and natural habitats become increasingly fragmented, understanding patterns of seed dispersal and the potential for long-distance colonization takes on new importance. We studied the dispersal and establishment of the northern pitcher plant Sarracenia purpurea, which grows commonly in isolated bogs throughout Canada and eastern North America. Median dispersal distance of S. purpurea is only 5 cm, which is insufficient to explain its occurrence throughout formerly glaciated regions of North America. Establishment probability of seeds in the field is approximately 5%, and juveniles are normally found clustered around adult plants. The large-scale population genetic structure of this species can be accounted for by rare long-distance dispersal events, but its predictable occurrence in isolated habitats requires additional explanation. Reid's paradox remains an open question, and predicting long-range colonization into fragmented habitats by species with limited dispersal ability is a novel challenge.

Modeling Coherent Structures in Canopy Flows

NASA Astrophysics Data System (ADS)

Luhar, Mitul

2017-11-01

It is well known that flows over vegetation canopies are characterized by the presence of energetic coherent structures. Since the mean profile over dense canopies exhibits an inflection point, the emergence of such structures is often attributed to a Kelvin-Helmholtz instability. However, though stability analyses provide useful mechanistic insights into canopy flows, they are limited in their ability to generate predictions for spectra and coherent structure. The present effort seeks to address this limitation by extending the resolvent formulation (McKeon and Sharma, 2010, J. Fluid Mech.) to canopy flows. Under the resolvent formulation, the turbulent velocity field is expressed as a superposition of propagating modes, identified via a gain-based (singular value) decomposition of the Navier-Stokes equations. A key advantage of this approach is that it reconciles multiple mechanisms that lead to high amplification in turbulent flows, including modal instability, transient growth, and critical-layer phenomena. Further, individual high-gain modes can be combined to generate more complete models for coherent structure and velocity spectra. Preliminary resolvent-based model predictions for canopy flows agree well with existing experiments and simulations.

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.

Relationships and Predictive Capabilities of Jump Assessments to Soccer-Specific Field Test Performance in Division I Collegiate Players.

PubMed

Lockie, Robert G; Stage, Alyssa A; Stokes, John J; Orjalo, Ashley J; Davis, DeShaun L; Giuliano, Dominic V; Moreno, Matthew R; Risso, Fabrice G; Lazar, Adrina; Birmingham-Babauta, Samantha A; Tomita, Tricia M

2016-12-03

Leg power is an important characteristic for soccer, and jump tests can measure this capacity. Limited research has analyzed relationships between jumping and soccer-specific field test performance in collegiate male players. Nineteen Division I players completed tests of: leg power (vertical jump (VJ), standing broad jump (SBJ), left- and right-leg triple hop (TH)); linear (30 m sprint; 0⁻5 m, 5⁻10 m, 0⁻10, 0⁻30 m intervals) and change-of-direction (505) speed; soccer-specific fitness (Yo-Yo Intermittent Recovery Test Level 2); and 7 × 30-m sprints to measure repeated-sprint ability (RSA; total time (TT), performance decrement (PD)). Pearson's correlations ( r ) determined jump and field test relationships; stepwise regression ascertained jump predictors of the tests ( p < 0.05). All jumps correlated with the 0⁻5, 0⁻10, and 0⁻30 m sprint intervals ( r = -0.65⁻-0.90). VJ, SBJ, and left- and right-leg TH correlated with RSA TT ( r = -0.51⁻-0.59). Right-leg TH predicted the 0⁻5 and 0⁻10 m intervals (R² = 0.55⁻0.81); the VJ predicted the 0⁻30 m interval and RSA TT (R² = 0.41⁻0.84). Between-leg TH asymmetry correlated with and predicted left-leg 505 and RSA PD ( r = -0.68⁻0.62; R² = 0.39⁻0.46). Improvements in jumping ability could contribute to faster speed and RSA performance in collegiate soccer players.

Predicting progress in Picture Exchange Communication System (PECS) use by children with autism.

PubMed

Pasco, Greg; Tohill, Christina

2011-01-01

The Picture Exchange Communication System (PECS) is a widely used communication intervention for non-verbal children with autism spectrum disorder. Findings for the benefits of PECS have almost universally been positive, although there is very limited information about the characteristics of PECS users that determine the amount of progress that they are likely to make. To explore the utility of using children's developmental age to predict the subsequent degree of progress using PECS. In a retrospective study, 23 non-verbal 5- and 6-year-old children with autism spectrum disorder attending a special school were assessed to determine their highest level of PECS ability. They were then allocated to one of two groups depending on whether or not they had mastered PECS phase III. All participants had been assessed using the Psycho-Educational Profile-Revised (PEP-R) on entry to the school and before being introduced to PECS. Total developmental age scores were examined to determine whether they accurately predicted membership of the two PECS ability groups. All the 16 children who had mastered PECS phase III had total developmental age scores of 16 months or above, whilst six of the seven children who had not progressed beyond phase III scored below 16 months--the other child had a score of 16 months. The assessment of the developmental level of potential PECS users may provide valuable predictive information for speech-and-language therapists and other professionals in relation to the likely degree of progress and in setting realistic and achievable targets. © 2010 Royal College of Speech & Language Therapists.

A Portable Platform for Evaluation of Visual Performance in Glaucoma Patients

PubMed Central

Rosen, Peter N.; Boer, Erwin R.; Gracitelli, Carolina P. B.; Abe, Ricardo Y.; Diniz-Filho, Alberto; Marvasti, Amir H.; Medeiros, Felipe A.

2015-01-01

Purpose To propose a new tablet-enabled test for evaluation of visual performance in glaucoma, the PERformance CEntered Portable Test (PERCEPT), and to evaluate its ability to predict history of falls and motor vehicle crashes. Design Cross-sectional study. Methods The study involved 71 patients with glaucomatous visual field defects on standard automated perimetry (SAP) and 59 control subjects. The PERCEPT was based on the concept of increasing visual task difficulty to improve detection of central visual field losses in glaucoma patients. Subjects had to perform a foveal 8-alternative-forced-choice orientation discrimination task, while detecting a simultaneously presented peripheral stimulus within a limited presentation time. Subjects also underwent testing with the Useful Field of View (UFOV) divided attention test. The ability to predict history of motor vehicle crashes and falls was investigated by odds ratios and incident-rate ratios, respectively. Results When adjusted for age, only the PERCEPT processing speed parameter showed significantly larger values in glaucoma compared to controls (difference: 243ms; P<0.001). PERCEPT results had a stronger association with history of motor vehicle crashes and falls than UFOV. Each 1 standard deviation increase in PERCEPT processing speed was associated with an odds ratio of 2.69 (P = 0.003) for predicting history of motor vehicle crashes and with an incident-rate ratio of 1.95 (P = 0.003) for predicting history of falls. Conclusion A portable platform for testing visual function was able to detect functional deficits in glaucoma, and its results were significantly associated with history of involvement in motor vehicle crashes and history of falls. PMID:26445501

The Use of Statistical Downscaling to Project Regional Climate Changes as they Relate to Future Energy Production

NASA Astrophysics Data System (ADS)

Werth, D. W.; O'Steen, L.; Chen, K.; Altinakar, M. S.; Garrett, A.; Aleman, S.; Ramalingam, V.

2010-12-01

Global climate change has the potential for profound impacts on society, and poses significant challenges to government and industry in the areas of energy security and sustainability. Given that the ability to exploit energy resources often depends on the climate, the possibility of climate change means we cannot simply assume that the untapped potential of today will still exist in the future. Predictions of future climate are generally based on global climate models (GCMs) which, due to computational limitations, are run at spatial resolutions of hundreds of kilometers. While the results from these models can predict climatic trends averaged over large spatial and temporal scales, their ability to describe the effects of atmospheric phenomena that affect weather on regional to local scales is inadequate. We propose the use of several optimized statistical downscaling techniques that can infer climate change at the local scale from coarse resolution GCM predictions, and apply the results to assess future sustainability for two sources of energy production dependent on adequate water resources: nuclear power (through the dissipation of waste heat from cooling towers, ponds, etc.) and hydroelectric power. All methods will be trained with 20th century data, and applied to data from the years 2040-2049 to get the local-scale changes. Models of cooling tower operation and hydropower potential will then use the downscaled data to predict the possible changes in energy production, and the implications of climate change on plant siting, design, and contribution to the future energy grid can then be examined.

Auditory Brainstem Response to Complex Sounds Predicts Self-Reported Speech-in-Noise Performance

ERIC Educational Resources Information Center

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

2013-01-01

Purpose: 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,…

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…

An empirical investigation on the forecasting ability of mallows model averaging in a macro economic environment

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Hock-Eam, Lim

2012-09-01

This paper investigates the forecasting ability of Mallows Model Averaging (MMA) by conducting an empirical analysis of five Asia countries, Malaysia, Thailand, Philippines, Indonesia and China's GDP growth rate. Results reveal that MMA has no noticeable differences in predictive ability compared to the general autoregressive fractional integrated moving average model (ARFIMA) and its predictive ability is sensitive to the effect of financial crisis. MMA could be an alternative forecasting method for samples without recent outliers such as financial crisis.

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

PubMed

McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

2014-05-01

Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

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.

Correlation Between Critical Thinking Disposition and Mental Self-Supporting Ability in Nursing Undergraduates: A Cross-Sectional Descriptive Study.

PubMed

Wu, Defang; Luo, Yang; Liao, Xinyu

2017-02-01

There is universal agreement on the essential role of critical thinking in nursing practice. Most studies into this topic have provided descriptive statistical information and insights on related external factors such as educational environment and teaching strategies. However, there has been limited research into the psychological factors that may predict the disposition of students toward critical thinking. This study explored the relationship between the disposition of nursing students toward critical thinking and their mental self-supporting ability to obtain a profile and determine the psychological predictors of critical thinking. A cross-sectional descriptive study was conducted in 2013 using a convenience sample from four nursing schools. Four hundred six Chinese nursing undergraduates completed two questionnaires including (a) the California Critical Thinking Disposition Inventory (Chinese version) and (b) the Mental Self-Supporting Questionnaire for University Students. Pearson's correlation and linear regression analysis were used to investigate the relationship between these two variables and the predicted positive psychological qualities for the critical thinking disposition of participants. Average participant scores for critical thinking disposition and mental self-supporting were 280.91 ± 28.43 and 76.40 ± 8.47, respectively. Positive correlations were observed between these two variables (r = .583, p < .01) and participants' self-decision, self-cognition, self-confidence, and self-responsibility, which suggest that these factors play a significant role in critical thinking disposition (R = .435, p < .01). The participants earned midlevel scores for both disposition toward critical thinking and mental self-supporting abilities.The four factors that had a major influence on critical thinking disposition included self-decision, self-cognition, self-confidence, and self-responsibility. Nursing educators should focus on improving the critical thinking ability of their students in these four aspects.

Ability to Categorize Food Predicts Hypothetical Food Choices in Head Start Preschoolers.

PubMed

Nicholson, Jody S; Barton, Jennifer M; Simons, Ali L

2018-03-01

To investigate whether preschoolers are able to identify and categorize foods, and whether their ability to classify food as healthy predicts their hypothetical food choice. Structured interviews and body measurements with preschoolers, and teacher reports of classroom performance. Six Head Start centers in a large southeastern region. A total of 235 preschoolers (mean age [SD], 4.73 [0.63] years; 45.4% girls). Teachers implemented a nutrition education intervention across the 2014-2015 school year in which children were taught to identify and categorize food as sometimes (ie, unhealthy) and anytime (ie, healthy). Preschooler responses to a hypothetical snack naming, classifying, and selection scenario. Hierarchical regression analyses to examine predictors of child hypothetical food selection. While controlling for child characteristics and cognitive functioning, preschoolers who were better at categorizing food as healthy or unhealthy were more likely to say they would choose the healthy food. Low-contrast food pairs in which food had to be classified based on multiple dimensions were outside the cognitive abilities of the preschoolers. Nutrition interventions may be more effective in helping children make healthy food choices if developmental limitations in preschoolers' abilities to categorize food is addressed in their curriculum. Classification of food into evaluative categories is challenging for this age group. Categorizing on multiple dimensions is difficult, and dichotomous labeling of food as good or bad is not always accurate in directing children toward making food choices. Future research could evaluate further preschoolers' developmental potential for food categorization and nutrition decision making and consider factors that influence healthy food choices at both snack and mealtime. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Association of Individual Characteristics with Teleoperation Performance.

PubMed

Pan, Dan; Zhang, Yijing; Li, Zhizhong; Tian, Zhiqiang

2016-09-01

A number of space activities (e.g., extravehicular astronaut rescue, cooperation in satellite services, space station supplies, and assembly) are implemented directly or assisted by remote robotic arms. Our study aimed to reveal those individual characteristics which could positively influence or even predict teleoperation performance of such a space robotic arm. There were 64 male volunteers without robot operation experience recruited for the study. Their individual characteristics were assessed, including spatial cognitive ability, cognitive style, and personality traits. The experimental tasks were three abstracted teleoperation tasks of a simulated space robotic arm: point aiming, line alignment, and obstacle avoidance. Teleoperation performance was measured from two aspects: task performance (completion time, extra distance moved, operation slips) and safety performance (collisions, joint limitations reached). The Pearson coefficients between individual characteristics and teleoperation performance were examined along with performance prediction models. It was found that the subjects with relatively high mental rotation ability or low neuroticism had both better task and safety performance (|r| = 0.212 ∼ 0.381). Subjects with relatively high perspective taking ability or high agreeableness had better task performance (r = -0.253; r = -0.249). Imagery subjects performed better than verbal subjects regarding both task and safety performance (|r| = 0.236 ∼ 0.290). Compared with analytic subjects, wholist subjects had better safety performance (r = 0.300). Additionally, extraverted subjects had better task performance (r = -0.259), but worse safety performance (r = 0.230). Those with high spatial cognitive ability, imagery and wholist cognitive style, low neuroticism, and high agreeableness were seen to have more advantages in working with the remote robotic arm. These results could be helpful to astronaut selection and training for space station missions. Pan D, Zhang Y, Li Z, Tian Z. Association of individual characteristics with teleoperation performance. Aerosp Med Hum Perform. 2016; 87(9):772-780.

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study

PubMed Central

Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients. PMID:29904574

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study.

PubMed

Tacchella, Andrea; Romano, Silvia; Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients.

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Lopes, Leonard V.; Burley, Casey L.; Aumann, Aric R.

2013-01-01

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Multi-scale predictions of coniferous forest mortality in the northern hemisphere

NASA Astrophysics Data System (ADS)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.

Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated ‘Omics Approach

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

Lindemann, Stephen R.; Mobberley, Jennifer M.; Cole, Jessica K.

The principles governing acquisition and interspecies exchange of nutrients in microbial communities and how those exchanges impact community productivity are poorly understood. Here, we examine energy and macronutrient acquisition in unicyanobacterial consortia for which species-resolved genome information exists for all members, allowing us to use multi-omic approaches to predict species’ abilities to acquire resources and examine expression of resource-acquisition genes during succession. Metabolic reconstruction indicated that a majority of heterotrophic community members lacked the genes required to directly acquire the inorganic nutrients provided in culture medium, suggesting high metabolic interdependency. The sole primary producer in consortium UCC-O, cyanobacterium Phormidium sp.more » OSCR, displayed declining expression of energy harvest, carbon fixation, and nitrate and sulfate reduction proteins but sharply increasing phosphate transporter expression over 28 days. Most heterotrophic members likewise exhibited signs of phosphorus starvation during succession. Though similar in their responses to phosphorus limitation, heterotrophs displayed species-specific expression of nitrogen acquisition genes. These results suggest niche partitioning around nitrogen sources may structure the community when organisms directly compete for limited phosphate. Such niche complementarity around nitrogen sources may increase community diversity and productivity in phosphate-limited phototrophic communities.« less

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify ("specifically stain") various biomembranes and membranous organelles.

PubMed

Horobin, R W; Stockert, J C; Rashid-Doubell, F

2015-05-01

We discuss a variety of biological targets including generic biomembranes and the membranes of the endoplasmic reticulum, endosomes/lysosomes, Golgi body, mitochondria (outer and inner membranes) and the plasma membrane of usual fluidity. For each target, we discuss the access of probes to the target membrane, probe uptake into the membrane and the mechanism of selectivity of the probe uptake. A statement of the QSAR decision rule that describes the required physicochemical features of probes that enable selective staining also is provided, followed by comments on exceptions and limits. Examples of probes typically used to demonstrate each target structure are noted and decision rule tabulations are provided for probes that localize in particular targets; these tabulations show distribution of probes in the conceptual space defined by the relevant structure parameters ("parameter space"). Some general implications and limitations of the QSAR models for probe targeting are discussed including the roles of certain cell and protocol factors that play significant roles in lipid staining. A case example illustrates the predictive ability of QSAR models. Key limiting values of the head group hydrophilicity parameter associated with membrane-probe interactions are discussed in an appendix.

Kinetics of protein–ligand unbinding: Predicting pathways, rates, and rate-limiting steps

PubMed Central

Tiwary, Pratyush; Limongelli, Vittorio; Salvalaglio, Matteo; Parrinello, Michele

2015-01-01

The ability to predict the mechanisms and the associated rate constants of protein–ligand unbinding is of great practical importance in drug design. In this work we demonstrate how a recently introduced metadynamics-based approach allows exploration of the unbinding pathways, estimation of the rates, and determination of the rate-limiting steps in the paradigmatic case of the trypsin–benzamidine system. Protein, ligand, and solvent are described with full atomic resolution. Using metadynamics, multiple unbinding trajectories that start with the ligand in the crystallographic binding pose and end with the ligand in the fully solvated state are generated. The unbinding rate koff is computed from the mean residence time of the ligand. Using our previously computed binding affinity we also obtain the binding rate kon. Both rates are in agreement with reported experimental values. We uncover the complex pathways of unbinding trajectories and describe the critical rate-limiting steps with unprecedented detail. Our findings illuminate the role played by the coupling between subtle protein backbone fluctuations and the solvation by water molecules that enter the binding pocket and assist in the breaking of the shielded hydrogen bonds. We expect our approach to be useful in calculating rates for general protein–ligand systems and a valid support for drug design. PMID:25605901

Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated ‘Omics Approach

DOE PAGES

Lindemann, Stephen R.; Mobberley, Jennifer M.; Cole, Jessica K.; ...

2017-06-13

The principles governing acquisition and interspecies exchange of nutrients in microbial communities and how those exchanges impact community productivity are poorly understood. Here, we examine energy and macronutrient acquisition in unicyanobacterial consortia for which species-resolved genome information exists for all members, allowing us to use multi-omic approaches to predict species’ abilities to acquire resources and examine expression of resource-acquisition genes during succession. Metabolic reconstruction indicated that a majority of heterotrophic community members lacked the genes required to directly acquire the inorganic nutrients provided in culture medium, suggesting high metabolic interdependency. The sole primary producer in consortium UCC-O, cyanobacterium Phormidium sp.more » OSCR, displayed declining expression of energy harvest, carbon fixation, and nitrate and sulfate reduction proteins but sharply increasing phosphate transporter expression over 28 days. Most heterotrophic members likewise exhibited signs of phosphorus starvation during succession. Though similar in their responses to phosphorus limitation, heterotrophs displayed species-specific expression of nitrogen acquisition genes. These results suggest niche partitioning around nitrogen sources may structure the community when organisms directly compete for limited phosphate. Such niche complementarity around nitrogen sources may increase community diversity and productivity in phosphate-limited phototrophic communities.« less

Dispersal similarly shapes both population genetics and community patterns in the marine realm

PubMed Central

Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

2016-01-01

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns. PMID:27344967

Divided attention limits perception of 3-D object shapes

PubMed Central

Scharff, Alec; Palmer, John; Moore, Cathleen M.

2013-01-01

Can one perceive multiple object shapes at once? We tested two benchmark models of object shape perception under divided attention: an unlimited-capacity and a fixed-capacity model. Under unlimited-capacity models, shapes are analyzed independently and in parallel. Under fixed-capacity models, shapes are processed at a fixed rate (as in a serial model). To distinguish these models, we compared conditions in which observers were presented with simultaneous or sequential presentations of a fixed number of objects (The extended simultaneous-sequential method: Scharff, Palmer, & Moore, 2011a, 2011b). We used novel physical objects as stimuli, minimizing the role of semantic categorization in the task. Observers searched for a specific object among similar objects. We ensured that non-shape stimulus properties such as color and texture could not be used to complete the task. Unpredictable viewing angles were used to preclude image-matching strategies. The results rejected unlimited-capacity models for object shape perception and were consistent with the predictions of a fixed-capacity model. In contrast, a task that required observers to recognize 2-D shapes with predictable viewing angles yielded an unlimited capacity result. Further experiments ruled out alternative explanations for the capacity limit, leading us to conclude that there is a fixed-capacity limit on the ability to perceive 3-D object shapes. PMID:23404158

Genetic improvement in mastitis resistance: comparison of selection criteria from cross-sectional and random regression sire models for somatic cell score.

PubMed

Odegård, J; Klemetsdal, G; Heringstad, B

2005-04-01

Several selection criteria for reducing incidence of mastitis were developed from a random regression sire model for test-day somatic cell score (SCS). For comparison, sire transmitting abilities were also predicted based on a cross-sectional model for lactation mean SCS. Only first-crop daughters were used in genetic evaluation of SCS, and the different selection criteria were compared based on their correlation with incidence of clinical mastitis in second-crop daughters (measured as mean daughter deviations). Selection criteria were predicted based on both complete and reduced first-crop daughter groups (261 or 65 daughters per sire, respectively). For complete daughter groups, predicted transmitting abilities at around 30 d in milk showed the best predictive ability for incidence of clinical mastitis, closely followed by average predicted transmitting abilities over the entire lactation. Both of these criteria were derived from the random regression model. These selection criteria improved accuracy of selection by approximately 2% relative to a cross-sectional model. However, for reduced daughter groups, the cross-sectional model yielded increased predictive ability compared with the selection criteria based on the random regression model. This result may be explained by the cross-sectional model being more robust, i.e., less sensitive to precision of (co)variance components estimates and effects of data structure.

Ability emotional intelligence and its relation to aggression across time and age groups.

PubMed

García-Sancho, Esperanza; Salguero, José M; Fernández-Berrocal, Pablo

2017-02-01

Emotional Intelligence (EI) has been associated with several indicators of psychosocial adjustment, including aggressive behavior, but the relevant research has been mostly cross-sectional, focused on adults, and limited to trait EI measures (García-Sancho, Salguero & Fernández-Berrocal, 2014; Mayer, Roberts & Barsade, ). The present work explored the relationship between Ability Emotional Intelligence (AEI) and aggression in both adults and adolescents using cross-sectional and longitudinal designs. We conducted two studies. Study 1 aimed to provide preliminary evidence about the relationship between AEI and aggression in adults. As literature has shown personality traits act as a strong predictor of aggression, study 1 also examined the potential incremental validity of AEI beyond personality traits in 474 undergraduate students (M = 22.76, SD = 5.13). The results indicated AEI explains a significant amount of unique variance for physical aggression, but not for verbal aggression after controlling personality traits. Study 2 aimed a longitudinal analysis of the relationship between EI and aggression in 151 adolescents (M = 14.74, SD = 0.84). AEI predicted physical aggression over time, but it did not predict verbal aggression. Results from both studies suggest a negative and significant relationship between AEI and physical aggression, however contrary our expectations, it did not for verbal aggression. These results highlight the important explanatory role of emotional abilities in physical aggressive conducts and the implications of these findings are discussed. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Hydrological Predictability for the Peruvian Amazon

NASA Astrophysics Data System (ADS)

Towner, Jamie; Stephens, Elizabeth; Cloke, Hannah; Bazo, Juan; Coughlan, Erin; Zsoter, Ervin

2017-04-01

Population growth in the Peruvian Amazon has prompted the expansion of livelihoods further into the floodplain and thus increasing vulnerability to the annual rise and fall of the river. This growth has coincided with a period of increasing hydrological extremes with more frequent severe flood events. The anticipation and forecasting of these events is crucial for mitigating vulnerability. Forecast-based Financing (FbF) an initiative of the German Red Cross implements risk reducing actions based on threshold exceedance within hydrometeorological forecasts using the Global Flood Awareness System (GloFAS). However, the lead times required to complete certain actions can be long (e.g. several weeks to months ahead to purchase materials and reinforce houses) and are beyond the current capabilities of GloFAS. Therefore, further calibration of the model is required in addition to understanding the climatic drivers and associated hydrological response for specific flood events, such as those observed in 2009, 2012 and 2015. This review sets out to determine the current capabilities of the GloFAS model while exploring the limits of predictability for the Amazon basin. More specifically, how the temporal patterns of flow within the main coinciding tributaries correspond to the overall Amazonian flood wave under various climatic and meteorological influences. Linking the source areas of flow to predictability within the seasonal forecasting system will develop the ability to expand the limit of predictability of the flood wave. This presentation will focus on the Iquitos region of Peru, while providing an overview of the new techniques and current challenges faced within seasonal flood prediction.

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.

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

Predicting Cognitive, Functional, and Diagnostic Change over 4 Years Using Baseline Subjective Cognitive Complaints in the Sydney Memory and Ageing Study.

PubMed

Slavin, Melissa J; Sachdev, Perminder S; Kochan, Nicole A; Woolf, Claudia; Crawford, John D; Giskes, Katrina; Reppermund, Simone; Trollor, Julian N; Draper, Brian; Delbaere, Kim; Brodaty, Henry

2015-09-01

There is limited understanding of the usefulness of subjective cognitive complaint(s) (SCC) in predicting longitudinal outcome because most studies focus solely on memory (as opposed to nonmemory cognitive) complaints, do not collect data from both participants and informants, do not control for relevant covariates, and have limited outcome measures. Therefore the authors investigate the usefulness of participant and informant SCCs in predicting change in cognition, functional abilities, and diagnostic classification of mild cognitive impairment or dementia in a community-dwelling sample over 4 years. Nondemented participants (N = 620) in the Sydney Memory and Ageing Study aged between 70 and 90 years completed 15 memory and 9 nonmemory SCC questions. An informant completed a baseline questionnaire that included 15 memory and 4 nonmemory SCC questions relating to the participant. Neuropsychological, functional, and diagnostic assessments were carried out at baseline and again at 4-year follow-up. Cross-sectional and longitudinal analyses were carried out to determine the association between SCC indices and neuropsychological, functional, and diagnostic data while controlling for psychological measures. Once participant characteristics were controlled for, participant complaints were generally not predictive of cognitive or functional decline, although participant memory-specific complaints were predictive of diagnostic conversion. Informant-related memory questions were associated with global cognitive and functional decline and with diagnostic conversion over 4 years. Informant memory complaint questions were better than participant complaints in predicting cognitive and functional decline as well as diagnoses over 4 years. Copyright © 2015 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Predictive ability of severe rainfall events over Catalonia for the year 2008

NASA Astrophysics Data System (ADS)

Comellas, A.; Molini, L.; Parodi, A.; Sairouni, A.; Llasat, M. C.; Siccardi, F.

2011-07-01

This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9-10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (≤24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC) rainfall forecasts; therefore we have not taken into account those episodes that might (or might not) have been missed by the official SMC warnings. Therefore, whenever we talk about "misses", it is always in relation to the deterministic LAMs' QPFs.

Injuries among powered two-wheeler users in eight European countries: a descriptive analysis of hospital discharge data.

PubMed

Forman, Jason L; Lopez-Valdes, Francisco J; Pollack, Keshia; Heredero-Ordoyo, Rafael; Molinero, Aquilino; Mansilla, Alberto; Fildes, Brian; Segui-Gomez, Maria

2012-11-01

Powered two-wheelers (PTWs--mopeds, motorcycles, and scooters) remain the most dangerous form of travel on today's roads. This study used hospital discharge data from eight European countries to examine the frequencies and patterns of injury among PTW users (age≥14 years), the predicted incidence of the loss of functional ability, and the mechanisms of the head injuries observed (all in light of increased helmet use). Of 977,557 injured patients discharged in 2004, 12,994 were identified as having been injured in PTW collisions. Lower extremity injuries accounted for 26% (25.6-26.7, 95% C.I.) of the total injuries, followed by upper extremity injuries (20.7%: 20.3-21.2), traumatic brain injuries (TBI) (18.5%: 18-19), and thoracic injuries (8.2%: 7.8-8.5). Approximately 80% of the lower extremity injury cases were expected to exhibit some functional disability one year following discharge (predicted Functional Capacity Index, pFCI-AIS98<100), compared to 47% of the upper extremity injury cases and 24% of the TBI cases. Although it occurred less frequently, patients that were expected to experience some functional limitation from TBI were predicted to fair worse on average (lose more functional ability) than patients expected to have functional limitations from extremity injuries. Cerebral concussion was the most common head injury observed (occurring in 56% of head injury cases), with most concussion cases (78%) exhibiting no other head injury. Among the AIS3+ head injuries that could be mapped to an injury mechanism, 48% of these were associated with a translational-impact mechanism, and 37% were associated with a rotational mechanism. The observation of high rates of expected long-term disability suggests that future efforts aim to mitigate lower and upper extremity injuries among PTW users. Likewise, the high rates of concussion and head injuries associated with a rotational mechanism provide goals for the next phase of PTW user head protection. Copyright © 2011 Elsevier Ltd. All rights reserved.

Predictive factors for work capacity in patients with musculoskeletal disorders.

PubMed

Lydell, Marie; Baigi, Amir; Marklund, Bertil; Månsson, Jörgen

2005-09-01

To identify predictive factors for work capacity in patients with musculoskeletal disorders. A descriptive, evaluative, quantitative study. The study was based on 385 patients who participated in a rehabilitation programme. Patients were divided into 2 groups depending on their ability to work. The groups were compared with each other with regard to sociodemographic factors, diagnoses, disability pension and number of sick days. The patient's level of exercise habits, ability to undertake activities, physical capacity, pain and quality of life were compared further using logistic regression analysis. Predictive factors for work capacity, such as ability to undertake activities, quality of life and fitness on exercise, were identified as important independent factors. Other well-known factors, i.e. gender, age, education, pain and earlier sickness certification periods, were also identified. Factors that were not significantly different between the groups were employment status, profession, diagnosis and levels of exercise habits. Identifying predictors for ability to return to work is an essential task for deciding on suitable individual rehabilitation. This study identified new predictive factors, such as ability to undertake activities, quality of life and fitness on exercise.

Eighteen-month-olds' ability to make gaze predictions following distraction or a long delay.

PubMed

Forssman, Linda; Bohlin, Gunilla; von Hofsten, Claes

2014-05-01

The abilities to flexibly allocate attention, select between conflicting stimuli, and make anticipatory gaze movements are important for young children's exploration and learning about their environment. These abilities constitute voluntary control of attention and show marked improvements in the second year of a child's life. Here we investigate the effects of visual distraction and delay on 18-month-olds' ability to predict the location of an occluded target in an experiment that requires switching of attention, and compare their performance to that of adults. Our results demonstrate that by 18 months of age children can readily overcome a previously learned response, even under a condition that involves visual distraction, but have difficulties with correctly updating their prediction when presented with a longer time delay. Further, the experiment shows that, overall, the 18-month-olds' allocation of visual attention is similar to that of adults, the primary difference being that adults demonstrate a superior ability to maintain attention on task and update their predictions over a longer time period. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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.

Electrical Resistance as a NDE Technique to Monitor Processing and Damage Accumulation in SiC/SiC Composites

NASA Technical Reports Server (NTRS)

Smith, Craig; Morscher, Gregory N.; Xia, Zhenhai

2008-01-01

Ceramic matrix composites are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems. The employment of these materials in such applications is limited by the ability to process components reliable and to accurately monitor and predict damage evolution that leads to failure under stressed-oxidation conditions. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. Electrical resistance of SiC/SiC composites is one technique that shows special promise towards this end. Since both the matrix and the fibers are conductive, changes in matrix or fiber properties should relate to changes in electrical conductivity along the length of a specimen or part. Initial efforts to quantify the electrical resistance of different fiber and different matrix SiC/SiC composites will be presented. Also, the effect of matrix cracking on electrical resistivity for several composite systems will be presented. The implications towards electrical resistance as a technique applied to composite processing, damage detection, and life-modeling will be discussed.

Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture.

PubMed

Ni, Guiyan; Cavero, David; Fangmann, Anna; Erbe, Malena; Simianer, Henner

2017-01-16

With the availability of next-generation sequencing technologies, genomic prediction based on whole-genome sequencing (WGS) data is now feasible in animal breeding schemes and was expected to lead to higher predictive ability, since such data may contain all genomic variants including causal mutations. Our objective was to compare prediction ability with high-density (HD) array data and WGS data in a commercial brown layer line with genomic best linear unbiased prediction (GBLUP) models using various approaches to weight single nucleotide polymorphisms (SNPs). A total of 892 chickens from a commercial brown layer line were genotyped with 336 K segregating SNPs (array data) that included 157 K genic SNPs (i.e. SNPs in or around a gene). For these individuals, genome-wide sequence information was imputed based on data from re-sequencing runs of 25 individuals, leading to 5.2 million (M) imputed SNPs (WGS data), including 2.6 M genic SNPs. De-regressed proofs (DRP) for eggshell strength, feed intake and laying rate were used as quasi-phenotypic data in genomic prediction analyses. Four weighting factors for building a trait-specific genomic relationship matrix were investigated: identical weights, -(log 10 P) from genome-wide association study results, squares of SNP effects from random regression BLUP, and variable selection based weights (known as BLUP|GA). Predictive ability was measured as the correlation between DRP and direct genomic breeding values in five replications of a fivefold cross-validation. Averaged over the three traits, the highest predictive ability (0.366 ± 0.075) was obtained when only genic SNPs from WGS data were used. Predictive abilities with genic SNPs and all SNPs from HD array data were 0.361 ± 0.072 and 0.353 ± 0.074, respectively. Prediction with -(log 10 P) or squares of SNP effects as weighting factors for building a genomic relationship matrix or BLUP|GA did not increase accuracy, compared to that with identical weights, regardless of the SNP set used. Our results show that little or no benefit was gained when using all imputed WGS data to perform genomic prediction compared to using HD array data regardless of the weighting factors tested. However, using only genic SNPs from WGS data had a positive effect on prediction ability.

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.

Prediction of welding shrinkage deformation of bridge steel box girder based on wavelet neural network

NASA Astrophysics Data System (ADS)

Tao, Yulong; Miao, Yunshui; Han, Jiaqi; Yan, Feiyun

2018-05-01

Aiming at the low accuracy of traditional forecasting methods such as linear regression method, this paper presents a prediction method for predicting the relationship between bridge steel box girder and its displacement with wavelet neural network. Compared with traditional forecasting methods, this scheme has better local characteristics and learning ability, which greatly improves the prediction ability of deformation. Through analysis of the instance and found that after compared with the traditional prediction method based on wavelet neural network, the rigid beam deformation prediction accuracy is higher, and is superior to the BP neural network prediction results, conform to the actual demand of engineering design.

Relationship between Perceived Limit-Setting Abilities, Autism Spectrum Disorder Severity, Behaviour Problems and Parenting Stress in Mothers of Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Reed, Phil; Howse, Jessie; Ho, Ben; Osborne, Lisa A.

2017-01-01

Parenting stress in mothers of children with autism spectrum disorder (ASD) is high and impacts perceptions about parenting. This study examined the relationship between parenting stress and observer-perceived limit-setting ability. Participants' perceptions of other parents' limit-setting ability were assessed by showing participants video clips…

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

PubMed Central

Jespersen, Martin Closter; Peters, Bjoern

2017-01-01

Abstract Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy and non-expert users. We believe that BepiPred-2.0 will be a valuable tool for the bioinformatics and immunology community. PMID:28472356

Clinical history and biologic age predicted falls better than objective functional tests.

PubMed

Gerdhem, Paul; Ringsberg, Karin A M; Akesson, Kristina; Obrant, Karl J

2005-03-01

Fall risk assessment is important because the consequences, such as a fracture, may be devastating. The objective of this study was to find the test or tests that best predicted falls in a population-based sample of elderly women. The fall-predictive ability of a questionnaire, a subjective estimate of biologic age and objective functional tests (gait, balance [Romberg and sway test], thigh muscle strength, and visual acuity) were compared in 984 randomly selected women, all 75 years of age. A recalled fall was the most important predictor for future falls. Only recalled falls and intake of psycho-active drugs independently predicted future falls. Women with at least five of the most important fall predictors (previous falls, conditions affecting the balance, tendency to fall, intake of psychoactive medication, inability to stand on one leg, high biologic age) had an odds ratio of 11.27 (95% confidence interval 4.61-27.60) for a fall (sensitivity 70%, specificity 79%). The more time-consuming objective functional tests were of limited importance for fall prediction. A simple clinical history, the inability to stand on one leg, and a subjective estimate of biologic age were more important as part of the fall risk assessment.

Sex-specific lean body mass predictive equations are accurate in the obese paediatric population

PubMed Central

Jackson, Lanier B.; Henshaw, Melissa H.; Carter, Janet; Chowdhury, Shahryar M.

2015-01-01

Background The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. Aim The purpose of this study was to independently validate these predictive equations in the obese paediatric population. Subjects and methods Obese subjects aged 4–21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. Results Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was −0.6% (−17.0%, 15.8%). Pearson’s correlation revealed a strong linear relationship between LBMm and LBMp (r=0.97, p<0.01). Conclusion This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children. PMID:26287383

Applicability of a panel method, which includes nonlinear effects, to a forward-swept-wing aircraft

NASA Technical Reports Server (NTRS)

Ross, J. C.

1984-01-01

The ability of a lower order panel method VSAERO, to accurately predict the lift and pitching moment of a complete forward-swept-wing/canard configuration was investigated. The program can simulate nonlinear effects including boundary-layer displacement thickness, wake roll up, and to a limited extent, separated wakes. The predictions were compared with experimental data obtained using a small-scale model in the 7- by 10- Foot Wind Tunnel at NASA Ames Research Center. For the particular configuration under investigation, wake roll up had only a small effect on the force and moment predictions. The effect of the displacement thickness modeling was to reduce the lift curve slope slightly, thus bringing the predicted lift into good agreement with the measured value. Pitching moment predictions were also improved by the boundary-layer simulation. The separation modeling was found to be sensitive to user inputs, but appears to give a reasonable representation of a separated wake. In general, the nonlinear capabilities of the code were found to improve the agreement with experimental data. The usefullness of the code would be enhanced by improving the reliability of the separated wake modeling and by the addition of a leading edge separation model.

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.

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.

Stigma as ego depletion: how being the target of prejudice affects self-control.

PubMed

Inzlicht, Michael; McKay, Linda; Aronson, Joshua

2006-03-01

This research examined whether stigma diminishes people's ability to control their behaviors. Because coping with stigma requires self-regulation, and self-regulation is a limited-capacity resource, we predicted that individuals belonging to stigmatized groups are less able to regulate their own behavior when they become conscious of their stigmatizing status or enter threatening environments. Study 1 uncovered a correlation between stigma sensitivity and self-regulation; the more Black college students were sensitive to prejudice, the less self-control they reported having. By experimentally activating stigma, Studies 2 and 3 provided causal evidence for stigma's ego-depleting qualities: When their stigma was activated, stigmatized participants (Black students and females) showed impaired self-control in two very different domains (attentional and physical self-regulation). These results suggest that (a) stigma is ego depleting and (b) coping with it can weaken the ability to control and regulate one's behaviors in domains unrelated to the stigma.

Functional evolution and structural conservation in chimeric cytochromes p450: calibrating a structure-guided approach.

PubMed

Otey, Christopher R; Silberg, Jonathan J; Voigt, Christopher A; Endelman, Jeffrey B; Bandara, Geethani; Arnold, Frances H

2004-03-01

Recombination generates chimeric proteins whose ability to fold depends on minimizing structural perturbations that result when portions of the sequence are inherited from different parents. These chimeric sequences can display functional properties characteristic of the parents or acquire entirely new functions. Seventeen chimeras were generated from two CYP102 members of the functionally diverse cytochrome p450 family. Chimeras predicted to have limited structural disruption, as defined by the SCHEMA algorithm, displayed CO binding spectra characteristic of folded p450s. Even this small population exhibited significant functional diversity: chimeras displayed altered substrate specificities, a wide range in thermostabilities, up to a 40-fold increase in peroxidase activity, and ability to hydroxylate a substrate toward which neither parent heme domain shows detectable activity. These results suggest that SCHEMA-guided recombination can be used to generate diverse p450s for exploring function evolution within the p450 structural framework.

Close encounters with DNA

PubMed Central

Maffeo, C.; Yoo, J.; Comer, J.; Wells, D. B.; Luan, B.; Aksimentiev, A.

2014-01-01

Over the past ten years, the all-atom molecular dynamics method has grown in the scale of both systems and processes amenable to it and in its ability to make quantitative predictions about the behavior of experimental systems. The field of computational DNA research is no exception, witnessing a dramatic increase in the size of systems simulated with atomic resolution, the duration of individual simulations and the realism of the simulation outcomes. In this topical review, we describe the hallmark physical properties of DNA from the perspective of all-atom simulations. We demonstrate the amazing ability of such simulations to reveal the microscopic physical origins of experimentally observed phenomena and we review the frustrating limitations associated with imperfections of present atomic force fields and inadequate sampling. The review is focused on the following four physical properties of DNA: effective electric charge, response to an external mechanical force, interaction with other DNA molecules and behavior in an external electric field. PMID:25238560

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

Lu, Liqiang; Gao, Xi; Li, Tingwen

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models tomore » predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.« less

Potential effects of global warming on the distribution of a temperate univoltine insect

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

Rooney, T.P.; Hurd, L.E.

1993-06-01

Poleward migration to remain within temperature tolerance ranges as the earth warms poses a problem for species with limited dispersal abilities. The life cycle of a typical temperate univoltine insect, Tenodera sinensis (Mantodea: Mantidae), is constrained by degree-days per season: too few prevent maturation before killing frost in the fall; too many allow egg hatch prior to killing frost. We combined field observations of dispersal ability with laboratory measurements of the relationship between temperature and maturation rate, and applied these to a global warming model to predict the effect of climate change on regional distribution of this insect by 2100more » A.D. Based on the simplified biological assumptions of our model, T, sinensis would be reduced to local populations in the northern portions and higher elevations of its present broadly contiguous range, and species with similar life histories may face regional or total extinction.« less

The Curse of Expertise: When More Knowledge Leads to Miscalibrated Explanatory Insight.

PubMed

Fisher, Matthew; Keil, Frank C

2016-07-01

Does expertise within a domain of knowledge predict accurate self-assessment of the ability to explain topics in that domain? We find that expertise increases confidence in the ability to explain a wide variety of phenomena. However, this confidence is unwarranted; after actually offering full explanations, people are surprised by the limitations in their understanding. For passive expertise (familiar topics), miscalibration is moderated by education; those with more education are accurate in their self-assessments (Experiment 1). But when those with more education consider topics related to their area of concentrated study (college major), they also display an illusion of understanding (Experiment 2). This "curse of expertise" is explained by a failure to recognize the amount of detailed information that had been forgotten (Experiment 3). While expertise can sometimes lead to accurate self-knowledge, it can also create illusions of competence. Copyright © 2015 Cognitive Science Society, Inc.

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

PubMed

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Close encounters with DNA.

PubMed

Maffeo, C; Yoo, J; Comer, J; Wells, D B; Luan, B; Aksimentiev, A

2014-10-15

Over the past ten years, the all-atom molecular dynamics method has grown in the scale of both systems and processes amenable to it and in its ability to make quantitative predictions about the behavior of experimental systems. The field of computational DNA research is no exception, witnessing a dramatic increase in the size of systems simulated with atomic resolution, the duration of individual simulations and the realism of the simulation outcomes. In this topical review, we describe the hallmark physical properties of DNA from the perspective of all-atom simulations. We demonstrate the amazing ability of such simulations to reveal the microscopic physical origins of experimentally observed phenomena. We also discuss the frustrating limitations associated with imperfections of present atomic force fields and inadequate sampling. The review is focused on the following four physical properties of DNA: effective electric charge, response to an external mechanical force, interaction with other DNA molecules and behavior in an external electric field.

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE PAGES

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent; ...

2018-03-06

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

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

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Short communication: cheminformatics analysis to identify predictors of antiviral drug penetration into the female genital tract.

PubMed

Thompson, Corbin G; Sedykh, Alexander; Nicol, Melanie R; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Kashuba, Angela D M

2014-11-01

The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R(2)test=0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ≥1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

Improved regulatory element prediction based on tissue-specific local epigenomic signatures

PubMed Central

He, Yupeng; Gorkin, David U.; Dickel, Diane E.; Nery, Joseph R.; Castanon, Rosa G.; Lee, Ah Young; Shen, Yin; Visel, Axel; Pennacchio, Len A.; Ren, Bing; Ecker, Joseph R.

2017-01-01

Accurate enhancer identification is critical for understanding the spatiotemporal transcriptional regulation during development as well as the functional impact of disease-related noncoding genetic variants. Computational methods have been developed to predict the genomic locations of active enhancers based on histone modifications, but the accuracy and resolution of these methods remain limited. Here, we present an algorithm, regulatory element prediction based on tissue-specific local epigenetic marks (REPTILE), which integrates histone modification and whole-genome cytosine DNA methylation profiles to identify the precise location of enhancers. We tested the ability of REPTILE to identify enhancers previously validated in reporter assays. Compared with existing methods, REPTILE shows consistently superior performance across diverse cell and tissue types, and the enhancer locations are significantly more refined. We show that, by incorporating base-resolution methylation data, REPTILE greatly improves upon current methods for annotation of enhancers across a variety of cell and tissue types. REPTILE is available at https://github.com/yupenghe/REPTILE/. PMID:28193886

Detection of Tetracycline in Milk using NIR Spectroscopy and Partial Least Squares

NASA Astrophysics Data System (ADS)

Wu, Nan; Xu, Chenshan; Yang, Renjie; Ji, Xinning; Liu, Xinyuan; Yang, Fan; Zeng, Ming

2018-02-01

The feasibility of measuring tetracycline in milk was investigated by near infrared (NIR) spectroscopic technique combined with partial least squares (PLS) method. The NIR transmittance spectra of 40 pure milk samples and 40 tetracycline adulterated milk samples with different concentrations (from 0.005 to 40 mg/L) were obtained. The pure milk and tetracycline adulterated milk samples were properly assigned to the categories with 100% accuracy in the calibration set, and the rate of correct classification of 96.3% was obtained in the prediction set. For the quantitation of tetracycline in adulterated milk, the root mean squares errors for calibration and prediction models were 0.61 mg/L and 4.22 mg/L, respectively. The PLS model had good fitting effect in calibration set, however its predictive ability was limited, especially for low tetracycline concentration samples. Totally, this approach can be considered as a promising tool for discrimination of tetracycline adulterated milk, as a supplement to high performance liquid chromatography.

Challenges in microbial ecology: building predictive understanding of community function and dynamics

PubMed Central

Widder, Stefanie; Allen, Rosalind J; Pfeiffer, Thomas; Curtis, Thomas P; Wiuf, Carsten; Sloan, William T; Cordero, Otto X; Brown, Sam P; Momeni, Babak; Shou, Wenying; Kettle, Helen; Flint, Harry J; Haas, Andreas F; Laroche, Béatrice; Kreft, Jan-Ulrich; Rainey, Paul B; Freilich, Shiri; Schuster, Stefan; Milferstedt, Kim; van der Meer, Jan R; Groβkopf, Tobias; Huisman, Jef; Free, Andrew; Picioreanu, Cristian; Quince, Christopher; Klapper, Isaac; Labarthe, Simon; Smets, Barth F; Wang, Harris; Soyer, Orkun S

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved. PMID:27022995

How does the Earth system generate and maintain thermodynamic disequilibrium and what does it imply for the future of the planet?

PubMed

Kleidon, Axel

2012-03-13

The Earth's chemical composition far from chemical equilibrium is unique in our Solar System, and this uniqueness has been attributed to the presence of widespread life on the planet. Here, I show how this notion can be quantified using non-equilibrium thermodynamics. Generating and maintaining disequilibrium in a thermodynamic variable requires the extraction of power from another thermodynamic gradient, and the second law of thermodynamics imposes fundamental limits on how much power can be extracted. With this approach and associated limits, I show that the ability of abiotic processes to generate geochemical free energy that can be used to transform the surface-atmosphere environment is strongly limited to less than 1 TW. Photosynthetic life generates more than 200 TW by performing photochemistry, thereby substantiating the notion that a geochemical composition far from equilibrium can be a sign for strong biotic activity. Present-day free energy consumption by human activity in the form of industrial activity and human appropriated net primary productivity is of the order of 50 TW and therefore constitutes a considerable term in the free energy budget of the planet. When aiming to predict the future of the planet, we first note that since global changes are closely related to this consumption of free energy, and the demands for free energy by human activity are anticipated to increase substantially in the future, the central question in the context of predicting future global change is then how human free energy demands can increase sustainably without negatively impacting the ability of the Earth system to generate free energy. This question could be evaluated with climate models, and the potential deficiencies in these models to adequately represent the thermodynamics of the Earth system are discussed. Then, I illustrate the implications of this thermodynamic perspective by discussing the forms of renewable energy and planetary engineering that would enhance the overall free energy generation and, thereby 'empower' the future of the planet.

Anthropometric measures in cardiovascular disease prediction: comparison of laboratory-based versus non-laboratory-based model.

PubMed

Dhana, Klodian; Ikram, M Arfan; Hofman, Albert; Franco, Oscar H; Kavousi, Maryam

2015-03-01

Body mass index (BMI) has been used to simplify cardiovascular risk prediction models by substituting total cholesterol and high-density lipoprotein cholesterol. In the elderly, the ability of BMI as a predictor of cardiovascular disease (CVD) declines. We aimed to find the most predictive anthropometric measure for CVD risk to construct a non-laboratory-based model and to compare it with the model including laboratory measurements. The study included 2675 women and 1902 men aged 55-79 years from the prospective population-based Rotterdam Study. We used Cox proportional hazard regression analysis to evaluate the association of BMI, waist circumference, waist-to-hip ratio and a body shape index (ABSI) with CVD, including coronary heart disease and stroke. The performance of the laboratory-based and non-laboratory-based models was evaluated by studying the discrimination, calibration, correlation and risk agreement. Among men, ABSI was the most informative measure associated with CVD, therefore ABSI was used to construct the non-laboratory-based model. Discrimination of the non-laboratory-based model was not different than laboratory-based model (c-statistic: 0.680-vs-0.683, p=0.71); both models were well calibrated (15.3% observed CVD risk vs 16.9% and 17.0% predicted CVD risks by the non-laboratory-based and laboratory-based models, respectively) and Spearman rank correlation and the agreement between non-laboratory-based and laboratory-based models were 0.89 and 91.7%, respectively. Among women, none of the anthropometric measures were independently associated with CVD. Among middle-aged and elderly where the ability of BMI to predict CVD declines, the non-laboratory-based model, based on ABSI, could predict CVD risk as accurately as the laboratory-based model among men. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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

PubMed Central

2017-01-01

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

Does the Value of Dynamic Assessment in Predicting End-of-First-Grade Mathematics Performance Differ as a Function of English Language Proficiency?

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2015-01-01

The purpose of this study was to assess the added value of dynamic assessment (DA) beyond more conventional static measures for predicting individual differences in year-end 1st-grade calculation (CA) and word-problem (WP) performance, as a function of limited English proficiency (LEP) status. At the start of 1st grade, students (129 LEP; 163 non-LEP) were assessed on a brief static mathematics test, an extended static mathematics test, static tests of domain-general abilities associated with CAs and WPs (vocabulary; reasoning), and DA. Near end of 1st grade, they were assessed on CA and WP. Regression analyses indicated that the value of the predictor depends on the predicted outcome and LEP status. In predicting CAs, the extended mathematics test and DA uniquely explained variance for LEP children, with stronger predictive value for the extended mathematics test; for non-LEP children, the extended mathematics test was the only significant predictor. However, in predicting WPs, only DA and vocabulary were uniquely predictive for LEP children, with stronger value for DA; for non-LEP children, the extended mathematics test and DA were comparably uniquely predictive. Neither the brief static mathematics test nor reasoning was significant in predicting either outcome. The potential value of a gated screening process, using an extended mathematics assessment to predict CAs and using DA to predict WPs, is discussed. PMID:26523068

Ensemble forecast of human West Nile virus cases and mosquito infection rates

NASA Astrophysics Data System (ADS)

Defelice, Nicholas B.; Little, Eliza; Campbell, Scott R.; Shaman, Jeffrey

2017-02-01

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

Ensemble forecast of human West Nile virus cases and mosquito infection rates.

PubMed

DeFelice, Nicholas B; Little, Eliza; Campbell, Scott R; Shaman, Jeffrey

2017-02-24

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

Application of a Physics-Based Stabilization Criterion to Flight System Thermal Testing

NASA Technical Reports Server (NTRS)

Baker, Charles; Garrison, Matthew; Cottingham, Christine; Peabody, Sharon

2010-01-01

The theory shown here can provide thermal stability criteria based on physics and a goal steady state error rather than on an arbitrary "X% Q/mC(sub P)" method. The ability to accurately predict steady-state temperatures well before thermal balance is reached could be very useful during testing. This holds true for systems where components are changing temperature at different rates, although it works better for the components closest to the sink. However, the application to these test cases shows some significant limitations: This theory quickly falls apart if the thermal control system in question is tightly coupled to a large mass not accounted for in the calculations, so it is more useful in subsystem-level testing than full orbiter tests. Tight couplings to a fluctuating sink causes noise in the steady state temperature predictions.

Empirical estimates to reduce modeling uncertainties of soil organic carbon in permafrost regions: a review of recent progress and remaining challenges

USGS Publications Warehouse

Mishra, U.; Jastrow, J.D.; Matamala, R.; Hugelius, G.; Koven, C.D.; Harden, Jennifer W.; Ping, S.L.; Michaelson, G.J.; Fan, Z.; Miller, R.M.; McGuire, A.D.; Tarnocai, C.; Kuhry, P.; Riley, W.J.; Schaefer, K.; Schuur, E.A.G.; Jorgenson, M.T.; Hinzman, L.D.

2013-01-01

The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.

Receiver operating characteristic analysis. Application to the study of quantum fluctuation effects in optic nerve of Rana pipiens

PubMed Central

1975-01-01

Receiver operating characteristic (ROC) analysis of nerve messages is described. The hypothesis that quantum fluctuations provide the only limit to the ability of frog ganglion cells to signal luminance change information is examined using ROC analysis. In the context of ROC analysis, the quantum fluctuation hypothesis predicts (a) the detectability of a luminance change signal should rise proportionally to the size of the change, (b) detectability should decrease as the square root of background, an implication of which is the deVries-Rose law, and (c) ROC curves should exhibit a shape particular to underlying Poisson distributions. Each of these predictions is confirmed for the responses of dimming ganglion cells to brief luminance decrements at scotopic levels, but none could have been tested using classical nerve message analysis procedures. PMID:172597

Current Trends in Modeling Research for Turbulent Aerodynamic Flows

NASA Technical Reports Server (NTRS)

Gatski, Thomas B.; Rumsey, Christopher L.; Manceau, Remi

2007-01-01

The engineering tools of choice for the computation of practical engineering flows have begun to migrate from those based on the traditional Reynolds-averaged Navier-Stokes approach to methodologies capable, in theory if not in practice, of accurately predicting some instantaneous scales of motion in the flow. The migration has largely been driven by both the success of Reynolds-averaged methods over a wide variety of flows as well as the inherent limitations of the method itself. Practitioners, emboldened by their ability to predict a wide-variety of statistically steady, equilibrium turbulent flows, have now turned their attention to flow control and non-equilibrium flows, that is, separation control. This review gives some current priorities in traditional Reynolds-averaged modeling research as well as some methodologies being applied to a new class of turbulent flow control problems.

Atypical birefringence pattern and the diagnostic ability of scanning laser polarimetry with enhanced corneal compensation in glaucoma.

PubMed

Rao, Harsha L; Yadav, Ravi K; Begum, Viquar U; Addepalli, Uday K; Senthil, Sirisha; Choudhari, Nikhil S; Garudadri, Chandra S

2015-03-01

To evaluate the effect of typical scan score (TSS), when within the acceptable limits, on the diagnostic performance of retinal nerve fibre layer (RNFL) parameters with the enhanced corneal compensation (ECC) protocol of scanning laser polarimetry (SLP) in glaucoma. In a cross-sectional study, 203 eyes of 160 glaucoma patients and 140 eyes of 104 control subjects underwent RNFL imaging with the ECC protocol of SLP. TSS was used to quantify atypical birefringence pattern (ABP) images. Influence of TSS on the diagnostic ability of SLP parameters was evaluated by receiver operating characteristic (ROC) regression models after adjusting for the effect of disease severity [based on mean deviation (MD)] on standard automated perimetry). Diagnostic abilities of all RNFL parameters of SLP increased when the TSS values were higher. This effect was statistically significant for TSNIT (coefficient: 0.08, p<0.001) and inferior average parameters (coefficient: 0.06, p=0.002) but not for nerve fibre indicator (NFI, coefficient: 0.03, p=0.21). In early glaucoma (MD of -5 dB), predicted area under ROC curve (AUC) for TSNIT average parameter improved from 0.642 at a TSS of 90 to 0.845 at a TSS of 100. In advanced glaucoma (MD of -15 dB), AUC for TSNIT average improved from 0.832 at a TSS of 90 to 0.947 at 100. Diagnostic performances of TSNIT and inferior average RNFL parameters with ECC protocol of SLP were significantly influenced by TSS even when the TSS values were within the acceptable limits. Diagnostic ability of NFI was unaffected by TSS values. © 2014 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Use of novel pollen species by specialist and generalist solitary bees (Hymenoptera: Megachilidae).

PubMed

Williams, Neal M

2003-01-01

If trade-offs between flexibility to use a range of host species and efficiency on a limited set underlie the evolution of diet breadth, one resulting prediction is that specialists ought to be more restricted than generalists in their ability to use novel resource species. I used foraging tests and feeding trials to compare the ability of a generalist and a specialist solitary mason bee species to collect and develop on two pollen species that are not normally used in natural populations (novel pollens). Osmia lignaria (Hymenoptera: Megachilidae) is a generalist pollen feeder; O. californica, is more specialized. Adults of the specialist were more limited in use of novel hosts, but only in some contexts. Both bee species refused to collect one novel pollen. The specialist accepted a second novel pollen only when it was presented along with its normal pollen, whereas the generalist collected novel pollen whether presented alone or with normal pollen. Surprisingly, larvae of the specialist were more flexible than were generalists. The specialist grew well on mixtures of normal and novel pollen species, in some cases better than on its normal host alone. Larvae of the generalist grew more poorly on all diets containing novel pollens than on their normal host. Data on these two species of bees suggest that specialization by itself need not reduce flexibility on novel hosts. The findings also provide information about mechanisms of specialization in bees. Similar to some folivores, specific cues of the pollen host and the bee's interpretation of these contribute, along with foraging economics, to pollen choice by adults. The ability of the larvae to cope with specific components of one pollen species need not interfere with its ability to use others.

Canine Hip Dysplasia: Diagnostic Imaging.

PubMed

Butler, J Ryan; Gambino, Jennifer

2017-07-01

Diagnostic imaging is the principal method used to screen for and diagnose hip dysplasia in the canine patient. Multiple techniques are available, each having advantages, disadvantages, and limitations. Hip-extended radiography is the most used method and is best used as a screening tool and for assessment for osteoarthritis. Distraction radiographic methods such as the PennHip method allow for improved detection of laxity and improved ability to predict future osteoarthritis development. More advanced techniques such as MRI, although expensive and not widely available, may improve patient screening and allow for improved assessment of cartilage health. Copyright © 2017 Elsevier Inc. All rights reserved.

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…

Concurrent validity of the differential ability scales, second edition with the Mullen Scales of Early Learning in young children with and without neurodevelopmental disorders.

PubMed

Farmer, Cristan; Golden, Christine; Thurm, Audrey

2016-01-01

Estimates of intelligence in young children with neurodevelopmental disorders are critical for making diagnoses, in characterizing symptoms of disorders, and in predicting future outcomes. The limitations of standardized testing for children with developmental delay or cognitive impairment are well known: Tests do not exist that provide developmentally appropriate material along with norms that extend to the lower reaches of ability. Two commonly used and interchanged instruments are the Mullen Scales of Early Learning (MSEL), a test of developmental level, and the Differential Ability Scales, second edition (DAS-II), a more traditional cognitive test. We evaluated the correspondence of contemporaneous MSEL and the DAS-II scores in a mixed sample of children aged 2-10 years with autism spectrum disorder (ASD), non-ASD developmental delays, and typically developing children across the full spectrum of cognitive ability. Consistent with published data on the original DAS and the MSEL, scores on the DAS-II and MSEL were highly correlated. However, curve estimation revealed large mean differences that varied as a function of the child's cognitive ability level. We conclude that interchanging MSEL and DAS-II scores without regard to the discrepancy in scores may produce misleading results in both cross-sectional and longitudinal studies of children with and without ASD, and, thus, this practice should be implemented with caution.

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…

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

PubMed

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

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.

Should Schools Expect Poor Physical and Mental Health, Social Adjustment, and Participation Outcomes in Students with Disability?

PubMed Central

Vaz, Sharmila; Cordier, Reinie; Falkmer, Marita; Ciccarelli, Marina; Parsons, Richard; McAuliffe, Tomomi; Falkmer, Torbjorn

2015-01-01

The literature on whether students with disabilities have worse physical and mental health, social adjustment, and participation outcomes when compared to their peers without disabilities is largely inconclusive. While the majority of case control studies showed significantly worse outcomes for students with disabilities; the proportion of variance accounted for is rarely reported. The current study used a population cross-sectional approach to determine the classification ability of commonly used screening and outcome measures in determining the disability status. Furthermore, the study aimed to identify the variables, if any, that best predicted the presence of disability. Results of univariate discriminant function analyses suggest that across the board, the sensitivity of the outcome/screening tools to correctly identify students with a disability was 31.9% higher than the related Positive Predictive Value (PPV). The lower PPV and Positive Likelihood Ratio (LR+) scores suggest that the included measures had limited discriminant ability (17.6% to 40.3%) in accurately identifying students at-risk for further assessment. Results of multivariate analyses suggested that poor health and hyperactivity increased the odds of having a disability about two to three times, while poor close perceived friendship and academic competences predicted disability with roughly the same magnitude. Overall, the findings of the current study highlight the need for researchers and clinicians to familiarize themselves with the psychometric properties of measures, and be cautious in matching the function of the measures with their research and clinical needs. PMID:25965845

Should schools expect poor physical and mental health, social adjustment, and participation outcomes in students with disability?

PubMed

Vaz, Sharmila; Cordier, Reinie; Falkmer, Marita; Ciccarelli, Marina; Parsons, Richard; McAuliffe, Tomomi; Falkmer, Torbjorn

2015-01-01

The literature on whether students with disabilities have worse physical and mental health, social adjustment, and participation outcomes when compared to their peers without disabilities is largely inconclusive. While the majority of case control studies showed significantly worse outcomes for students with disabilities; the proportion of variance accounted for is rarely reported. The current study used a population cross-sectional approach to determine the classification ability of commonly used screening and outcome measures in determining the disability status. Furthermore, the study aimed to identify the variables, if any, that best predicted the presence of disability. Results of univariate discriminant function analyses suggest that across the board, the sensitivity of the outcome/screening tools to correctly identify students with a disability was 31.9% higher than the related Positive Predictive Value (PPV). The lower PPV and Positive Likelihood Ratio (LR+) scores suggest that the included measures had limited discriminant ability (17.6% to 40.3%) in accurately identifying students at-risk for further assessment. Results of multivariate analyses suggested that poor health and hyperactivity increased the odds of having a disability about two to three times, while poor close perceived friendship and academic competences predicted disability with roughly the same magnitude. Overall, the findings of the current study highlight the need for researchers and clinicians to familiarize themselves with the psychometric properties of measures, and be cautious in matching the function of the measures with their research and clinical needs.

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

Allison, Steven D.

The role of specific micro-organisms in the carbon cycle, and their responses to environmental change, are unknown in most ecosystems. This knowledge gap limits scientists’ ability to predict how important ecosystem processes, like soil carbon storage and loss, will change with climate and other environmental factors. The investigators addressed this knowledge gap by transplanting microbial communities from different environments into new environments and measuring the response of community composition and carbon cycling over time. Using state-of-the-art sequencing techniques, computational tools, and nanotechnology, the investigators showed that microbial communities on decomposing plant material shift dramatically with natural and experimentally-imposed drought. Microbialmore » communities also shifted in response to added nitrogen, but the effects were smaller. These changes had implications for carbon cycling, with lower rates of carbon loss under drought conditions, and changes in the efficiency of decomposition with nitrogen addition. Even when transplanted into the same conditions, microbial communities from different environments remained distinct in composition and functioning for up to one year. Changes in functioning were related to differences in enzyme gene content across different microbial groups. Computational approaches developed for this project allowed the conclusions to be tested more broadly in other ecosystems, and new computer models will facilitate the prediction of microbial traits and functioning across environments. The data and models resulting from this project benefit the public by improving the ability to predict how microbial communities and carbon cycling functions respond to climate change, nutrient enrichment, and other large-scale environmental changes.« less

Self-awareness of impairment and the decision to drive after an extended period of wakefulness.

PubMed

Jones, Christopher B; Dorrian, Jillian; Jay, Sarah M; Lamond, Nicole; Ferguson, Sally; Dawson, Drew

2006-01-01

Fatigue is an increasingly noted factor in road accidents. The ability to predict and be aware of impairment in terms of driving capability is important for potential legal liability and road safety. However, to date, there have been few studies that have investigated the accuracy of individuals in predicting how safely they could drive during conditions of sleep loss. Research has demonstrated that individuals rate themselves as better than the population average in a number of domains, including driving-related skills. Therefore, this study also aimed to investigate self-ratings of predicted driving ability during extended wakefulness and compare them to ratings made of a hypothetical other person under the same conditions. Thirty-two participants remained awake for a period of 40 h. Every 2 h, they completed the Psychomotor Vigilance Task (PVT) and rated on a seven-point scale how well they thought they could drive safely, react quickly in an emergency, and stay in their own lane. They were also asked to assess how they thought someone else in their own position could drive. The participants rated their driving ability as becoming significantly poorer at the same time that their PVT performance became significantly slower. Self-ratings indicating a qualitative assessment of poorer than neutral driving occurred at 03:00 h for both the "drive safely" and "react quickly" questions, after 19 h of continuous wakefulness (starting at 08:00 h). This occurred at 05:00 h for the "keep in my lane" question. Previous studies with a similar protocol demonstrated that under these conditions, individuals exhibit a performance decrements equivalent to someone with a blood alcohol concentration of 0.05% (the legal driving limit in Australia). Participants consistently rated the ability of others to drive as poorer than their own. The main implication from this study for road safety and legal liability is that it is reasonable to focus on a person's perception of the situation, as it does align with objective reality to a certain extent. A concern in terms of road safety is potential overconfidence, indicated by rating others consistently poorer than themselves.

A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

PubMed

Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

2007-07-20

Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

Spatial variation in water loss predicts terrestrial salamander distribution and population dynamics.

PubMed

Peterman, W E; Semlitsch, R D

2014-10-01

Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders.

Mathematical model to predict drivers' reaction speeds.

PubMed

Long, Benjamin L; Gillespie, A Isabella; Tanaka, Martin L

2012-02-01

Mental distractions and physical impairments can increase the risk of accidents by affecting a driver's ability to control the vehicle. In this article, we developed a linear mathematical model that can be used to quantitatively predict drivers' performance over a variety of possible driving conditions. Predictions were not limited only to conditions tested, but also included linear combinations of these tests conditions. Two groups of 12 participants were evaluated using a custom drivers' reaction speed testing device to evaluate the effect of cell phone talking, texting, and a fixed knee brace on the components of drivers' reaction speed. Cognitive reaction time was found to increase by 24% for cell phone talking and 74% for texting. The fixed knee brace increased musculoskeletal reaction time by 24%. These experimental data were used to develop a mathematical model to predict reaction speed for an untested condition, talking on a cell phone with a fixed knee brace. The model was verified by comparing the predicted reaction speed to measured experimental values from an independent test. The model predicted full braking time within 3% of the measured value. Although only a few influential conditions were evaluated, we present a general approach that can be expanded to include other types of distractions, impairments, and environmental conditions.

Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

PubMed Central

Pena Cabra, Oscar David; Watanabe, Takashi

2013-01-01

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary. PMID:24187580

Effects and detection of raw material variability on the performance of near-infrared calibration models for pharmaceutical products.

PubMed

Igne, Benoit; Shi, Zhenqi; Drennen, James K; Anderson, Carl A

2014-02-01

The impact of raw material variability on the prediction ability of a near-infrared calibration model was studied. Calibrations, developed from a quaternary mixture design comprising theophylline anhydrous, lactose monohydrate, microcrystalline cellulose, and soluble starch, were challenged by intentional variation of raw material properties. A design with two theophylline physical forms, three lactose particle sizes, and two starch manufacturers was created to test model robustness. Further challenges to the models were accomplished through environmental conditions. Along with full-spectrum partial least squares (PLS) modeling, variable selection by dynamic backward PLS and genetic algorithms was utilized in an effort to mitigate the effects of raw material variability. In addition to evaluating models based on their prediction statistics, prediction residuals were analyzed by analyses of variance and model diagnostics (Hotelling's T(2) and Q residuals). Full-spectrum models were significantly affected by lactose particle size. Models developed by selecting variables gave lower prediction errors and proved to be a good approach to limit the effect of changing raw material characteristics. Hotelling's T(2) and Q residuals provided valuable information that was not detectable when studying only prediction trends. Diagnostic statistics were demonstrated to be critical in the appropriate interpretation of the prediction of quality parameters. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Control and prediction components of movement planning in stuttering vs. nonstuttering adults

PubMed Central

Daliri, Ayoub; Prokopenko, Roman A.; Flanagan, J. Randall; Max, Ludo

2014-01-01

Purpose Stuttering individuals show speech and nonspeech sensorimotor deficiencies. To perform accurate movements, the sensorimotor system needs to generate appropriate control signals and correctly predict their sensory consequences. Using a reaching task, we examined the integrity of these control and prediction components, separately, for movements unrelated to the speech motor system. Method Nine stuttering and nine nonstuttering adults made fast reaching movements to visual targets while sliding an object under the index finger. To quantify control, we determined initial direction error and end-point error. To quantify prediction, we calculated the correlation between vertical and horizontal forces applied to the object—an index of how well vertical force (preventing slip) anticipated direction-dependent variations in horizontal force (moving the object). Results Directional and end-point error were significantly larger for the stuttering group. Both groups performed similarly in scaling vertical force with horizontal force. Conclusions The stuttering group's reduced reaching accuracy suggests limitations in generating control signals for voluntary movements, even for non-orofacial effectors. Typical scaling of vertical force with horizontal force suggests an intact ability to predict the consequences of planned control signals. Stuttering may be associated with generalized deficiencies in planning control signals rather than predicting the consequences of those signals. PMID:25203459

Effect of strength and speed of torque development on balance recovery with the ankle strategy.

PubMed

Robinovitch, Stephen N; Heller, Britta; Lui, Andrew; Cortez, Jeffrey

2002-08-01

In the event of an unexpected disturbance to balance, the ability to recover a stable upright stance should depend not only on the magnitude of torque that can be generated by contraction of muscles spanning the lower extremity joints but also on how quickly these torques can be developed. In the present study, we used a combination of experimental and mathematical models of balance recovery by sway (feet in place responses) to test this hypothesis. Twenty-three young subjects participated in experiments in which they were supported in an inclined standing position by a horizontal tether and instructed to recover balance by contracting only their ankle muscles. The maximum lean angle where they could recover balance without release of the tether (static recovery limit) averaged 14.9 +/- 1.4 degrees (mean +/- SD). The maximum initial lean angle where they could recover balance after the tether was unexpectedly released and the ankles were initially relaxed (dynamic recovery limit) averaged 5.9 +/- 1.1 degrees, or 60 +/- 11% smaller than the static recovery limit. Peak ankle torque did not differ significantly between the two conditions (and averaged 116 +/- 32 Nm), indicating the strong effect on recovery ability of latencies in the onset and subsequent rates of torque generation (which averaged 99 +/- 13 ms and 372 +/- 267 N. m/s, respectively). Additional experiments indicated that dynamic recovery limits increased 11 +/- 14% with increases in the baseline ankle torques prior to release (from an average value of 31 +/- 18 to 54 +/- 24 N. m). These trends are in agreement with predictions from a computer simulation based on an inverted pendulum model, which illustrate the specific combinations of baseline ankle torque, rate of torque generation, and peak ankle torque that are required to attain target recovery limits.

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.

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.…

Joint proprioception, muscle strength, and functional ability in patients with osteoarthritis of the knee.

PubMed

van der Esch, M; Steultjens, M; Harlaar, J; Knol, D; Lems, W; Dekker, J

2007-06-15

To test the hypotheses that poor knee joint proprioception is related to limitations in functional ability, and poor proprioception aggravates the impact of muscle weakness on limitations in functional ability in osteoarthritis (OA) of the knee. Sixty-three patients with symptomatic OA of the knee were tested. Proprioceptive acuity was assessed by establishing the joint motion detection threshold (JMDT) in the anteroposterior direction. Muscle strength was measured using a computer-driven isokinetic dynamometer. Functional ability was assessed by the 100-meter walking test, the Get Up and Go (GUG) test, and the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlation analyses were performed to assess the relationship between proprioception, muscle strength, and functional ability. Regression analyses were performed to assess the impact of proprioception on the relationship between muscle strength and functional ability. Poor proprioception (high JMDT) was related to more limitation in functional ability (walking time r = 0.30, P < 0.05; GUG time r = 0.30, P < 0.05; WOMAC-PF r = 0.26, P <0.05). In regression analyses, the interaction between proprioception and muscle strength was significantly related to functional ability (walking time, P < 0.001 and GUG time, P < 0.001) but not to WOMAC-PF score (P = 0.625). In patients with poor proprioception, reduction of muscle strength was associated with more severe deterioration of functional ability than in patients with accurate proprioception. Patients with poor proprioception show more limitation in functional ability, but this relationship is rather weak. In patients with poor proprioception, muscle weakness has a stronger impact on limitations in functional ability than in patients with accurate proprioception.

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.

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.

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).

Reciprocal Relationships between Teacher Ratings of Internalizing and Externalizing Behaviors in Adolescents with Different Levels of Cognitive Abilities.

PubMed

Morin, Alexandre J S; Arens, A Katrin; Maïano, Christophe; Ciarrochi, Joseph; Tracey, Danielle; Parker, Philip D; Craven, Rhonda G

2017-04-01

Are internalizing and externalizing behavior problems interrelated via mutually reinforcing relationships (with each behavior leading to increases over time in levels of the other behavior) or mutually suppressing relationships (with each behavior leading to decreases over time in levels of the other behavior)? Past research on the directionality of these relationships has led to ambiguous results, particularly in adolescence. Furthermore, the extent to which prior results will generalize to adolescents with low levels of cognitive abilities remains unknown. This second limit is particularly important, given that these adolescents are known to present higher levels of externalizing and internalizing behaviors than their peers with average-to-high levels of cognitive abilities, and that the mechanisms involved in the reciprocal relationships between these two types of behaviors may differ across both populations. This study examines the directionality of the longitudinal relationships between externalizing and internalizing behavior problems as rated by teachers across three measurement waves (corresponding to Grades 8-10) in matched samples of 138 adolescents (34.78 % girls) with low levels of cognitive abilities and 556 adolescents (44.88 % girls) with average-to-high levels of cognitive abilities. The results showed that the measurement structure was fully equivalent across time periods and groups of adolescents, revealing high levels of developmental stability in both types of problems, and moderately high levels of cross-sectional associations. Levels of both internalizing and externalizing behaviors were higher among adolescents with low levels of cognitive abilities relative to those with average-to-high levels of cognitive abilities. Finally, the predictive analyses revealed negative reciprocal longitudinal relationships (i.e., mutually suppressing relationships) between externalizing and internalizing problems, a result that was replicated within samples of adolescents with low, and average-to-high levels of cognitive ability.