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Sample records for predict individual efficiency

  1. Specialization does not predict individual efficiency in an ant.

    PubMed

    Dornhaus, Anna

    2008-11-18

    The ecological success of social insects is often attributed to an increase in efficiency achieved through division of labor between workers in a colony. Much research has therefore focused on the mechanism by which a division of labor is implemented, i.e., on how tasks are allocated to workers. However, the important assumption that specialists are indeed more efficient at their work than generalist individuals--the "Jack-of-all-trades is master of none" hypothesis--has rarely been tested. Here, I quantify worker efficiency, measured as work completed per time, in four different tasks in the ant Temnothorax albipennis: honey and protein foraging, collection of nest-building material, and brood transports in a colony emigration. I show that individual efficiency is not predicted by how specialized workers were on the respective task. Worker efficiency is also not consistently predicted by that worker's overall activity or delay to begin the task. Even when only the worker's rank relative to nestmates in the same colony was used, specialization did not predict efficiency in three out of the four tasks, and more specialized workers actually performed worse than others in the fourth task (collection of sand grains). I also show that the above relationships, as well as median individual efficiency, do not change with colony size. My results demonstrate that in an ant species without morphologically differentiated worker castes, workers may nevertheless differ in their ability to perform different tasks. Surprisingly, this variation is not utilized by the colony--worker allocation to tasks is unrelated to their ability to perform them. What, then, are the adaptive benefits of behavioral specialization, and why do workers choose tasks without regard for whether they can perform them well? We are still far from an understanding of the adaptive benefits of division of labor in social insects.

  2. Predicting Recovery Potential for Individual Stroke Patients Increases Rehabilitation Efficiency.

    PubMed

    Stinear, Cathy M; Byblow, Winston D; Ackerley, Suzanne J; Barber, P Alan; Smith, Marie-Claire

    2017-04-01

    Several clinical measures and biomarkers are associated with motor recovery after stroke, but none are used to guide rehabilitation for individual patients. The objective of this study was to evaluate the implementation of upper limb predictions in stroke rehabilitation, by combining clinical measures and biomarkers using the Predict Recovery Potential (PREP) algorithm. Predictions were provided for patients in the implementation group (n=110) and withheld from the comparison group (n=82). Predictions guided rehabilitation therapy focus for patients in the implementation group. The effects of predictive information on clinical practice (length of stay, therapist confidence, therapy content, and dose) were evaluated. Clinical outcomes (upper limb function, impairment and use, independence, and quality of life) were measured 3 and 6 months poststroke. The primary clinical practice outcome was inpatient length of stay. The primary clinical outcome was Action Research Arm Test score 3 months poststroke. Length of stay was 1 week shorter for the implementation group (11 days; 95% confidence interval, 9-13 days) than the comparison group (17 days; 95% confidence interval, 14-21 days; P=0.001), controlling for upper limb impairment, age, sex, and comorbidities. Therapists were more confident (P=0.004) and modified therapy content according to predictions for the implementation group (P<0.05). The algorithm correctly predicted the primary clinical outcome for 80% of patients in both groups. There were no adverse effects of algorithm implementation on patient outcomes at 3 or 6 months poststroke. PREP algorithm predictions modify therapy content and increase rehabilitation efficiency after stroke without compromising clinical outcome. URL: http://anzctr.org.au. Unique identifier: ACTRN12611000755932. © 2017 American Heart Association, Inc.

  3. Predictive information speeds up visual awareness in an individuation task by modulating threshold setting, not processing efficiency.

    PubMed

    De Loof, Esther; Van Opstal, Filip; Verguts, Tom

    2016-04-01

    Theories on visual awareness claim that predicted stimuli reach awareness faster than unpredicted ones. In the current study, we disentangle whether prior information about the upcoming stimulus affects visual awareness of stimulus location (i.e., individuation) by modulating processing efficiency or threshold setting. Analogous research on stimulus identification revealed that prior information modulates threshold setting. However, as identification and individuation are two functionally and neurally distinct processes, the mechanisms underlying identification cannot simply be extrapolated directly to individuation. The goal of this study was therefore to investigate how individuation is influenced by prior information about the upcoming stimulus. To do so, a drift diffusion model was fitted to estimate the processing efficiency and threshold setting for predicted versus unpredicted stimuli in a cued individuation paradigm. Participants were asked to locate a picture, following a cue that was congruent, incongruent or neutral with respect to the picture's identity. Pictures were individuated faster in the congruent and neutral condition compared to the incongruent condition. In the diffusion model analysis, the processing efficiency was not significantly different across conditions. However, the threshold setting was significantly higher following an incongruent cue compared to both congruent and neutral cues. Our results indicate that predictive information about the upcoming stimulus influences visual awareness by shifting the threshold for individuation rather than by enhancing processing efficiency.

  4. Predicting Individual Fuel Economy

    SciTech Connect

    Lin, Zhenhong; Greene, David L

    2011-01-01

    To make informed decisions about travel and vehicle purchase, consumers need unbiased and accurate information of the fuel economy they will actually obtain. In the past, the EPA fuel economy estimates based on its 1984 rules have been widely criticized for overestimating on-road fuel economy. In 2008, EPA adopted a new estimation rule. This study compares the usefulness of the EPA's 1984 and 2008 estimates based on their prediction bias and accuracy and attempts to improve the prediction of on-road fuel economies based on consumer and vehicle attributes. We examine the usefulness of the EPA fuel economy estimates using a large sample of self-reported on-road fuel economy data and develop an Individualized Model for more accurately predicting an individual driver's on-road fuel economy based on easily determined vehicle and driver attributes. Accuracy rather than bias appears to have limited the usefulness of the EPA 1984 estimates in predicting on-road MPG. The EPA 2008 estimates appear to be equally inaccurate and substantially more biased relative to the self-reported data. Furthermore, the 2008 estimates exhibit an underestimation bias that increases with increasing fuel economy, suggesting that the new numbers will tend to underestimate the real-world benefits of fuel economy and emissions standards. By including several simple driver and vehicle attributes, the Individualized Model reduces the unexplained variance by over 55% and the standard error by 33% based on an independent test sample. The additional explanatory variables can be easily provided by the individuals.

  5. Neuroanatomy Predicts Individual Risk Attitudes

    PubMed Central

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W.; Glimcher, Paul W.

    2014-01-01

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  6. Developmental dyslexia: predicting individual risk.

    PubMed

    Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

    2015-09-01

    Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by

  7. Developmental dyslexia: predicting individual risk

    PubMed Central

    Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

    2015-01-01

    Background Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as ‘dyslexic’ or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Results Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Conclusions Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. PMID:25832320

  8. Individual alerting efficiency modulates time perception

    PubMed Central

    Liu, Peiduo; Yang, Wenjing; Yuan, Xiangyong; Bi, Cuihua; Chen, Antao; Huang, Xiting

    2015-01-01

    Time perception plays a fundamental role in human perceptual and motor activities, and can be influenced by various factors, such as selective attention and arousal. However, little is known about the influence of individual alerting efficiency on perceived duration. In this study, we explored this question by running two experiments. The Attentional Networks Test was used to evaluate individual differences in alerting efficiency in each experiment. Temporal bisection (Experiment 1) and time generalization task (Experiment 2) were used to explore the participants’ perception of duration. The results indicated that subjects in the high alerting efficiency group overestimated interval durations and estimated durations more accurately compared with subjects in the low alerting efficiency group. The two experiments showed that the sensitivity of time was not influenced by individual alerting efficiency. Based on previous studies and current findings, we infer that individual differences in alerting efficiency may influence time perception through modulating the latency of the attention-controlled switch and the speed of the peacemaker within the framework of the internal clock model. PMID:25904881

  9. Categories Influence Predictions about Individual Consistency

    ERIC Educational Resources Information Center

    Rhodes, Marjorie; Gelman, Susan A.

    2008-01-01

    Predicting how people will behave in the future is a critical social-cognitive task. In four studies (N = 150, ages preschool to adult), young children (ages 4-5) used category information to guide their expectations about individual consistency. They predicted that psychological properties (preferences and fears) would remain consistent over time…

  10. Structural network efficiency predicts conversion to dementia

    PubMed Central

    Tuladhar, Anil M.; van Uden, Ingeborg W.M.; Rutten-Jacobs, Loes C.A.; Lawrence, Andrew; van der Holst, Helena; van Norden, Anouk; de Laat, Karlijn; van Dijk, Ewoud; Claassen, Jurgen A.H.R.; Kessels, Roy P.C.; Markus, Hugh S.; Norris, David G.

    2016-01-01

    Objective: To examine whether structural network connectivity at baseline predicts incident all-cause dementia in a prospective hospital-based cohort of elderly participants with MRI evidence of small vessel disease (SVD). Methods: A total of 436 participants from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC), a prospective hospital-based cohort of elderly without dementia with cerebral SVD, were included in 2006. During follow-up (2011–2012), dementia was diagnosed. The structural network was constructed from baseline diffusion tensor imaging followed by deterministic tractography and measures of efficiency using graph theory were calculated. Cox proportional regression analyses were conducted. Results: During 5 years of follow-up, 32 patients developed dementia. MRI markers for SVD were strongly associated with network measures. Patients with dementia showed lower total network strength and global and local efficiency at baseline as compared with the group without dementia. Lower global network efficiency was independently associated with increased risk of incident all-cause dementia (hazard ratio 0.63, 95% confidence interval 0.42–0.96, p = 0.032); in contrast, individual SVD markers including lacunes, white matter hyperintensities volume, and atrophy were not independently associated. Conclusions: These results support a role of network disruption playing a pivotal role in the genesis of dementia in SVD, and suggest network analysis of the connectivity of white matter has potential as a predictive marker in the disease. PMID:26888983

  11. Energy efficiency: Perspectives on individual behavior

    SciTech Connect

    Kempton, W.; Neiman, M.

    1986-01-01

    A collection of research papers on the personal behavior and attitudes that affect residential energy use. Articles in the first section address the factors that affect decision-making by consumers; convenience and personal opinions often override rational economic choices. The research in the second section uses aggregate survey data to gain insight into energy behavior. Papers in the third section use detailed monitoring of individual households to analyze personal behavior and home energy management, and the fourth section includes papers on the interaction of building systems with occupants. These papers demonstrate that, to be successful, energy conservation programs must consider the ''human factor'' in addition to the conventional energy parameters (e.g. weather, insulation, and appliance efficiencies). Main emphasis was given to: energy conservation; consumers; personal behavior; economic decision-making; buildings; energy policy; hot water use; thermostats; attitudes; applied anthropology.

  12. Predicting individual fusional range from optometric data

    NASA Astrophysics Data System (ADS)

    Endrikhovski, Serguei; Jin, Elaine; Miller, Michael E.; Ford, Robert W.

    2005-03-01

    A model was developed to predict the range of disparities that can be fused by an individual user from optometric measurements. This model uses parameters, such as dissociated phoria and fusional reserves, to calculate an individual user"s fusional range (i.e., the disparities that can be fused on stereoscopic displays) when the user views a stereoscopic stimulus from various distances. This model is validated by comparing its output with data from a study in which the individual fusional range of a group of users was quantified while they viewed a stereoscopic display from distances of 0.5, 1.0, and 2.0 meters. Overall, the model provides good data predictions for the majority of the subjects and can be generalized for other viewing conditions. The model may, therefore, be used within a customized stereoscopic system, which would render stereoscopic information in a way that accounts for the individual differences in fusional range. Because the comfort of an individual user also depends on the user"s ability to fuse stereo images, such a system may, consequently, improve the comfort level and viewing experience for people with different stereoscopic fusional capabilities.

  13. Estimating Energy Expenditure using Individualized, Power-Specific Gross Efficiencies.

    PubMed

    Homestead, E P; Peterman, J E; Kane, L A; Contini, E J; Byrnes, W C

    2016-12-01

    Our purpose was to determine if using an individual's power-specific gross efficiency improves the accuracy of estimating energy expenditure from cycling power. 30 subjects performed a graded cycling test to develop 4 gross efficiencies: individual power-specific gross efficiencies, a group mean power-specific gross efficiency, individual fixed gross efficiencies, and a group mean fixed gross efficiency. Energy expenditure was estimated from power using these different gross efficiencies and compared to measured energy expenditure during moderate- and hard-intensity constant-power and 2 variable-power cycling bouts. Estimated energy expenditures using individual or group mean power-specific gross efficiencies were not different from measured energy expenditure across all cycling bouts (p>0.05). To examine the intra-individual variability of the estimates, absolute difference scores (absolute value of estimated minus measured energy expenditure) were compared, where values closer to zero represent more accurate individual estimates. The absolute difference score using individual power-specific gross efficiencies was significantly lower compared to the other gross efficiencies across all cycling bouts (p<0.01). Significant and strong correlations (r≥0.97, p<0.001) were found across all cycling bouts between estimated and measured energy expenditures using individual power-specific gross efficiencies. In conclusion, using an individual's power-specific gross efficiency significantly improves their energy expenditure estimate across different power outputs.

  14. Neural Variability Quenching Predicts Individual Perceptual Abilities.

    PubMed

    Arazi, Ayelet; Censor, Nitzan; Dinstein, Ilan

    2017-01-04

    Neural activity during repeated presentations of a sensory stimulus exhibits considerable trial-by-trial variability. Previous studies have reported that trial-by-trial neural variability is reduced (quenched) by the presentation of a stimulus. However, the functional significance and behavioral relevance of variability quenching and the potential physiological mechanisms that may drive it have been studied only rarely. Here, we recorded neural activity with EEG as subjects performed a two-interval forced-choice contrast discrimination task. Trial-by-trial neural variability was quenched by ∼40% after the presentation of the stimulus relative to the variability apparent before stimulus presentation, yet there were large differences in the magnitude of variability quenching across subjects. Individual magnitudes of quenching predicted individual discrimination capabilities such that subjects who exhibited larger quenching had smaller contrast discrimination thresholds and steeper psychometric function slopes. Furthermore, the magnitude of variability quenching was strongly correlated with a reduction in broadband EEG power after stimulus presentation. Our results suggest that neural variability quenching is achieved by reducing the amplitude of broadband neural oscillations after sensory input, which yields relatively more reproducible cortical activity across trials and enables superior perceptual abilities in individuals who quench more.

  15. Effect of Individual Component Life Distribution on Engine Life Prediction

    NASA Technical Reports Server (NTRS)

    Zaretsky, Erwin V.; Hendricks, Robert C.; Soditus, Sherry M.

    2003-01-01

    The effect of individual engine component life distributions on engine life prediction was determined. A Weibull-based life and reliability analysis of the NASA Energy Efficient Engine was conducted. The engine s life at a 95 and 99.9 percent probability of survival was determined based upon the engine manufacturer s original life calculations and assumed values of each of the component s cumulative life distributions as represented by a Weibull slope. The lives of the high-pressure turbine (HPT) disks and blades were also evaluated individually and as a system in a similar manner. Knowing the statistical cumulative distribution of each engine component with reasonable engineering certainty is a condition precedent to predicting the life and reliability of an entire engine. The life of a system at a given reliability will be less than the lowest-lived component in the system at the same reliability (probability of survival). Where Weibull slopes of all the engine components are equal, the Weibull slope had a minimal effect on engine L(sub 0.1) life prediction. However, at a probability of survival of 95 percent (L(sub 5) life), life decreased with increasing Weibull slope.

  16. Intrinsic functional connectivity predicts individual differences in distractibility.

    PubMed

    Poole, Victoria N; Robinson, Meghan E; Singleton, Omar; DeGutis, Joseph; Milberg, William P; McGlinchey, Regina E; Salat, David H; Esterman, Michael

    2016-06-01

    Distractor suppression, the ability to filter and ignore task-irrelevant information, is critical for efficient task performance. While successful distractor suppression relies on a balance of activity in neural networks responsible for attention maintenance (dorsal attention network; DAN), reorientation (ventral attention network; VAN), and internal thought (default mode network, DMN), the degree to which intrinsic connectivity within and between these networks contributes to individual differences in distractor suppression ability is not well-characterized. For the purposes of understanding these interactions, the current study collected resting-state fMRI data from 32 Veterans and, several months later (7±5 months apart), performance on the additional singleton paradigm, a measure of distractor suppression. Using multivariate support vector regression models composed of resting state connectivity between regions of the DAN, VAN, and DMN, and a leave-one-subject-out cross-validation procedure, we were able to predict an individual's task performance, yielding a significant correlation between the actual and predicted distractor suppression (r=0.48, p=0.0053). Network-level analyses revealed that greater within-network DMN connectivity was predictive of better distractor suppression, while greater connectivity between the DMN and attention networks was predictive of poorer distractor suppression. The strongest connection hubs were determined to be the right frontal eye field and temporoparietal junction of the DAN and VAN, respectively, and medial (ventromedial prefrontal and posterior cingulate cortices) and bilateral prefrontal regions of the DMN. These results are amongst a small but growing number of studies demonstrating that resting state connectivity is related to stable individual differences in cognitive ability, and suggest that greater integrity and independence of the DMN is related to better attentional ability.

  17. A pharmacogenomic method for individualized prediction of drug sensitivity

    PubMed Central

    Cohen, Adam L; Soldi, Raffaella; Zhang, Haiyu; Gustafson, Adam M; Wilcox, Ryan; Welm, Bryan E; Chang, Jeffrey T; Johnson, Evan; Spira, Avrum; Jeffrey, Stefanie S; Bild, Andrea H

    2011-01-01

    Identifying the best drug for each cancer patient requires an efficient individualized strategy. We present MATCH (Merging genomic and pharmacologic Analyses for Therapy CHoice), an approach using public genomic resources and drug testing of fresh tumor samples to link drugs to patients. Valproic acid (VPA) is highlighted as a proof-of-principle. In order to predict specific tumor types with high probability of drug sensitivity, we create drug response signatures using publically available gene expression data and assess sensitivity in a data set of >40 cancer types. Next, we evaluate drug sensitivity in matched tumor and normal tissue and exclude cancer types that are no more sensitive than normal tissue. From these analyses, breast tumors are predicted to be sensitive to VPA. A meta-analysis across breast cancer data sets shows that aggressive subtypes are most likely to be sensitive to VPA, but all subtypes have sensitive tumors. MATCH predictions correlate significantly with growth inhibition in cancer cell lines and three-dimensional cultures of fresh tumor samples. MATCH accurately predicts reduction in tumor growth rate following VPA treatment in patient tumor xenografts. MATCH uses genomic analysis with in vitro testing of patient tumors to select optimal drug regimens before clinical trial initiation. PMID:21772261

  18. Computationally Efficient Prediction of Ionic Liquid Properties.

    PubMed

    Chaban, Vitaly V; Prezhdo, Oleg V

    2014-06-05

    Due to fundamental differences, room-temperature ionic liquids (RTIL) are significantly more viscous than conventional molecular liquids and require long simulation times. At the same time, RTILs remain in the liquid state over a much broader temperature range than the ordinary liquids. We exploit the ability of RTILs to stay liquid at several hundred degrees Celsius and introduce a straightforward and computationally efficient method for predicting RTIL properties at ambient temperature. RTILs do not alter phase behavior at 600-800 K. Therefore, their properties can be smoothly extrapolated down to ambient temperatures. We numerically prove the validity of the proposed concept for density and ionic diffusion of four different RTILs. This simple method enhances the computational efficiency of the existing simulation approaches as applied to RTILs by more than an order of magnitude.

  19. Functional brain network efficiency predicts intelligence.

    PubMed

    Langer, Nicolas; Pedroni, Andreas; Gianotti, Lorena R R; Hänggi, Jürgen; Knoch, Daria; Jäncke, Lutz

    2012-06-01

    The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

  20. Measuring the operational efficiency of individual theme park attractions.

    PubMed

    Kim, Changhee; Kim, Soowook

    2016-01-01

    This study assesses the operation efficiency of theme park attractions using the data envelopment analysis, utilizing actual data on 15 attractions at Samsung Everland located in Yongin-si, Republic of Korea. In particular, this study identifies crowding and waiting time as one of the main causes of visitor's satisfaction, and analyzes the efficiency of individual attractions in terms of waiting time. The installation area, installation cost, and annual repair cost are set as input factors and the number of annual users and customer satisfaction as output factors. The results show that the roller coaster-type attractions were less efficient than other types of attractions while rotating-type attractions were relatively more efficient. However, an importance performance analysis on individual attraction's efficiency and satisfaction showed that operational efficiency should not be the sole consideration in attraction installation. In addition, the projection points for input factors for efficient use of attractions and the appropriate reference set for benchmarking are provided as guideline for attraction efficiency management.

  1. Extraversion predicts individual differences in face recognition.

    PubMed

    Li, Jingguang; Tian, Moqian; Fang, Huizhen; Xu, Miao; Li, He; Liu, Jia

    2010-07-01

    In daily life, one of the most common social tasks we perform is to recognize faces. However, the relation between face recognition ability and social activities is largely unknown. Here we ask whether individuals with better social skills are also better at recognizing faces. We found that extraverts who have better social skills correctly recognized more faces than introverts. However, this advantage was absent when extraverts were asked to recognize non-social stimuli (e.g., flowers). In particular, the underlying facet that makes extraverts better face recognizers is the gregariousness facet that measures the degree of inter-personal interaction. In addition, the link between extraversion and face recognition ability was independent of general cognitive abilities. These findings provide the first evidence that links face recognition ability to our daily activity in social communication, supporting the hypothesis that extraverts are better at decoding social information than introverts.

  2. Efficient temporal and interlayer parameter prediction for weighted prediction in scalable high efficiency video coding

    NASA Astrophysics Data System (ADS)

    Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi

    2017-01-01

    Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.

  3. Efficient computation of volume in flow predictions

    NASA Technical Reports Server (NTRS)

    Vinokur, M.; Kordulla, W.

    1983-01-01

    An efficient method for calculating cell volumes for time-dependent three-dimensional flow predictions by finite volume calculations is presented. Eight arbitrary corner points are considered and the shape face is divided into two planar triangles. The volume is then dependent on the orientation of the partitioning. In the case of a hexahedron, it is noted that any open surface with a boundary that is a closed curve possesses a surface vector independent of the surface shape. Expressions are defined for the surface vector, which is independent of the partitioning surface diagonal used to quantify the volume. Using a decomposition of the cell volume involving two corners, with each the vertex of three diagonals and six corners which are vertices of one diagonal, gives portions which are tetrahedra. The resultant mesh is can be used for time-dependent finite volume calculations one requires less computer time than previous methods.

  4. Group-regularized individual prediction: theory and application to pain.

    PubMed

    Lindquist, Martin A; Krishnan, Anjali; López-Solà, Marina; Jepma, Marieke; Woo, Choong-Wan; Koban, Leonie; Roy, Mathieu; Atlas, Lauren Y; Schmidt, Liane; Chang, Luke J; Reynolds Losin, Elizabeth A; Eisenbarth, Hedwig; Ashar, Yoni K; Delk, Elizabeth; Wager, Tor D

    2017-01-15

    Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. No Longer Confidential: Estimating the Confidence of Individual Regression Predictions

    PubMed Central

    Briesemeister, Sebastian; Rahnenführer, Jörg; Kohlbacher, Oliver

    2012-01-01

    Quantitative predictions in computational life sciences are often based on regression models. The advent of machine learning has led to highly accurate regression models that have gained widespread acceptance. While there are statistical methods available to estimate the global performance of regression models on a test or training dataset, it is often not clear how well this performance transfers to other datasets or how reliable an individual prediction is–a fact that often reduces a user’s trust into a computational method. In analogy to the concept of an experimental error, we sketch how estimators for individual prediction errors can be used to provide confidence intervals for individual predictions. Two novel statistical methods, named CONFINE and CONFIVE, can estimate the reliability of an individual prediction based on the local properties of nearby training data. The methods can be applied equally to linear and non-linear regression methods with very little computational overhead. We compare our confidence estimators with other existing confidence and applicability domain estimators on two biologically relevant problems (MHC–peptide binding prediction and quantitative structure-activity relationship (QSAR)). Our results suggest that the proposed confidence estimators perform comparable to or better than previously proposed estimation methods. Given a sufficient amount of training data, the estimators exhibit error estimates of high quality. In addition, we observed that the quality of estimated confidence intervals is predictable. We discuss how confidence estimation is influenced by noise, the number of features, and the dataset size. Estimating the confidence in individual prediction in terms of error intervals represents an important step from plain, non-informative predictions towards transparent and interpretable predictions that will help to improve the acceptance of computational methods in the biological community. PMID:23166592

  6. Predicting individual brain functional connectivity using a Bayesian hierarchical model.

    PubMed

    Dai, Tian; Guo, Ying

    2017-02-15

    Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual

  7. Relationship between efficiency and predictability in stock price change

    NASA Astrophysics Data System (ADS)

    Eom, Cheoljun; Oh, Gabjin; Jung, Woo-Sung

    2008-09-01

    In this study, we evaluate the relationship between efficiency and predictability in the stock market. The efficiency, which is the issue addressed by the weak-form efficient market hypothesis, is calculated using the Hurst exponent and the approximate entropy (ApEn). The predictability corresponds to the hit-rate; this is the rate of consistency between the direction of the actual price change and that of the predicted price change, as calculated via the nearest neighbor prediction method. We determine that the Hurst exponent and the ApEn value are negatively correlated. However, predictability is positively correlated with the Hurst exponent.

  8. Predicting Motor Sequence Learning in Individuals With Chronic Stroke.

    PubMed

    Wadden, Katie P; Asis, Kristopher De; Mang, Cameron S; Neva, Jason L; Peters, Sue; Lakhani, Bimal; Boyd, Lara A

    2017-01-01

    Conventionally, change in motor performance is quantified with discrete measures of behavior taken pre- and postpractice. As a high degree of movement variability exists in motor performance after stroke, pre- and posttesting of motor skill may lack sensitivity to predict potential for motor recovery. Evaluate the use of predictive models of motor learning based on individual performance curves and clinical characteristics of motor function in individuals with stroke. Ten healthy and fourteen individuals with chronic stroke performed a continuous joystick-based tracking task over 6 days, and at a 24-hour delayed retention test, to assess implicit motor sequence learning. Individuals with chronic stroke demonstrated significantly slower rates of improvements in implicit sequence-specific motor performance compared with a healthy control (HC) group when root mean squared error performance data were fit to an exponential function. The HC group showed a positive relationship between a faster rate of change in implicit sequence-specific motor performance during practice and superior performance at the delayed retention test. The same relationship was shown for individuals with stroke only after accounting for overall motor function by including Wolf Motor Function Test rate in our model. Nonlinear information extracted from multiple time points across practice, specifically the rate of motor skill acquisition during practice, relates strongly with changes in motor behavior at the retention test following practice and could be used to predict optimal doses of practice on an individual basis. © The Author(s) 2016.

  9. Individual Factors Predicting Mental Health Court Diversion Outcome

    ERIC Educational Resources Information Center

    Verhaaff, Ashley; Scott, Hannah

    2015-01-01

    Objective: This study examined which individual factors predict mental health court diversion outcome among a sample of persons with mental illness participating in a postcharge diversion program. Method: The study employed secondary analysis of existing program records for 419 persons with mental illness in a court diversion program. Results:…

  10. Individual Factors Predicting Mental Health Court Diversion Outcome

    ERIC Educational Resources Information Center

    Verhaaff, Ashley; Scott, Hannah

    2015-01-01

    Objective: This study examined which individual factors predict mental health court diversion outcome among a sample of persons with mental illness participating in a postcharge diversion program. Method: The study employed secondary analysis of existing program records for 419 persons with mental illness in a court diversion program. Results:…

  11. Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax

    ERIC Educational Resources Information Center

    Kidd, Evan; Arciuli, Joanne

    2016-01-01

    Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68)…

  12. Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax

    ERIC Educational Resources Information Center

    Kidd, Evan; Arciuli, Joanne

    2016-01-01

    Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68)…

  13. Prediction of Intrinsically Caused Tripping Events in Individuals With Stroke.

    PubMed

    Zhang, Fan; Bohlen, Peter; Lewek, Michael D; Huang, He

    2017-08-01

    This study investigated the feasibility of predicting intrinsically caused trips (ICTs) in individuals with stroke. Gait kinematics collected from 12 individuals with chronic stroke, who demonstrated ICTs in treadmill walking, were analyzed. A prediction algorithm based on the outlier principle was employed. Sequential forward selection (SFS) and minimum-redundancy-maximum-relevance (mRMR) were used separately to identify the precursors for accurate ICT prediction. The results showed that it was feasible to predict ICTs around 50-260 ms before ICTs occurred in the swing phase by monitoring lower limb kinematics during the preceding stance phase. Both SFS and mRMR were effective in identifying the precursors of ICTs. For 9 out of the 12 subjects, the paretic lower limb's shank orientation in the sagittal plane and the vertical velocity of the paretic foot's center of gravity were important in predicting ICTs accurately; the averaged area under receiver operating characteristic curve achieved 0.95 and above. For the other three subjects, kinematics of the less affected limb or proximal joints in the paretic side were identified as the precursors to an ICT, potentially due to the variations of neuromotor deficits among stroke survivors. Although additional engineering efforts are still needed to address the challenges in making our design clinically practical, the outcome of this study may lead to further proactive engineering mechanisms for ICT avoidance and therefore reduce the risk of falls in individuals with stroke.

  14. Masting promotes individual- and population-level reproduction by increasing pollination efficiency.

    PubMed

    Moreira, Xoaquín; Abdala-Roberts, Luis; Linhart, Yan B; Mooney, Kailen A

    2014-04-01

    Masting is a reproductive strategy defined as the intermittent and synchronized production of large seed crops by a plant population. The pollination efficiency hypothesis proposes that masting increases pollination success in plants. Despite its general appeal, no previous studies have used long-term data together with population- and individual-level analyses to assess pollination efficiency between mast and non-mast events. Here we rigorously tested the pollination efficiency hypothesis in ponderosa pine (Pinus ponderosa), a long-lived monoecious, wind-pollinated species, using a data set on 217 trees monitored annually for 20 years. Relative investment in male and female function by individual trees did not vary between mast and non-mast years. At both the population and individual level, the rate of production of mature female cones relative to male strobili production was higher in mast than non-mast years, consistent with the predicted benefit of reproductive synchrony on reproductive success. In addition, at the individual level we found a higher conversion of unfertilized female conelets into mature female cones during a mast year compared to a non-mast year. Collectively, parallel results at the population and individual tree level provide robust evidence for the ecological, and potentially also evolutionary, benefits of masting through increased pollination efficiency.

  15. Prediction of Individual Brain Maturity Using fMRI

    PubMed Central

    Dosenbach, Nico U. F.; Nardos, Binyam; Cohen, Alexander L.; Fair, Damien A.; Power, Jonathan D.; Church, Jessica A.; Nelson, Steven M.; Wig, Gagan S.; Vogel, Alecia C.; Lessov-Schlaggar, Christina N.; Barnes, Kelly Anne; Dubis, Joseph W.; Feczko, Eric; Coalson, Rebecca S.; Pruett, John R.; Barch, Deanna M.; Petersen, Steven E.; Schlaggar, Bradley L.

    2011-01-01

    Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals’ brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain’s major functional networks. PMID:20829489

  16. Efficient Methods to Compute Genomic Predictions

    USDA-ARS?s Scientific Manuscript database

    Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and simultaneously estimate thousands of marker effects. Algorithms were derived and computer programs tested on simulated data for 50,000 markers and 2,967 bulls. Accurate estimates of ...

  17. Auditory working memory predicts individual differences in absolute pitch learning.

    PubMed

    Van Hedger, Stephen C; Heald, Shannon L M; Koch, Rachelle; Nusbaum, Howard C

    2015-07-01

    Absolute pitch (AP) is typically defined as the ability to label an isolated tone as a musical note in the absence of a reference tone. At first glance the acquisition of AP note categories seems like a perceptual learning task, since individuals must assign a category label to a stimulus based on a single perceptual dimension (pitch) while ignoring other perceptual dimensions (e.g., loudness, octave, instrument). AP, however, is rarely discussed in terms of domain-general perceptual learning mechanisms. This is because AP is typically assumed to depend on a critical period of development, in which early exposure to pitches and musical labels is thought to be necessary for the development of AP precluding the possibility of adult acquisition of AP. Despite this view of AP, several previous studies have found evidence that absolute pitch category learning is, to an extent, trainable in a post-critical period adult population, even if the performance typically achieved by this population is below the performance of a "true" AP possessor. The current studies attempt to understand the individual differences in learning to categorize notes using absolute pitch cues by testing a specific prediction regarding cognitive capacity related to categorization - to what extent does an individual's general auditory working memory capacity (WMC) predict the success of absolute pitch category acquisition. Since WMC has been shown to predict performance on a wide variety of other perceptual and category learning tasks, we predict that individuals with higher WMC should be better at learning absolute pitch note categories than individuals with lower WMC. Across two studies, we demonstrate that auditory WMC predicts the efficacy of learning absolute pitch note categories. These results suggest that a higher general auditory WMC might underlie the formation of absolute pitch categories for post-critical period adults. Implications for understanding the mechanisms that underlie the

  18. Predicting muscle forces of individuals with hemiparesis following stroke

    PubMed Central

    Kesar, Trisha M; Ding, Jun; Wexler, Anthony S; Perumal, Ramu; Maladen, Ryan; Binder-Macleod, Stuart A

    2008-01-01

    Background Functional electrical stimulation (FES) has been used to improve function in individuals with hemiparesis following stroke. An ideal functional electrical stimulation (FES) system needs an accurate mathematical model capable of designing subject and task-specific stimulation patterns. Such a model was previously developed in our laboratory and shown to predict the isometric forces produced by the quadriceps femoris muscles of able-bodied individuals and individuals with spinal cord injury in response to a wide range of clinically relevant stimulation frequencies and patterns. The aim of this study was to test our isometric muscle force model on the quadriceps femoris, ankle dorsiflexor, and ankle plantar-flexor muscles of individuals with post-stroke hemiparesis. Methods Subjects were seated on a force dynamometer and isometric forces were measured in response to a range of stimulation frequencies (10 to 80-Hz) and 3 different patterns. Subject-specific model parameter values were obtained by fitting the measured force responses from 2 stimulation trains. The model parameters thus obtained were then used to obtain predicted forces for a range of frequencies and patterns. Predicted and measured forces were compared using intra-class correlation coefficients, r2 values, and model error relative to the physiological error (variability of measured forces). Results Results showed excellent agreement between measured and predicted force-time responses (r2 >0.80), peak forces (ICCs>0.84), and force-time integrals (ICCs>0.82) for the quadriceps, dorsiflexor, and plantar-fexor muscles. The model error was within or below the +95% confidence interval of the physiological error for >88% comparisons between measured and predicted forces. Conclusion Our results show that the model has potential to be incorporated as a feed-forward controller for predicting subject-specific stimulation patterns during FES. PMID:18304360

  19. Efficient Coding of the Prediction Residual.

    DTIC Science & Technology

    1979-12-27

    Page I. Average of Fundamental and Formant Frequencies and Formant Amplitudes of Vowels by 76 Speakers .. ........... ... 28 II. Representation of IPA...0, 1, ..., M-1 p - Order of the LPC filter F1, F2, ... - Formant frequencies r,(m) - Output of the ith bandpass filter m = 0, 1, ..., M-l; z = 1, 2...correlation coefficients and other parameters that represent the formant frequency characteristics. The other waveform is the prediction residual. Figure

  20. Individual efficiency for the use of feed resources in rabbits.

    PubMed

    Piles, M; García-Tomás, M; Rafel, O; Ramon, J; Ibañez-Escriche, N; Varona, L

    2007-11-01

    A Bayesian procedure, which allows consideration of the individual variation in the feed resource allocation pattern, is described and implemented in 2 sire lines of rabbit (Caldes and R). The procedure is based on a hierarchical Bayesian scheme, where the first stage of the model consists of a multiple regression model of feed intake on metabolic BW and BW gain. In a second stage, an animal model was assumed including batch, parity order, litter size, and common environmental litter effects. Animals were reared during the fattening period (from weaning at 32 d of age to 60 d of age) in individual cages on an experimental farm, and were fed ad libitum with a commercial diet. Body weight (g) and cumulative feed intake (g) were recorded weekly. Individual BW gain (g) and average BW (ABW, g) were calculated from these data for each 7-d period. Metabolic BW (g(0.75)) was estimated as ABW(0.75). The number of animals actually measured was 444 and 445 in the Caldes and R lines, respectively. Marginal posterior distributions of the genetic parameters were obtained by Gibbs sampling. Posterior means (posterior SD) for heritabilities for partial coefficients of regression of feed intake on metabolic BW and feed intake on BW gain were estimated to be 0.35 (0.17) and 0.40 (0.17), respectively, in the Caldes line and 0.26 (0.19) and 0.27 (0.14), respectively, in line R. The estimated posterior means (posterior SD) for the proportion of the phenotypic variance due to common litter environmental effects of the same coefficients of regression were respectively, 0.39 (0.14) and 0.28 (0.13) in the Caldes line and 0.44 (0.22) and 0.49 (0.14) in line R. These results suggest that efficiency of use of feed resources could be improved by including these coefficients in an index of selection.

  1. Numerical prediction of Pelton turbine efficiency

    NASA Astrophysics Data System (ADS)

    Jošt, D.; Mežnar, P.; Lipej, A.

    2010-08-01

    This paper presents a numerical analysis of flow in a 2 jet Pelton turbine with horizontal axis. The analysis was done for the model at several operating points in different operating regimes. The results were compared to the results of a test of the model. Analysis was performed using ANSYS CFX-12.1 computer code. A k-ω SST turbulent model was used. Free surface flow was modelled by two-phase homogeneous model. At first, a steady state analysis of flow in the distributor with two injectors was performed for several needle strokes. This provided us with data on flow energy losses in the distributor and the shape and velocity of jets. The second step was an unsteady analysis of the runner with jets. Torque on the shaft was then calculated from pressure distribution data. Averaged torque values are smaller than measured ones. Consequently, calculated turbine efficiency is also smaller than the measured values, the difference is about 4 %. The shape of the efficiency diagram conforms well to the measurements.

  2. Predicting Individual Differences in Response to Sleep Loss

    DTIC Science & Technology

    2011-09-15

    2011 4. TITLE Predicting Individual Differences in Response to Sleep Loss 5a. Contract Number: 5b. Grant Number: 5c. Program Element Number: 5d...ADDRESS(ES) Naval Medical Reserach Unit – Dayton 2624 Q St., Bldg. 851, Area B Wright-Patterson AFB, OH 45433 8. PERFORMING ORGANIZATION... Program Department of the Navy 2300 E Street, NW Washington, DC 20372-5300 10. SPONSOR/MONITOR’S ACRONYM(S) BUMED 11. SPONSOR/MONITOR’S REPORT

  3. Stress responsiveness predicts individual variation in mate selectivity.

    PubMed

    Vitousek, Maren N; Romero, L Michael

    2013-06-15

    Steroid hormones, including glucocorticoids, mediate a variety of behavioral and physiological processes. Circulating hormone concentrations vary substantially within populations, and although hormone titers predict reproductive success in several species, little is known about how individual variation in circulating hormone concentrations is linked with most reproductive behaviors in free-living organisms. Mate choice is an important and often costly component of reproduction that also varies substantially within populations. We examined whether energetically costly mate selection behavior in female Galápagos marine iguanas (Amblyrhynchus cristatus) was associated with individual variation in the concentrations of hormones previously shown to differ between reproductive and non-reproductive females during the breeding season (corticosterone and testosterone). Stress-induced corticosterone levels - which are suppressed in female marine iguanas during reproduction - were individually repeatable throughout the seven-week breeding period. Mate selectivity was strongly predicted by individual variation in stress-induced corticosterone: reproductive females that secreted less corticosterone in response to a standardized stressor assessed more displaying males. Neither baseline corticosterone nor testosterone predicted variation in mate selectivity. Scaled body mass was not significantly associated with mate selectivity, but females that began the breeding period in lower body condition showed a trend towards being less selective about potential mates. These results provide the first evidence that individual variation in the corticosterone stress response is associated with how selective females are in their choice of a mate, an important contributor to fitness in many species. Future research is needed to determine the functional basis of this association, and whether transient acute increases in circulating corticosterone directly mediate mate choice behaviors.

  4. Who punishes? Personality traits predict individual variation in punitive sentiment.

    PubMed

    Roberts, S Craig; Vakirtzis, Antonios; Kristjánsdóttir, Lilja; Havlíček, Jan

    2013-02-18

    Cross-culturally, participants in public goods games reward participants and punish defectors to a degree beyond that warranted by rational, profit-maximizing considerations. Costly punishment, where individuals impose costs on defectors at a cost to themselves, is thought to promote the maintenance of cooperation. However, despite substantial variation in the extent to which people punish, little is known about why some individuals, and not others, choose to pay these costs. Here, we test whether personality traits might contribute to variation in helping and punishment behavior. We first replicate a previous study using public goods scenarios to investigate effects of sex, relatedness and likelihood of future interaction on willingness to help a group member or to punish a transgressor. As in the previous study, we find that individuals are more willing to help related than unrelated needy others and that women are more likely to express desire to help than men. Desire to help was higher if the probability of future interaction is high, at least among women. In contrast, among these variables, only participant sex predicted some measures of punitive sentiment. Extending the replication, we found that punitive sentiment, but not willingness to help, was predicted by personality traits. Most notably, participants scoring lower on Agreeableness expressed more anger towards and greater desire to punish a transgressor, and were more willing to engage in costly punishment, at least in our scenario. Our results suggest that some personality traits may contribute to underpinning individual variation in social enforcement of cooperation.

  5. Efficiency of individual dosage of digoxin with calculated concentration.

    PubMed

    Zhao, Li; Yang, Peng; Li, Pengmei; Wang, Xiaoxing; Qin, Wangjun; Zhang, Xianglin

    2014-01-01

    Digoxin is a frequently prescribed drug, particularly in the elderly population, in which there is an increased prevalence of atrial fibrillation and cardiac failure. With its complex pharmacokinetic profile and narrow therapeutic index, use of digoxin requires regular monitoring of blood levels. Recent evidence suggests that a lower concentration range (0.4-1.0 ng/mL) is preferable in patients with congestive heart failure and a higher range (0.8-2.0 ng/mL) is needed in patients with atrial tachyarrhythmia. The Konishi equation is widely used to predict the serum digoxin concentration (SDC) in Japan. This study assessed the correlation between SDC predicted by the Konishi equation and that actually measured in Chinese patients and investigated the impact of renal function on SDC. The study subjects comprised 72 patients with cardiac failure or/and atrial tachyarrhythmia seen at our hospital from January 2012 to December 2013. The patients were divided into five groups according to Kidney Diseases Outcome Quality Initiative guidelines. SDCs were measured using the Abbott Architect i1000 immunology analyzer. The correlations between measured SDCs and calculated SDCs and between clearance of digoxin and creatinine clearance rate were assessed retrospectively. The correlation between measured and predicted SDC calculated by the Konishi equation was significant (r=0.655, P<0.001) for the 72 patients overall; however, correlations within the different stages of renal function were nonsignificant, with a correlation found only in patients with stage 3 (30 mL per minute < creatinine clearance <60 mL per minute). With regard to the correlation between clearance of digoxin and creatinine clearance, our results show that although there was a significant correlation between clearance of digoxin and creatinine clearance in the group overall, correlations were not evident within the different stages of renal function. The results of this study indicate that clearance of digoxin

  6. Aeration efficiency over stepped cascades: better predictions from flow regimes.

    PubMed

    Khdhiri, Hatem; Potier, Olivier; Leclerc, Jean-Pierre

    2014-05-15

    Stepped cascades are recognized as high potential air-water gas exchangers. In natural rivers, these structures enhance oxygen transfer to water by creating turbulence at interface with increasing air entrainment in water and air-water surface exchange. Stepped cascades could be really useful to improve the natural self-purification process by providing oxygen to aerobic micro-organisms. The aeration performance of these structures depends on several operating and geometrical parameters. In the literature, several empirical correlations for aeration efficiency prediction on stepped cascades exist. Most of these correlations are only applicable for operating and geometrical parameters in the range of which they have been developed. In this paper, 398 experimental sets of data (from our experiments and collected from literature) were used to develop a correlation for aeration prediction over stepped cascades derived from dimensional analysis and parameterized for each individual flow regime in order to consider change in flow regime effect on oxygen transfer. This new correlation allowed calculating the whole set of data obtained for cascades with steps heights between 0.05 m and 0.254 m, cascade total height between 0.25 m and 2.5 m, for discharges per unit of width ranging from 0.28 10(-3) m(2)/s to 600 10(-3) m(2)/s and for cascade steps number between 3 and 25. In these ranges of parameters, standard deviation for aeration efficiency estimation was found to be less than 17%. Finally, advices were proposed to help and improve the structure design in order to improve aeration. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Individual Identifiability Predicts Population Identifiability in Forensic Microsatellite Markers.

    PubMed

    Algee-Hewitt, Bridget F B; Edge, Michael D; Kim, Jaehee; Li, Jun Z; Rosenberg, Noah A

    2016-04-04

    Highly polymorphic genetic markers with significant potential for distinguishing individual identity are used as a standard tool in forensic testing [1, 2]. At the same time, population-genetic studies have suggested that genetically diverse markers with high individual identifiability also confer information about genetic ancestry [3-6]. The dual influence of polymorphism levels on ancestry inference and forensic desirability suggests that forensically useful marker sets with high levels of individual identifiability might also possess substantial ancestry information. We study a standard forensic marker set-the 13 CODIS loci used in the United States and elsewhere [2, 7-9]-together with 779 additional microsatellites [10], using direct population structure inference to test whether markers with substantial individual identifiability also produce considerable information about ancestry. Despite having been selected for individual identification and not for ancestry inference [11], the CODIS markers generate nontrivial model-based clustering patterns similar to those of other sets of 13 tetranucleotide microsatellites. Although the CODIS markers have relatively low values of the F(ST) divergence statistic, their high heterozygosities produce greater ancestry inference potential than is possessed by less heterozygous marker sets. More generally, we observe that marker sets with greater individual identifiability also tend toward greater population identifiability. We conclude that population identifiability regularly follows as a byproduct of the use of highly polymorphic forensic markers. Our findings have implications for the design of new forensic marker sets and for evaluations of the extent to which individual characteristics beyond identification might be predicted from current and future forensic data.

  8. Individualized Risk Prediction Model for Lung Cancer in Korean Men

    PubMed Central

    Park, Sohee; Nam, Byung-Ho; Yang, Hye-Ryung; Lee, Ji An; Lim, Hyunsun; Han, Jun Tae; Park, Il Su; Shin, Hai-Rim; Lee, Jin Soo

    2013-01-01

    Purpose Lung cancer is the leading cause of cancer deaths in Korea. The objective of the present study was to develop an individualized risk prediction model for lung cancer in Korean men using population-based cohort data. Methods From a population-based cohort study of 1,324,804 Korean men free of cancer at baseline, the individualized absolute risk of developing lung cancer was estimated using the Cox proportional hazards model. We checked the validity of the model using C statistics and the Hosmer–Lemeshow chi-square test on an external validation dataset. Results The risk prediction model for lung cancer in Korean men included smoking exposure, age at smoking initiation, body mass index, physical activity, and fasting glucose levels. The model showed excellent performance (C statistic = 0.871, 95% CI = 0.867–0.876). Smoking was significantly associated with the risk of lung cancer in Korean men, with a four-fold increased risk in current smokers consuming more than one pack a day relative to non-smokers. Age at smoking initiation was also a significant predictor for developing lung cancer; a younger age at initiation was associated with a higher risk of developing lung cancer. Conclusion This is the first study to provide an individualized risk prediction model for lung cancer in an Asian population with very good model performance. In addition to current smoking status, earlier exposure to smoking was a very important factor for developing lung cancer. Since most of the risk factors are modifiable, this model can be used to identify those who are at a higher risk and who can subsequently modify their lifestyle choices to lower their risk of lung cancer. PMID:23408946

  9. Folk beliefs about genetic variation predict avoidance of biracial individuals

    PubMed Central

    Kang, Sonia K.; Plaks, Jason E.; Remedios, Jessica D.

    2015-01-01

    People give widely varying estimates for the amount of genetic overlap that exists between humans. While some laypeople believe that humans are highly genetically similar to one another, others believe that humans share very little genetic overlap. These studies examine how beliefs about genetic overlap affect neural and evaluative reactions to racially-ambiguous and biracial targets. In Study 1, we found that lower genetic overlap estimates predicted a stronger neural avoidance response to biracial compared to monoracial targets. In Study 2, we found that lower genetic overlap estimates predicted longer response times to classify biracial (vs. monoracial) faces into racial categories. In Study 3, we manipulated genetic overlap beliefs and found that participants in the low overlap condition explicitly rated biracial targets more negatively than those in the high overlap condition. Taken together, these data suggest that genetic overlap beliefs influence perceivers’ processing fluency and evaluation of biracial and racially-ambiguous individuals. PMID:25904875

  10. Individual differences in time perspective predict autonoetic experience.

    PubMed

    Arnold, Kathleen M; McDermott, Kathleen B; Szpunar, Karl K

    2011-09-01

    Tulving (1985) posited that the capacity to remember is one facet of a more general capacity-autonoetic (self-knowing) consciousness. Autonoetic consciousness was proposed to underlie the ability for "mental time travel" both into the past (remembering) and into the future to envision potential future episodes (episodic future thinking). The current study examines whether individual differences can predict autonoetic experience. Specifically, the Zimbardo Time Perspective Inventory (ZTPI, Zimbardo & Boyd, 1999) was administered to 133 undergraduate students, who also rated phenomenological experiences accompanying autobiographical remembering and episodic future thinking. Scores on two of the five subscales of the ZTPI (Future and Present-Hedonistic) predicted the degree to which people reported feelings of mentally traveling backward (or forward) in time and the degree to which they reported re- or pre-experiencing the event, but not ten other rated properties less related to autonoetic consciousness.

  11. Individual differences during acquisition predict shifts in generalization.

    PubMed

    Wisniewski, Matthew G; Church, Barbara A; Mercado, Eduardo

    2014-05-01

    Learning to distinguish subtle differences in objects or events can impact how one generalizes. In some cases, training can cause novel events to appear more familiar or attractive than those actually experienced during training: the peak shift effect. This study examined whether individual differences in learning led to systematic patterns of generalization. Participants were trained to identify simulated birdsongs, and then tested on their ability to identify a target song presented among several similar songs that differed in pitch. Initial analysis showed that those attaining moderate proficiency at discriminating songs during training were more likely to shift than those performing poorly or proficiently. However, a neural network trained to output individuals' gradient dynamics using only performance during training as input found an additional set of training variables that predicted shift. Specifically, one subset of shifters had highly conservative response biases accompanied by very little change to perceptual sensitivity in training. These findings suggest that discrimination learning may only lead to generalization shifts in some individuals, and that all individuals who shift may not do so for the same reason.

  12. Predicting the Individual Risk of Acute Severe Colitis at Diagnosis.

    PubMed

    Cesarini, Monica; Collins, Gary S; Rönnblom, Anders; Santos, Antonieta; Wang, Lai Mun; Sjöberg, Daniel; Parkes, Miles; Keshav, Satish; Travis, Simon P L

    2017-03-01

    Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. The development cohort included patients aged 16-89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1-29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10mg/l, or haemoglobin < 12g/dl F or < 14g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy.

  13. Prediction of Alzheimer's disease using individual structural connectivity networks

    PubMed Central

    Shao, Junming; Myers, Nicholas; Yang, Qinli; Feng, Jing; Plant, Claudia; Böhm, Christian; Förstl, Hans; Kurz, Alexander; Zimmer, Claus; Meng, Chun; Riedl, Valentin; Wohlschläger, Afra; Sorg, Christian

    2012-01-01

    Alzheimer's disease (AD) progressively degrades the brain's gray and white matter. Changes in white matter reflect changes in the brain's structural connectivity pattern. Here, we established individual structural connectivity networks (ISCNs) to distinguish predementia and dementia AD from healthy aging in individual scans. Diffusion tractography was used to construct ISCNs with a fully automated procedure for 21 healthy control subjects (HC), 23 patients with mild cognitive impairment and conversion to AD dementia within 3 years (AD-MCI), and 17 patients with mild AD dementia. Three typical pattern classifiers were used for AD prediction. Patients with AD and AD-MCI were separated from HC with accuracies greater than 95% and 90%, respectively, irrespective of prediction approach and specific fiber properties. Most informative connections involved medial prefrontal, posterior parietal, and insular cortex. Patients with mild AD were separated from those with AD-MCI with an accuracy of approximately 85%. Our finding provides evidence that ISCNs are sensitive to the impact of earliest stages of AD. ISCNs may be useful as a white matter-based imaging biomarker to distinguish healthy aging from AD. PMID:22405045

  14. Prediction and Quantification of Individual Athletic Performance of Runners.

    PubMed

    Blythe, Duncan A J; Király, Franz J

    2016-01-01

    We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners' performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel's formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design.

  15. Prediction and Quantification of Individual Athletic Performance of Runners

    PubMed Central

    2016-01-01

    We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners’ performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel’s formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design. PMID:27336162

  16. Predictability and heritability of individual differences in fear learning.

    PubMed

    Shumake, Jason; Furgeson-Moreira, Sergio; Monfils, Marie H

    2014-09-01

    Our objective was to characterize individual differences in fear conditioning and extinction in an outbred rat strain, to test behavioral predictors of these individual differences, and to assess their heritability. We fear-conditioned 100 Long-Evans rats, attempted to extinguish fear the next day, and tested extinction recall on the third day. The distribution of freezing scores after fear conditioning was skewed, with most rats showing substantial freezing; after fear extinction, the distribution was bimodal with most rats showing minimal freezing, but a substantial portion showing maximal freezing. Longer rearing episodes measured prior to conditioning predicted less freezing at the beginning of extinction, but differences in extinction learning were not predicted by any baseline exploratory behaviors. We tested the heritability of extinction differences by breeding rats from the top and bottom 20% of freezing scores during extinction recall. We then ran the offspring through the same conditioning/extinction procedure, with the addition of recording ultrasonic vocalizations throughout training and testing. Only a minority of rats emitted distress vocalizations during fear acquisition, but the incidence was less frequent in the offspring of good extinguishers than in poor extinguishers or randomly bred controls. The occurrence of distress vocalizations during acquisition predicted higher levels of freezing during fear recall regardless of breeding line, but the relationship between vocalization and freezing was no longer evident following extinction training, at which point freezing levels were influenced only by breeding and not by vocalization. The heritability (h(2)) of extinction recall was estimated at 0.36, consistent with human estimates.

  17. Predicting Smartphone Operating System from Personality and Individual Differences.

    PubMed

    Shaw, Heather; Ellis, David A; Kendrick, Libby-Rae; Ziegler, Fenja; Wiseman, Richard

    2016-12-01

    Android and iPhone devices account for over 90 percent of all smartphones sold worldwide. Despite being very similar in functionality, current discourse and marketing campaigns suggest that key individual differences exist between users of these two devices; however, this has never been investigated empirically. This is surprising, as smartphones continue to gain momentum across a variety of research disciplines. In this article, we consider if individual differences exist between these two distinct groups. In comparison to Android users, we found that iPhone owners are more likely to be female, younger, and increasingly concerned about their smartphone being viewed as a status object. Key differences in personality were also observed with iPhone users displaying lower levels of Honesty-Humility and higher levels of emotionality. Following this analysis, we were also able to build and test a model that predicted smartphone ownership at above chance level based on these individual differences. In line with extended self-theory, the type of smartphone owned provides some valuable information about its owner. These findings have implications for the increasing use of smartphones within research particularly for those working within Computational Social Science and PsychoInformatics, where data are typically collected from devices and applications running a single smartphone operating system.

  18. Individual differences in intrinsic brain connectivity predict decision strategy

    PubMed Central

    Anderson, Kevin M.; Plitt, Mark; Martin, Alex

    2014-01-01

    When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions. PMID:25031254

  19. Individual differences in intrinsic brain connectivity predict decision strategy.

    PubMed

    Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

    2014-10-15

    When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

  20. Characterisation of individual pixel efficiency in the PILATUS II sensor

    NASA Astrophysics Data System (ADS)

    Schubert, A.; O'Keefe, G. J.; Sobott, B. A.; Kirby, N. M.; Rassool, R. P.

    2010-11-01

    Synchrotron applications such as protein crystallography and small-angle X-ray scattering (SAXS) demand precise knowledge of detector pixel efficiency for data corrections. Current techniques used to determine detector efficiency are only applicable for the specific set-up for which the calibration is performed. Here the effect of comparator thresholding on pixel efficiency for PILATUS is presented for standard amplifier and shaper gain settings, allowing users to make necessary corrections to their intensity data for various threshold settings without requiring repeated empirical calibrations. A three-dimensional TCAD simulation of the sensor is also presented and is used to confirm the experimental result.

  1. A Multi-Scale Modeling Framework for Individualized, Spatiotemporal Prediction of Drug Effects and Toxicological Risk

    PubMed Central

    Diaz Ochoa, Juan G.; Bucher, Joachim; Péry, Alexandre R. R.; Zaldivar Comenges, José M.; Niklas, Jens; Mauch, Klaus

    2013-01-01

    In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy. PMID:23346056

  2. Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data.

    PubMed

    Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D

    2017-01-15

    Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r=0.7033, MCCB social cognition r=0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r=0.7785, PANSS negative r=0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Individual differences in saccharin acceptance predict rats' food intake.

    PubMed

    Boakes, Robert A; Martire, Sarah I; Rooney, Kieron B; Kendig, Michael D

    2016-10-01

    Following previous results indicating that low acceptance of saccharin-sweetened yoghurt was associated with slower weight gain, the aim of this experiment was to determine which of three measures of individual differences would predict subsequent chow consumption, body weight gain, and fat mass. Pre-test measures consisted of amount of running in an activity wheel, amount of 0.1% saccharin solution consumed over 24h, and performance on an elevated plus maze (EPM). Rats were then maintained for three weeks on a diet of standard chow and water. Subsequent post-testing repeated the procedures used in pre-testing. The rats were then culled and fat pads excised and weighed. Pre-testing revealed a negative correlation between saccharin acceptance and activity, while neither measure correlated with anxiety in the EPM. Pre-test saccharin acceptance was positively correlated with subsequent chow consumption, percent weight gain, and g/kg fat mass. Multiple regression analyses including all three pre-test measures confirmed saccharin acceptance as a predictor of chow consumption and, marginally, of fat pad mass, while high anxiety predicted low percent body weight gain. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Predicting the use of Individualized Risk Assessment for Breast Cancer

    PubMed Central

    Bartle-Haring, Suzanne; Toviessi, Paula; Katafiasz, Heather

    2008-01-01

    Purpose The purpose of this study was to investigate the decision to obtain individualized risk assessment after a breast cancer education session. Methods A sample of both African American and Caucasian women was used to determine if there were differences by race/ethnicity in uptake of the assessment and differences in the variables that were most predictive of uptake. The sample included 166 women between the ages of 18 and 80. Sixty-two percent of the sample were African American women. Key Findings The results suggested that African American women and Caucasian women used different factors and used other factors differently to decide whether or not to obtain an individualized risk assessment. Conclusions and Implications These results are discussed within the context of health disparities among ethnic minority and Caucasian women with implications for breast cancer control programs. The results of this study would suggest that knowledge alone does not lead to opting for a personalized risk assessment, and that African American and Caucasian women use different pieces of information, or information differently to make decision about getting more personalized information about risk. PMID:18319147

  5. Multimodal Movement Prediction - Towards an Individual Assistance of Patients

    PubMed Central

    Kirchner, Elsa Andrea; Tabie, Marc; Seeland, Anett

    2014-01-01

    Assistive devices, like exoskeletons or orthoses, often make use of physiological data that allow the detection or prediction of movement onset. Movement onset can be detected at the executing site, the skeletal muscles, as by means of electromyography. Movement intention can be detected by the analysis of brain activity, recorded by, e.g., electroencephalography, or in the behavior of the subject by, e.g., eye movement analysis. These different approaches can be used depending on the kind of neuromuscular disorder, state of therapy or assistive device. In this work we conducted experiments with healthy subjects while performing self-initiated and self-paced arm movements. While other studies showed that multimodal signal analysis can improve the performance of predictions, we show that a sensible combination of electroencephalographic and electromyographic data can potentially improve the adaptability of assistive technical devices with respect to the individual demands of, e.g., early and late stages in rehabilitation therapy. In earlier stages for patients with weak muscle or motor related brain activity it is important to achieve high positive detection rates to support self-initiated movements. To detect most movement intentions from electroencephalographic or electromyographic data motivates a patient and can enhance her/his progress in rehabilitation. In a later stage for patients with stronger muscle or brain activity, reliable movement prediction is more important to encourage patients to behave more accurately and to invest more effort in the task. Further, the false detection rate needs to be reduced. We propose that both types of physiological data can be used in an and combination, where both signals must be detected to drive a movement. By this approach the behavior of the patient during later therapy can be controlled better and false positive detections, which can be very annoying for patients who are further advanced in rehabilitation, can be

  6. Artificial neural networks reveal efficiency in genetic value prediction.

    PubMed

    Peixoto, L A; Bhering, L L; Cruz, C D

    2015-06-18

    The objective of this study was to evaluate the efficiency of artificial neural networks (ANNs) for predicting genetic value in experiments carried out in randomized blocks. Sixteen scenarios were simulated with different values of heritability (10, 20, 30, and 40%), coefficient of variation (5 and 10%), and the number of genotypes per block (150 and 200 for validation, and 5000 for neural network training). One hundred validation populations were used in each scenario. Accuracy of ANNs was evaluated by comparing the correlation of network value with genetic value, and of phenotypic value with genetic value. Neural networks were efficient in predicting genetic value with a 0.64 to 10.3% gain compared to the phenotypic value, regardless the simulated population size, heritability, or coefficient of variation. Thus, the artificial neural network is a promising technique for predicting genetic value in balanced experiments.

  7. pcrEfficiency: a Web tool for PCR amplification efficiency prediction

    PubMed Central

    2011-01-01

    Background Relative calculation of differential gene expression in quantitative PCR reactions requires comparison between amplification experiments that include reference genes and genes under study. Ignoring the differences between their efficiencies may lead to miscalculation of gene expression even with the same starting amount of template. Although there are several tools performing PCR primer design, there is no tool available that predicts PCR efficiency for a given amplicon and primer pair. Results We have used a statistical approach based on 90 primer pair combinations amplifying templates from bacteria, yeast, plants and humans, ranging in size between 74 and 907 bp to identify the parameters that affect PCR efficiency. We developed a generalized additive model fitting the data and constructed an open source Web interface that allows the obtention of oligonucleotides optimized for PCR with predicted amplification efficiencies starting from a given sequence. Conclusions pcrEfficiency provides an easy-to-use web interface allowing the prediction of PCR efficiencies prior to web lab experiments thus easing quantitative real-time PCR set-up. A web-based service as well the source code are provided freely at http://srvgen.upct.es/efficiency.html under the GPL v2 license. PMID:22014212

  8. Individual brain structure and modelling predict seizure propagation.

    PubMed

    Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

    2017-03-01

    See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

  9. Prediction of individual season of birth using MRI

    PubMed Central

    Pantazatos, Spiro P.

    2014-01-01

    Previous research suggests statistical associations between season of birth (SOB) with prevalence of neurobehavioral disorders such as schizophrenia and bipolar disorder, personality traits, and suicidal behavior. These effects are thought to be mediated by seasonal differences in perinatal photoperiod, which was recently shown to imprint circadian clock neurons and behavior in rodents. However, it is unknown whether SOB is associated with any measurable differences in the normal human adult brain, and whether individual SOB can be deduced based on phenotype. Here I show that SOB predicts neuroanatomical differences in regional grey matter volume, and that MRI scans carry spatially distributed information allowing significantly above chance prediction of an individual’s SOB. Using an open source database of over 550 structural brain scans, Voxel-Based Morphometry (VBM) analysis showed a significant SOB effect in left superior temporal gyrus (STG) in males (p=0.009, FWE whole-brain corrected), with greater grey matter volumes in fall and winter births. A cosinor analysis revealed a significant annual periodicity in left STG grey matter volume (Zero Amplitude Test: p<5×10-7), with a peak towards the end of December and a nadir towards the end of June, suggesting that perinatal photoperiod accounts for this SOB effect. Whole-brain VBM maps were used as input features to multivariate machine-learning based analyses to classify SOB. Significantly greater than chance prediction was achieved in females (overall accuracy 35%, p<0.001), but not in males (overall accuracy 26%, p=0.45). Pair-wise binary classification in females revealed the highest discrimination was obtained for winter vs. summer classification (peak area under the ROC curve=0.71, p<0.0005). Discriminating regions included fusiform and middle temporal gyrus, inferior and superior parietal lobe, cerebellum, and dorsolateral and dorsomedial prefrontal cortex. Results indicate SOB is detectable with MRI

  10. A model for individualized risk prediction of contralateral breast cancer.

    PubMed

    Chowdhury, Marzana; Euhus, David; Onega, Tracy; Biswas, Swati; Choudhary, Pankaj K

    2017-01-01

    Patients diagnosed with invasive breast cancer (BC) or ductal carcinoma in situ are increasingly choosing to undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral BC (CBC). This is a particularly disturbing trend as a large proportion of these CPMs are believed to be medically unnecessary. Many BC patients tend to substantially overestimate their CBC risk. Thus, there is a pressing need to educate patients effectively on their CBC risk. We develop a CBC risk prediction model to aid physicians in this task. We used data from two sources: Breast Cancer Surveillance Consortium and Surveillance, Epidemiology, and End Results to build the model. The model building steps are similar to those used in developing the BC risk assessment tool (popularly known as Gail model) for counseling women on their BC risk. Our model, named CBCRisk, is exclusively designed for counseling women diagnosed with unilateral BC on the risk of developing CBC. We identified eight factors to be significantly associated with CBC-age at first BC diagnosis, anti-estrogen therapy, family history of BC, high-risk pre-neoplasia status, estrogen receptor status, breast density, type of first BC, and age at first birth. Combining the relative risk estimates with the relevant hazard rates, CBCRisk projects absolute risk of developing CBC over a given period. By providing individualized CBC risk estimates, CBCRisk may help in counseling of BC patients. In turn, this may potentially help alleviate the rate of medically unnecessary CPMs.

  11. Individual Differences in Nonsymbolic Ratio Processing Predict Symbolic Math Performance.

    PubMed

    Matthews, Percival G; Lewis, Mark Rose; Hubbard, Edward M

    2016-02-01

    What basic capacities lay the foundation for advanced numerical cognition? Are there basic nonsymbolic abilities that support the understanding of advanced numerical concepts, such as fractions? To date, most theories have posited that previously identified core numerical systems, such as the approximate number system (ANS), are ill-suited for learning fraction concepts. However, recent research in developmental psychology and neuroscience has revealed a ratio-processing system (RPS) that is sensitive to magnitudes of nonsymbolic ratios and may be ideally suited for supporting fraction concepts. We provide evidence for this hypothesis by showing that individual differences in RPS acuity predict performance on four measures of mathematical competence, including a university entrance exam in algebra. We suggest that the nonsymbolic RPS may support symbolic fraction understanding much as the ANS supports whole-number concepts. Thus, even abstract mathematical concepts, such as fractions, may be grounded not only in higher-order logic and language, but also in basic nonsymbolic processing abilities. © The Author(s) 2015.

  12. Individual differences in white matter microstructure predict semantic control.

    PubMed

    Nugiel, Tehila; Alm, Kylie H; Olson, Ingrid R

    2016-12-01

    In everyday conversation, we make many rapid choices between competing concepts and words in order to convey our intent. This process is termed semantic control, and it is thought to rely on information transmission between a distributed semantic store in the temporal lobes and a more discrete region, optimized for retrieval and selection, in the left inferior frontal gyrus. Here, we used diffusion tensor imaging in a group of neurologically normal young adults to investigate the relationship between semantic control and white matter tracts that have been implicated in semantic memory retrieval. Participants completed a verb generation task that taps semantic control (Snyder & Munakata, 2008; Snyder et al., 2010) and underwent a diffusion imaging scan. Deterministic tractography was performed to compute indices representing the microstructural properties of the inferior fronto-occipital fasciculus (IFOF), the uncinate fasciculus (UF), and the inferior longitudinal fasciculus (ILF). Microstructural measures of the UF failed to predict semantic control performance. However, there was a significant relationship between microstructure of the left IFOF and ILF and individual differences in semantic control. Our findings support the view put forth by Duffau (2013) that the IFOF is a key structural pathway in semantic retrieval.

  13. Culture and self in South Africa: individualism-collectivism predictions.

    PubMed

    Eaton, L; Louw, J

    2000-04-01

    People from collectivist cultures may have more concrete and interdependent self-concepts than do people from individualist cultures (G. Hofstede, 1980). African cultures are considered collectivist (H. C. Triandis, 1989), but research on self-concept and culture has neglected this continent. The authors attempted a partial replication in an African context of cross-cultural findings on the abstract-concrete and independent-interdependent dimensions of self-construal (referred to as the abstract-specific and the autonomous-social dimensions, respectively, by E. Rhee, J. S. Uleman, H. K. Lee, & R. J. Roman, 1995). University students in South Africa took the 20 Statements Test (M. Kuhn & T. S. McPartland, 1954; Rhee et al.); home languages were rough indicators of cultural identity. The authors used 3 coding schemes to analyze the content of 78 protocols from African-language speakers and 77 protocols from English speakers. In accord with predictions from individualism-collectivism theory, the African-language speakers produced more interdependent and concrete self-descriptions than did the English speakers. Additional findings concerned the orthogonality of the 2 dimensions and the nature and assessment of the social self-concept.

  14. An analytical method to predict efficiency of aircraft gearboxes

    NASA Technical Reports Server (NTRS)

    Anderson, N. E.; Loewenthal, S. H.; Black, J. D.

    1984-01-01

    A spur gear efficiency prediction method previously developed by the authors was extended to include power loss of planetary gearsets. A friction coefficient model was developed for MIL-L-7808 oil based on disc machine data. This combined with the recent capability of predicting losses in spur gears of nonstandard proportions allows the calculation of power loss for complete aircraft gearboxes that utilize spur gears. The method was applied to the T56/501 turboprop gearbox and compared with measured test data. Bearing losses were calculated with large scale computer programs. Breakdowns of the gearbox losses point out areas for possible improvement.

  15. An analytical method to predict efficiency of aircraft gearboxes

    NASA Technical Reports Server (NTRS)

    Anderson, N. E.; Loewenthal, S. H.; Black, J. D.

    1984-01-01

    A spur gear efficiency prediction method previously developed by the authors was extended to include power loss of planetary gearsets. A friction coefficient model was developed for MIL-L-7808 oil based on disc machine data. This combined with the recent capability of predicting losses in spur gears of nonstandard proportions allows the calculation of power loss for complete aircraft gearboxes that utilize spur gears. The method was applied to the T56/501 turboprop gearbox and compared with measured test data. Bearing losses were calculated with large scale computer programs. Breakdowns of the gearbox losses point out areas for possible improvement.

  16. Using connectome-based predictive modeling to predict individual behavior from brain connectivity.

    PubMed

    Shen, Xilin; Finn, Emily S; Scheinost, Dustin; Rosenberg, Monica D; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

    2017-03-01

    Neuroimaging is a fast-developing research area in which anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale data sets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: (i) feature selection, (ii) feature summarization, (iii) model building, and (iv) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a considerable amount of the variance in these measures. It has been demonstrated that the CPM protocol performs as well as or better than many of the existing approaches in brain-behavior prediction. As CPM focuses on linear modeling and a purely data-driven approach, neuroscientists with limited or no experience in machine learning or optimization will find it easy to implement these protocols. Depending on the volume of data to be processed, the protocol can take 10-100 min for model building, 1-48 h for permutation testing, and 10-20 min for visualization of results.

  17. An Improved Methodology for Individualized Performance Prediction of Sleep-Deprived Individuals with the Two-Process Model

    DTIC Science & Technology

    2009-01-01

    process model of sleep regulation for developing individualized biomathematical models that predict performance impairment for individuals subjected to total sleep loss. This new method advances our previous work in two important ways. First, it enables model customization to start as soon as the first performance measurement from an individual becomes available. This was achieved by optimally combining the performance information obtained from the individual’s performance measurements with a priori performance information using a Bayesian framework, while retaining

  18. Efficient clustering of identity-by-descent between multiple individuals

    PubMed Central

    Qian, Yu; Browning, Brian L.; Browning, Sharon R.

    2014-01-01

    Motivation: Most existing identity-by-descent (IBD) detection methods only consider haplotype pairs; less attention has been paid to considering multiple haplotypes simultaneously, even though IBD is an equivalence relation on haplotypes that partitions a set of haplotypes into IBD clusters. Multiple-haplotype IBD clusters may have advantages over pairwise IBD in some applications, such as IBD mapping. Existing methods for detecting multiple-haplotype IBD clusters are often computationally expensive and unable to handle large samples with thousands of haplotypes. Results: We present a clustering method, efficient multiple-IBD, which uses pairwise IBD segments to infer multiple-haplotype IBD clusters. It expands clusters from seed haplotypes by adding qualified neighbors and extends clusters across sliding windows in the genome. Our method is an order of magnitude faster than existing methods and has comparable performance with respect to the quality of clusters it uncovers. We further investigate the potential application of multiple-haplotype IBD clusters in association studies by testing for association between multiple-haplotype IBD clusters and low-density lipoprotein cholesterol in the Northern Finland Birth Cohort. Using our multiple-haplotype IBD cluster approach, we found an association with a genomic interval covering the PCSK9 gene in these data that is missed by standard single-marker association tests. Previously published studies confirm association of PCSK9 with low-density lipoprotein. Availability and implementation: Source code is available under the GNU Public License http://cs.au.dk/~qianyuxx/EMI/. Contact: qianyuxx@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24363374

  19. Hepcidin level predicts hemoglobin concentration in individuals undergoing repeated phlebotomy.

    PubMed

    Mast, Alan E; Schlumpf, Karen S; Wright, David J; Johnson, Bryce; Glynn, Simone A; Busch, Michael P; Olbina, Gordana; Westerman, Mark; Nemeth, Elizabeta; Ganz, Tomas

    2013-08-01

    Dietary iron absorption is regulated by hepcidin, an iron regulatory protein produced by the liver. Hepcidin production is regulated by iron stores, erythropoiesis and inflammation, but its physiology when repeated blood loss occurs has not been characterized. Hepcidin was assayed in plasma samples obtained from 114 first-time/reactivated (no blood donations in preceding 2 years) female donors and 34 frequent (≥3 red blood cell donations in preceding 12 months) male donors as they were phlebotomized ≥4 times over 18-24 months. Hepcidin levels were compared to ferritin and hemoglobin levels using multivariable repeated measures regression models. Hepcidin, ferritin and hemoglobin levels declined with increasing frequency of donation in the first-time/reactivated females. Hepcidin and ferritin levels correlated well with each other (Spearman's correlation of 0.74), but on average hepcidin varied more between donations for a given donor relative to ferritin. In a multivariable repeated measures regression model the predicted inter-donation decline in hemoglobin varied as a function of hepcidin and ferritin; hemoglobin was 0.51 g/dL lower for subjects with low (>45.7 ng/mL) or decreasing hepcidin and low ferritin (>26 ng/mL), and was essentially zero for other subjects including those with high (>45.7 ng/mL) or increasing hepcidin and low ferritin (>26 ng/mL) levels (P<0.001). In conclusion, hepcidin levels change rapidly in response to dietary iron needed for erythropoiesis. The dynamic regulation of hepcidin in the presence of a low levels of ferritin suggests that plasma hepcidin concentration may provide clinically useful information about an individual's iron status (and hence capacity to tolerate repeated blood donations) beyond that of ferritin alone. Clinicaltrials.gov identifier: NCT00097006.

  20. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

  1. Predicting Change in Postpartum Depression: An Individual Growth Curve Approach.

    ERIC Educational Resources Information Center

    Buchanan, Trey

    Recently, methodologists interested in examining problems associated with measuring change have suggested that developmental researchers should focus upon assessing change at both intra-individual and inter-individual levels. This study used an application of individual growth curve analysis to the problem of maternal postpartum depression.…

  2. Predicting Change in Postpartum Depression: An Individual Growth Curve Approach.

    ERIC Educational Resources Information Center

    Buchanan, Trey

    Recently, methodologists interested in examining problems associated with measuring change have suggested that developmental researchers should focus upon assessing change at both intra-individual and inter-individual levels. This study used an application of individual growth curve analysis to the problem of maternal postpartum depression.…

  3. Joint prediction of multiple scores captures better individual traits from brain images.

    PubMed

    Rahim, Mehdi; Thirion, Bertrand; Bzdok, Danilo; Buvat, Irène; Varoquaux, Gaël

    2017-09-01

    To probe individual variations in brain organization, population imaging relates features of brain images to rich descriptions of the subjects such as genetic information or behavioral and clinical assessments. Capturing common trends across these measurements is important: they jointly characterize the disease status of patient groups. In particular, mapping imaging features to behavioral scores with predictive models opens the way toward more precise diagnosis. Here we propose to jointly predict all the dimensions (behavioral scores) that make up the individual profiles, using so-called multi-output models. This approach often boosts prediction accuracy by capturing latent shared information across scores. We demonstrate the efficiency of multi-output models on two independent resting-state fMRI datasets targeting different brain disorders (Alzheimer's Disease and schizophrenia). Furthermore, the model with joint prediction generalizes much better to a new cohort: a model learned on one study is more accurately transferred to an independent one. Finally, we show how multi-output models can easily be extended to multi-modal settings, combining heterogeneous data sources for a better overall accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Individual cell heterogeneity in Predictive Food Microbiology: Challenges in predicting a "noisy" world.

    PubMed

    Koutsoumanis, Konstantinos P; Aspridou, Zafiro

    2017-01-02

    Gene expression is a fundamentally noisy process giving rise to a significant cell to cell variability at the phenotype level. The phenotypic noise is manifested in a wide range of microbial traits. Heterogeneous behavior of individual cells is observed at the growth, survival and inactivation responses and should be taken into account in the context of Predictive Food Microbiology (PMF). Recent methodological advances can be employed for the study and modeling of single cell dynamics leading to a new generation of mechanistic models which can provide insight into the link between phenotype, gene-expression, protein and metabolic functional units at the single cell level. Such models however, need to deal with an enormous amount of interactions and processes that influence each other, forming an extremely complex system. In this review paper, we discuss the importance of noise and present the future challenges in predicting the "noisy" microbial responses in foods.

  5. TPV efficiency measurements and predictions for a closed cavity geometry

    SciTech Connect

    Gethers, C.K.; Ballinger, C.T.; Postlethwait, M.A.; DePoy, D.M.; Baldasaro, P.F.

    1997-05-01

    A thermophotovoltaic (TPV) efficiency measurement, within a closed cavity, is an integrated test which incorporates four fundamental parameters of TPV direct energy conversion. These are: (1) the TPV devices, (2) spectral control, (3) a radiation/photon source, and (4) closed cavity geometry effects. The overall efficiency of the TPV device is controlled by the TP cell performance, the spectral control characteristics, the radiator temperature and the geometric arrangement. Controlled efficiency measurements and predictions provide valuable feedback on all four. This paper describes and compares two computer codes developed to model 16, 1 cm{sup 2} TPV cells (in a 4 x 4 configuration) in a cavity geometry. The first code, subdivides the infrared spectrum into several bands and then numerically integrates over the spectrum to provide absorbed heat flux and cell electrical output performance predictions (assuming infinite parallel plates). The second code, utilizes a Monte Carlo Photon Transport code that tracks photons, from birth at the radiation source, until they either escape or are absorbed. Absorption depends upon energy dependent reflection probabilities assigned to every geometrical surface within the cavity. The model also has the capability of tallying above and below bandgap absorptions (as a function of location) and can support various radiator temperature profiles. The arrays were fabricated using 0.55 eV InGaAs cells with Si/SiO interference filters for spectral control and at steady state conditions, array efficiency was calculated as the ratio of the load matched power to its absorbed heat flux. Preliminary experimental results are also compared with predictions.

  6. TPV efficiency predictions and measurements for a closed cavity geometry

    SciTech Connect

    Gethers, C.K.; Ballinger, C.T.; Postlethwait, M.A.; DePoy, D.M.; Baldasaro, P.F.

    1997-05-01

    A thermophotovoltaic (TPV) efficiency measurement, within a closed cavity, is an integrated test which incorporates four fundamental parameters of TPV direct energy conversion. These are: (1) the TPV devices, (2) spectral control, (3) a radiation/photon source, and (4) closed cavity geometry affects. The overall efficiency of the TPV device is controlled by the TPV cell performance, the spectral control characteristics, the radiator temperature and the geometric arrangement. Controlled efficiency measurements and predictions provide valuable feedback on all four. This paper describes and compares two computer codes developed to model 16, 1 cm{sup 2} TPV cells (in a 4x4 configuration) in a cavity geometry. The first code subdivides the infrared spectrum into several bands and then numerically integrates over the spectrum to provide absorbed heat flux and cell performance predictions (assuming infinite parallel plates). The second utilizes a Monte Carlo Ray-Tracing code that tracks photons, from birth at the radiation source, until they either escape or are absorbed. Absorption depends upon energy dependent reflection probabilities assigned to every geometrical surface within the cavity. The model also has the capability of tallying above and below bandgap absorptions (as a function of location) and can support various radiator temperature profiles. The arrays are fabricated using 0.55 eV InGaAs cells with Si/SiO interference filters for spectral control and at steady state conditions, array efficiency was calculated as the ratio of the load matched power to its absorbed heat flux. Preliminary experimental results are also compared with predictions.

  7. On the uncertainty of individual prediction because of sampling predictors.

    PubMed

    Shen, Changyu; Li, Xiaochun

    2016-05-30

    Prediction of an outcome for a given unit based on prediction models built on a training sample plays a major role in many research areas. The uncertainty of the prediction is predominantly characterized by the subject sampling variation in current practice, where prediction models built on hypothetically re-sampled units yield variable predictions for the same unit of interest. It is almost always true that the predictors used to build prediction models are simply a subset of the entirety of factors related to the outcome. Following the frequentist principle, we can account for the variation because of hypothetically re-sampled predictors used to build the prediction models. This is particularly important in medicine where the prediction has important and sometime life-death consequences on a patient's health status. In this article, we discuss some rationale along this line in the context of medicine. We propose a simple approach to estimate the standard error of the prediction that accounts for the variation because of sampling both subjects and predictors under logistic and Cox regression models. A simulation study is presented to support our argument and demonstrate the performance of our method. The concept and method are applied to a real data set. Copyright © 2015 John Wiley & Sons, Ltd.

  8. Ordinal classification for efficient plant stress prediction in hyperspectral data

    NASA Astrophysics Data System (ADS)

    Behmann, J.; Schmitter, P.; Steinrücken, J.; Plümer, L.

    2014-09-01

    Detection of crop stress from hyperspectral images is of high importance for breeding and precision crop protection. However, the continuous monitoring of stress in phenotyping facilities by hyperspectral imagers produces huge amounts of uninterpreted data. In order to derive a stress description from the images, interpreting algorithms with high prediction performance are required. Based on a static model, the local stress state of each pixel has to be predicted. Due to the low computational complexity, linear models are preferable. In this paper, we focus on drought-induced stress which is represented by discrete stages of ordinal order. We present and compare five methods which are able to derive stress levels from hyperspectral images: One-vs.-one Support Vector Machine (SVM), one-vs.-all SVM, Support Vector Regression (SVR), Support Vector Ordinal Regression (SVORIM) and Linear Ordinal SVM classification. The methods are applied on two data sets - a real world set of drought stress in single barley plants and a simulated data set. It is shown, that Linear Ordinal SVM is a powerful tool for applications which require high prediction performance under limited resources. It is significantly more efficient than the one-vs.-one SVM and even more efficient than the less accurate one-vs.-all SVM. Compared to the very compact SVORIM model, it represents the senescence process much more accurate.

  9. Predicting Prosociality among Urban Adolescents: Individual, Family, and Neighborhood Influences

    ERIC Educational Resources Information Center

    Drinkard, Allyson M.

    2017-01-01

    Prosociality, conceptualized as a willingness to help, to be fair, and to be friendly to others, is essential to the maintenance of a civil society and has been linked with multiple measures of individual well-being. This study examines how individual, family, and neighborhood factors affect adolescents' level of prosociality and tests for…

  10. Predicting Optimal Preference Assessment Methods for Individuals with Developmental Disabilities

    ERIC Educational Resources Information Center

    Thomson, Kendra M.; Czarnecki, Diana; Martin, Toby L.; Yu, C. T.; Martin, Garry L.

    2007-01-01

    The single-stimulus (SS) preference assessment procedure has been described as more appropriate than the paired stimulus (PS) procedure for "lower functioning" individuals, but this guideline's vagueness limits its usefulness. We administered the SS and PS preference assessment procedures with food items to seven individuals with severe…

  11. Predicting Optimal Preference Assessment Methods for Individuals with Developmental Disabilities

    ERIC Educational Resources Information Center

    Thomson, Kendra M.; Czarnecki, Diana; Martin, Toby L.; Yu, C. T.; Martin, Garry L.

    2007-01-01

    The single-stimulus (SS) preference assessment procedure has been described as more appropriate than the paired stimulus (PS) procedure for "lower functioning" individuals, but this guideline's vagueness limits its usefulness. We administered the SS and PS preference assessment procedures with food items to seven individuals with severe…

  12. Machined immersion grating with theoretically predicted diffraction efficiency.

    PubMed

    Ikeda, Yuji; Kobayashi, Naoto; Sarugaku, Yuki; Sukegawa, Takashi; Sugiyama, Shigeru; Kaji, Sayumi; Nakanishi, Kenshi; Kondo, Sohei; Yasui, Chikako; Kataza, Hirokazu; Nakagawa, Takao; Kawakita, Hideyo

    2015-06-01

    An immersion grating composed of a transmissive material with a high refractive index (n>2) is a powerful device for high-resolution spectroscopy in the infrared region. Although the original idea is attributed to Fraunhofer about 200 years ago, an immersion grating with high diffraction efficiency has never been realized due to the difficulty in processing infrared crystals that are mostly brittle. While anisotropic etching is one successful method for fabricating a fine groove pattern on Si crystal, machining is necessary for realizing the ideal groove shape on any kind of infrared crystal. In this paper, we report the realization of the first, to the best of our knowledge, machined immersion grating made of single-crystal CdZnTe with a high diffraction efficiency that is almost identical to that theoretically predicted by rigorous coupled-wave analysis.

  13. Measurement and prediction of Energy Efficient Engine noise

    NASA Technical Reports Server (NTRS)

    Lavin, S. P.; Ho, P. Y.; Chamberlin, R.

    1984-01-01

    The NASA/GE Energy Efficient Engine (E3) static noise levels were measured in an acoustic arena on the Integrated Core and Low Spool Test System. These measured levels were scaled to the appropriate size to power four study aircraft and were projected to flight for evaluation of noise levels relative to FAR36, Stage III limits. As a result of these evaluations, it is predicted that the NASA/GE E3 engine with a wide spacing cut-on blade/vane ratio fan and a forced mixer nozzle can meet FAR36 Stage III limits with sufficient design margin.

  14. Efficient use of accessibility in microRNA target prediction

    PubMed Central

    Marín, Ray M.; Vaníček, Jiří

    2011-01-01

    Considering accessibility of the 3′UTR is believed to increase the precision of microRNA target predictions. We show that, contrary to common belief, ranking by the hybridization energy or by the sum of the opening and hybridization energies, used in currently available algorithms, is not an efficient way to rank predictions. Instead, we describe an algorithm which also considers only the accessible binding sites but which ranks predictions according to over-representation. When compared with experimentally validated and refuted targets in the fruit fly and human, our algorithm shows a remarkable improvement in precision while significantly reducing the computational cost in comparison with other free energy based methods. In the human genome, our algorithm has at least twice higher precision than other methods with their default parameters. In the fruit fly, we find five times more validated targets among the top 500 predictions than other methods with their default parameters. Furthermore, using a common statistical framework we demonstrate explicitly the advantages of using the canonical ensemble instead of using the minimum free energy structure alone. We also find that ‘naïve’ global folding sometimes outperforms the local folding approach. PMID:20805242

  15. Eye blink rate predicts individual differences in pseudoneglect

    PubMed Central

    Slagter, Heleen A.; Davidson, Richard J.; Tomer, Rachel

    2010-01-01

    Most healthy individuals display a subtle spatial attentional bias, exhibiting relative inattention for stimuli on one side of the visual field, a phenomenon known as pseudoneglect. Prior work in animals and patients has implicated dopamine in spatial attention asymmetries. The current study therefore examined - in healthy individuals - the relationship between the attentional bias and spontaneous eye-blink rate (EBR), a putative measure of central dopaminergic function. We found that those individuals, who blinked more often under resting conditions, displayed greater preference for the right side of the visual display in a subsequent attention task. This finding may support the idea that the observed attentional bias in healthy individuals reflects asymmetries in dopaminergic circuits, and corroborates previous findings implicating dopamine in spatial attention. PMID:20036680

  16. Prediction aluminum corrosion inhibitor efficiency using artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Ebrahimi, Sh; Kalhor, E. G.; Nabavi, S. R.; Alamiparvin, L.; Pogaku, R.

    2016-06-01

    In this study, activity of some Schiff bases as aluminum corrosion inhibitor was investigated using artificial neural network (ANN). Hence, corrosion inhibition efficiency of Schiff bases (in any type) were gathered from different references. Then these molecules were drawn and optimized in Hyperchem software. Molecular descriptors generating and descriptors selection were fulfilled by Dragon software and principal component analysis (PCA) method, respectively. These structural descriptors along with environmental descriptors (ambient temperature, time of exposure, pH and the concentration of inhibitor) were used as input variables. Furthermore, aluminum corrosion inhibition efficiency was used as output variable. Experimental data were split into three sets: training set (for model building) and test set (for model validation) and simulation (for general model). Modeling was performed by Multiple linear regression (MLR) methods and artificial neural network (ANN). The results obtained in linear models showed poor correlation between experimental and theoretical data. However nonlinear model presented satisfactory results. Higher correlation coefficient of ANN (R > 0.9) revealed that ANN can be successfully applied for prediction of aluminum corrosion inhibitor efficiency of Schiff bases in different environmental conditions.

  17. Predicting Eighth-Grade Algebra Students with Individualized Education Programs

    ERIC Educational Resources Information Center

    Faulkner, Valerie N.; Crossland, Cathy L.; Stiff, Lee V.

    2013-01-01

    This study investigated the extent to which student performance and teacher perception of student performance affect placement in eighth-grade mathematics classes for students with disabilities. Authors used the Early Childhood Longitudinal Study--Kindergarten dataset to investigate how each of the following factors predicted placement in…

  18. Coherent Motion Sensitivity Predicts Individual Differences in Subtraction

    ERIC Educational Resources Information Center

    Boets, Bart; De Smedt, Bert; Ghesquiere, Pol

    2011-01-01

    Recent findings suggest deficits in coherent motion sensitivity, an index of visual dorsal stream functioning, in children with poor mathematical skills or dyscalculia, a specific learning disability in mathematics. We extended these data using a longitudinal design to unravel whether visual dorsal stream functioning is able to "predict"…

  19. Coherent Motion Sensitivity Predicts Individual Differences in Subtraction

    ERIC Educational Resources Information Center

    Boets, Bart; De Smedt, Bert; Ghesquiere, Pol

    2011-01-01

    Recent findings suggest deficits in coherent motion sensitivity, an index of visual dorsal stream functioning, in children with poor mathematical skills or dyscalculia, a specific learning disability in mathematics. We extended these data using a longitudinal design to unravel whether visual dorsal stream functioning is able to "predict"…

  20. Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton.

    PubMed

    Miller, Robert J; Muller, Erik B; Cole, Bryan; Martin, Tyronne; Nisbet, Roger; Bielmyer-Fraser, Gretchen K; Jarvis, Tayler A; Keller, Arturo A; Cherr, Gary; Lenihan, Hunter S

    2017-02-01

    High Throughput Screening (HTS) using in vitro assessments at the subcellular level has great promise for screening new chemicals and emerging contaminants to identify high-risk candidates, but their linkage to ecological impacts has seldom been evaluated. We tested whether a battery of subcellular HTS tests could be used to accurately predict population-level effects of engineered metal nanoparticles (ENPs) on marine phytoplankton, important primary producers that support oceanic food webs. To overcome well-known difficulties of estimating ecologically meaningful toxicity parameters, we used novel Dynamic Energy Budget and Toxicodynamic (DEBtox) modeling techniques to evaluate impacts of ENPs on population growth rates. Our results show that population growth was negatively impacted by all four ENPs tested, but the HTS tests assessing many cell/physiological functions lacked predictive power at the population level. However, declining photosynthetic efficiency, a traditional physiological endpoint for photoautotrophs, was a good predictor of population level effects in phytoplankton. DEBtox techniques provided robust estimates of EC10 for population growth rates in exponentially growing batch cultures of phytoplankton, and should be widely useful for ecotoxicological testing. Adoption of HTS approaches for ecotoxicological assessment should carefully evaluate the predictive power of specific assays to minimize the risk that effects at higher levels of biological organization may go undetected.

  1. Predicting Children's Depressive Symptoms from Community and Individual Risk Factors

    ERIC Educational Resources Information Center

    Dallaire, Danielle H.; Cole, David A.; Smith, Thomas M.; Ciesla, Jeffrey A.; LaGrange, Beth; Jacquez, Farrah M.; Pineda, Ashley Q.; Truss, Alanna E.; Folmer, Amy S.

    2008-01-01

    Community, demographic, familial, and personal risk factors of childhood depressive symptoms were examined from an ecological theoretical approach using hierarchical linear modeling. Individual-level data were collected from an ethnically diverse (73% African-American) community sample of 197 children and their parents; community-level data were…

  2. Predicting Individual Affect of Health Interventions to Reduce HPV Prevalence

    SciTech Connect

    Corley, Courtney D.; Mihalcea, Rada; Mikler, Armin R.; Sanfilippo, Antonio P.

    2011-04-01

    Recently, human papilloma virus has been implicated to cause several throat and oral cancers and hpv is established to cause most cervical cancers. A human papilloma virus vaccine has been proven successful to reduce infection incidence in FDA clinical trials and it is currently available in the United States. Current intervention policy targets adolescent females for vaccination; however, the expansion of suggested guidelines may extend to other age groups and males as well. This research takes a first step towards automatically predicting personal beliefs, regarding health intervention, on the spread of disease. Using linguistic or statistical approaches, sentiment analysis determines a texts affective content. Self-reported HPV vaccination beliefs published in web and social media are analyzed for affect polarity and leveraged as knowledge inputs to epidemic models. With this in mind, we have developed a discrete-time model to facilitate predicting impact on the reduction of HPV prevalence due to arbitrary age and gender targeted vaccination schemes.

  3. Predicting individual affect of health interventions to reduce HPV prevalence.

    PubMed

    Corley, Courtney D; Mihalcea, Rada; Mikler, Armin R; Sanfilippo, Antonio P

    2011-01-01

    Recently, human papilloma virus (HPV) has been implicated to cause several throat and oral cancers and HPV is established to cause most cervical cancers. A human papilloma virus vaccine has been proven successful to reduce infection incidence in FDA clinical trials, and it is currently available in the USA. Current intervention policy targets adolescent females for vaccination; however, the expansion of suggested guidelines may extend to other age groups and males as well. This research takes a first step toward automatically predicting personal beliefs, regarding health intervention, on the spread of disease. Using linguistic or statistical approaches, sentiment analysis determines a text's affective content. Self-reported HPV vaccination beliefs published in web and social media are analyzed for affect polarity and leveraged as knowledge inputs to epidemic models. With this in mind, we have developed a discrete-time model to facilitate predicting impact on the reduction of HPV prevalence due to arbitrary age- and gender-targeted vaccination schemes.

  4. Individual differences in individualism and collectivism predict ratings of virtual cities' liveability and environmental quality.

    PubMed

    Rubin, Mark; Morrison, Tessa

    2014-01-01

    The present research investigated individual differences in individualism and collectivism as predictors of people's reactions to cities. Psychology undergraduate students (N = 148) took virtual guided tours around historical cities. They then evaluated the cities' liveability and environmental quality and completed measures of individualism and collectivism. Mediation analyses showed that people who scored high in self-responsibility (individualism) rated the cities as more liveable because they perceived them to be richer and better resourced. In contrast, people who scored high in collectivism rated the cities as having a better environmental quality because they perceived them to (1) provide a greater potential for community and social life and (2) allow people to express themselves. These results indicate that people's evaluations of virtual cities are based on the degree to which certain aspects of the cities are perceived to be consistent with individualist and collectivist values.

  5. Use of Demographics to Predict High Risk Individuals for Suicide

    DTIC Science & Technology

    2013-06-01

    strategies that will save more lives (Lyle, 2013). DoD spokewoman, Cynthia O. Smith, said “We are deeply concerned about suicide in the military...assesses an individual’s perceived stress and was designed to measure “the degree to which individuals appraise situations in their lives as...personal lives (18.9%). The most frequently indicated stressors for both men and women were being away from family (16.6%), deployment (13.4%), and

  6. Energy-efficient container handling using hybrid model predictive control

    NASA Astrophysics Data System (ADS)

    Xin, Jianbin; Negenborn, Rudy R.; Lodewijks, Gabriel

    2015-11-01

    The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of three key interacting machines for carrying out the so-called bay handling task, involving transporting containers between a vessel and the stacking area in an automated container terminal. The behaviours of the interacting machines are modelled as a collection of interconnected hybrid systems. Hybrid model predictive control (MPC) is proposed to achieve optimal performance, balancing the handling capacity and energy consumption. The underlying control problem is hereby formulated as a mixed-integer linear programming problem. Simulation studies illustrate that a higher penalty on energy consumption indeed leads to improved sustainability using less energy. Moreover, simulations illustrate how the proposed energy-efficient hybrid MPC controller performs under different types of uncertainties.

  7. Socioeconomic gradients predict individual differences in neurocognitive abilities.

    PubMed

    Noble, Kimberly G; McCandliss, Bruce D; Farah, Martha J

    2007-07-01

    Socioeconomic status (SES) is associated with childhood cognitive achievement. In previous research we found that this association shows neural specificity; specifically we found that groups of low and middle SES children differed disproportionately in perisylvian/language and prefrontal/executive abilities relative to other neurocognitive abilities. Here we address several new questions: To what extent does this disparity between groups reflect a gradient of SES-related individual differences in neurocognitive development, as opposed to a more categorical difference? What other neurocognitive systems differ across individuals as a function of SES? Does linguistic ability mediate SES differences in other systems? And how do specific prefrontal/executive subsystems vary with SES? One hundred and fifty healthy, socioeconomically diverse first-graders were administered tasks tapping language, visuospatial skills, memory, working memory, cognitive control, and reward processing. SES explained over 30% of the variance in language, and a smaller but highly significant portion of the variance in most other systems. Statistically mediating factors and possible interventional approaches are discussed.

  8. Individual differences predict low prevalence visual search performance.

    PubMed

    Peltier, Chad; Becker, Mark W

    2017-01-01

    Critical real-world visual search tasks such as radiology and baggage screening rely on the detection of rare targets. When targets are rare, observers search for a relatively short amount of time and have a high miss rate, a pattern of results known as the low prevalence effect. Attempts to improve the search for rare targets have been unsuccessful or resulted in an increase in detections at the price of more false alarms. As an alternative to improving visual search performance through experimental manipulations, an individual differences approach found that those with higher working memory capacity were better at finding rare targets. We build on the individual differences approach and assess 141 observers' visual working memory capacity (vWMC), vigilance, attentional control, big five personality traits, and performance in both high and low prevalence search tasks. vWMC, vigilance, attentional control, high prevalence visual search performance, and level of introversion were all significant predictors of low prevalence search accuracy, and together account for more than 50% of the variance in search performance. With the exception of vigilance, these factors are also significant predictors of reaction time; better performance was associated with longer reaction times, suggesting these factors identify observers who maintain relatively high quitting thresholds, even with low target prevalence. Our results suggest that a quick and easy-to-administer battery of tasks can identify observers who are likely to perform well in low prevalence search tasks, and these predictor variables are associated with higher quitting thresholds, leading to higher accuracy.

  9. Individual differences in nonverbal number skills predict math anxiety.

    PubMed

    Lindskog, Marcus; Winman, Anders; Poom, Leo

    2017-02-01

    Math anxiety (MA) involves negative affect and tension when solving mathematical problems, with potentially life-long consequences. MA has been hypothesized to be a consequence of negative learning experiences and cognitive predispositions. Recent research indicates genetic and neurophysiological links, suggesting that MA stems from a basic level deficiency in symbolic numerical processing. However, the contribution of evolutionary ancient purely nonverbal processes is not fully understood. Here we show that the roots of MA may go beyond symbolic numbers. We demonstrate that MA is correlated with precision of the Approximate Number System (ANS). Individuals high in MA have poorer ANS functioning than those low in MA. This correlation remains significant when controlling for other forms of anxiety and for cognitive variables. We show that MA mediates the documented correlation between ANS precision and math performance, both with ANS and with math performance as independent variable in the mediation model. In light of our results, we discuss the possibility that MA has deep roots, stemming from a non-verbal number processing deficiency. The findings provide new evidence advancing the theoretical understanding of the developmental etiology of MA.

  10. Baseline BOLD correlation predicts individuals' stimulus-evoked BOLD responses.

    PubMed

    Liu, Xiao; Zhu, Xiao-Hong; Chen, Wei

    2011-02-01

    To investigate whether individuals' ongoing neuronal activity at resting state can affect their response to brain stimulation, fMRI BOLD signals were imaged from the human visual cortex of fifteen healthy subjects in the absence and presence of visual stimulation. It was found that the temporal correlation strength but not amplitude of baseline BOLD signal fluctuations acquired under the eyes-fixed condition is positively correlated with the amplitude of stimulus-evoked BOLD responses across subjects. Moreover, the spatiotemporal correlations of baseline BOLD signals imply a coherent network covering the visual system, which is topographically indistinguishable from the "resting-state visual network" observed under the eyes-closed condition. The overall findings suggest that the synchronization of ongoing brain activity plays an important role in determining stimulus-evoked brain activity even at an early stage of the sensory system. The tight relationship between baseline BOLD correlation and stimulus-evoked BOLD amplitude provides an essential basis for understanding and interpreting the large inter-subject BOLD variability commonly observed in numerous fMRI studies and potentially for improving group fMRI analysis. This study highlights the importance to integrate the information from both resting-state coherent networks and task-evoked neural responses for a better understanding of how the brain functions.

  11. Individual variability in behavioral flexibility predicts sign-tracking tendency

    PubMed Central

    Nasser, Helen M.; Chen, Yu-Wei; Fiscella, Kimberly; Calu, Donna J.

    2015-01-01

    Sign-tracking rats show heightened sensitivity to food- and drug-associated cues, which serve as strong incentives for driving reward seeking. We hypothesized that this enhanced incentive drive is accompanied by an inflexibility when incentive value changes. To examine this we tested rats in Pavlovian outcome devaluation or second-order conditioning prior to the assessment of sign-tracking tendency. To assess behavioral flexibility we trained rats to associate a light with a food outcome. After the food was devalued by pairing with illness, we measured conditioned responding (CR) to the light during an outcome devaluation probe test. The level of CR during outcome devaluation probe test correlated with the rats' subsequent tracking tendency, with sign-tracking rats failing to suppress CR to the light after outcome devaluation. To assess Pavlovian incentive learning, we trained rats on first-order (CS+, CS−) and second-order (SOCS+, SOCS−) discriminations. After second-order conditioning, we measured CR to the second-order cues during a probe test. Second-order conditioning was observed across all rats regardless of tracking tendency. The behavioral inflexibility of sign-trackers has potential relevance for understanding individual variation in vulnerability to drug addiction. PMID:26578917

  12. Predictive Models of Alcohol Use Based on Attitudes and Individual Values

    ERIC Educational Resources Information Center

    Del Castillo Rodríguez, José A. García; López-Sánchez, Carmen; Soler, M. Carmen Quiles; Del Castillo-López, Álvaro García; Pertusa, Mónica Gázquez; Campos, Juan Carlos Marzo; Inglés, Cándido J.

    2013-01-01

    Two predictive models are developed in this article: the first is designed to predict people' attitudes to alcoholic drinks, while the second sets out to predict the use of alcohol in relation to selected individual values. University students (N = 1,500) were recruited through stratified sampling based on sex and academic discipline. The…

  13. Predictive Models of Alcohol Use Based on Attitudes and Individual Values

    ERIC Educational Resources Information Center

    Del Castillo Rodríguez, José A. García; López-Sánchez, Carmen; Soler, M. Carmen Quiles; Del Castillo-López, Álvaro García; Pertusa, Mónica Gázquez; Campos, Juan Carlos Marzo; Inglés, Cándido J.

    2013-01-01

    Two predictive models are developed in this article: the first is designed to predict people' attitudes to alcoholic drinks, while the second sets out to predict the use of alcohol in relation to selected individual values. University students (N = 1,500) were recruited through stratified sampling based on sex and academic discipline. The…

  14. Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?

    ERIC Educational Resources Information Center

    Mozer, Michael C.; Pashler, Harold; Homaei, Hadjar

    2008-01-01

    Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect…

  15. Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?

    ERIC Educational Resources Information Center

    Mozer, Michael C.; Pashler, Harold; Homaei, Hadjar

    2008-01-01

    Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect…

  16. Prediction of Cardiovascular Risk Using Framingham, ASSIGN and QRISK2: How Well Do They Predict Individual Rather than Population Risk?

    PubMed Central

    van Staa, Tjeerd-Pieter; Gulliford, Martin; Ng, Edmond S.-W.; Goldacre, Ben; Smeeth, Liam

    2014-01-01

    Background The objective of this study was to evaluate the performance of risk scores (Framingham, Assign and QRISK2) in predicting high cardiovascular disease (CVD) risk in individuals rather than populations. Methods and findings This study included 1.8 million persons without CVD and prior statin prescribing using the Clinical Practice Research Datalink. This contains electronic medical records of the general population registered with a UK general practice. Individual CVD risks were estimated using competing risk regression models. Individual differences in the 10-year CVD risks as predicted by risk scores and competing risk models were estimated; the population was divided into 20 subgroups based on predicted risk. CVD outcomes occurred in 69,870 persons. In the subgroup with lowest risks, risk predictions by QRISK2 were similar to individual risks predicted using our competing risk model (99.9% of people had differences of less than 2%); in the subgroup with highest risks, risk predictions varied greatly (only 13.3% of people had differences of less than 2%). Larger deviations between QRISK2 and our individual predicted risks occurred with calendar year, different ethnicities, diabetes mellitus and number of records for medical events in the electronic health records in the year before the index date. A QRISK2 estimate of low 10-year CVD risk (<15%) was confirmed by Framingham, ASSIGN and our individual predicted risks in 89.8% while an estimate of high 10-year CVD risk (≥20%) was confirmed in only 48.6% of people. The majority of cases occurred in people who had predicted 10-year CVD risk of less than 20%. Conclusions Application of existing CVD risk scores may result in considerable misclassification of high risk status. Current practice to use a constant threshold level for intervention for all patients, together with the use of different scoring methods, may inadvertently create an arbitrary classification of high CVD risk. PMID:25271417

  17. Automation to improve efficiency of field expedient injury prediction screening.

    PubMed

    Teyhen, Deydre S; Shaffer, Scott W; Umlauf, Jon A; Akerman, Raymond J; Canada, John B; Butler, Robert J; Goffar, Stephen L; Walker, Michael J; Kiesel, Kyle B; Plisky, Phillip J

    2012-07-01

    Musculoskeletal injuries are a primary source of disability in the U.S. Military. Physical training and sports-related activities account for up to 90% of all injuries, and 80% of these injuries are considered overuse in nature. As a result, there is a need to develop an evidence-based musculoskeletal screen that can assist with injury prevention. The purpose of this study was to assess the capability of an automated system to improve the efficiency of field expedient tests that may help predict injury risk and provide corrective strategies for deficits identified. The field expedient tests include survey questions and measures of movement quality, balance, trunk stability, power, mobility, and foot structure and mobility. Data entry for these tests was automated using handheld computers, barcode scanning, and netbook computers. An automated algorithm for injury risk stratification and mitigation techniques was run on a server computer. Without automation support, subjects were assessed in 84.5 ± 9.1 minutes per subject compared with 66.8 ± 6.1 minutes per subject with automation and 47.1 ± 5.2 minutes per subject with automation and process improvement measures (p < 0.001). The average time to manually enter the data was 22.2 ± 7.4 minutes per subject. An additional 11.5 ± 2.5 minutes per subject was required to manually assign an intervention strategy. Automation of this injury prevention screening protocol using handheld devices and netbook computers allowed for real-time data entry and enhanced the efficiency of injury screening, risk stratification, and prescription of a risk mitigation strategy.

  18. Individual but not fragile: individual differences in task control predict Stroop facilitation.

    PubMed

    Kalanthroff, E; Henik, A

    2013-06-01

    The Stroop effect is composed of interference and facilitation effects. The facilitation is less stable and thus many times is referred to as a "fragile effect". Here we suggest the facilitation effect is highly vulnerable to individual differences in control over the task conflict (between relevant color naming and irrelevant word reading in the Stroop task). We replicated previous findings of a significant correlation between stop-signal reaction time (SSRT) and Stroop interference, and also found a significant correlation between SSRT and the Stroop facilitation effect-participants with low inhibitory control (i.e., long SSRT) had no facilitation effect or even a reversed one. These results shed new light on the "fragile" facilitation effect and highlight the necessity of awareness of task conflict, especially in the Stroop task. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. RD-optimized competition scheme for efficient motion prediction

    NASA Astrophysics Data System (ADS)

    Jung, J.; Laroche, G.; Pesquet, B.

    2007-01-01

    H.264/MPEG4-AVC is the latest video codec provided by the Joint Video Team, gathering ITU-T and ISO/IEC experts. Technically there are no drastic changes compared to its predecessors H.263 and MPEG-4 part 2. It however significantly reduces the bitrate and seems to be progressively adopted by the market. The gain mainly results from the addition of efficient motion compensation tools, variable block sizes, multiple reference frames, 1/4-pel motion accuracy and powerful Skip and Direct modes. A close study of the bits repartition in the bitstream reveals that motion information can represent up to 40% of the total bitstream. As a consequence reduction of motion cost is a priority for future enhancements. This paper proposes a competition-based scheme for the prediction of the motion. It impacts the selection of the motion vectors, based on a modified rate-distortion criterion, for the Inter modes and for the Skip mode. Combined spatial and temporal predictors take benefit of temporal redundancies, where the spatial median usually fails. An average 7% bitrate saving compared to a standard H.264/MPEG4-AVC codec is reported. In addition, on the fly adaptation of the set of predictors is proposed and preliminary results are provided.

  20. Cognitive trait anxiety, situational stress, and mental effort predict shifting efficiency: Implications for attentional control theory.

    PubMed

    Edwards, Elizabeth J; Edwards, Mark S; Lyvers, Michael

    2015-06-01

    Attentional control theory (ACT) predicts that trait anxiety and situational stress interact to impair performance on tasks that involve attentional shifting. The theory suggests that anxious individuals recruit additional effort to prevent shortfalls in performance effectiveness (accuracy), with deficits becoming evident in processing efficiency (the relationship between accuracy and time taken to perform the task). These assumptions, however, have not been systematically tested. The relationship between cognitive trait anxiety, situational stress, and mental effort in a shifting task (Wisconsin Card Sorting Task) was investigated in 90 participants. Cognitive trait anxiety was operationalized using questionnaire scores, situational stress was manipulated through ego threat instructions, and mental effort was measured using a visual analogue scale. Dependent variables were performance effectiveness (an inverse proportion of perseverative errors) and processing efficiency (an inverse proportion of perseverative errors divided by response time on perseverative error trials). The predictors were not associated with performance effectiveness; however, we observed a significant 3-way interaction on processing efficiency. At higher mental effort (+1 SD), higher cognitive trait anxiety was associated with poorer efficiency independently of situational stress, whereas at lower effort (-1 SD), this relationship was highly significant and most pronounced for those in the high-stress condition. These results are important because they provide the first systematic test of the relationship between trait anxiety, situational stress, and mental effort on shifting performance. The data are also consistent with the notion that effort moderates the relationship between anxiety and shifting efficiency, but not effectiveness.

  1. Predicting the peak growth velocity in the individual child: validation of a new growth model.

    PubMed

    Busscher, Iris; Kingma, Idsart; de Bruin, Rob; Wapstra, Frits Hein; Verkerke, Gijsvertus J; Veldhuizen, Albert G

    2012-01-01

    Predicting the peak growth velocity in an individual patient with adolescent idiopathic scoliosis is essential or determining the prognosis of the disorder and timing of the (surgical) treatment. Until the present time, no accurate method has been found to predict the timing and magnitude of the pubertal growth spurt in the individual child. A mathematical model was developed in which the partial individual growth velocity curve was linked to the generic growth velocity curve. The generic curve was shifted and stretched or shrunk, both along the age axis and the height velocity axis. The individual age and magnitude of the PGV were obtained from the new predicted complete growth velocity curve. Predictions were made using 2, 1.5, 1 and 0.5 years of the available longitudinal data of the individual child, starting at different ages. The predicted values of 210 boys and 162 girls were compared to the child's own original values of the PGV. The individual differences were compared to differences obtained when using the generic growth velocity curve as a standard. Using 2 years of data as input for the model, all predictions of the age of the PGV in boys and girls were significantly better in comparison to using the generic values. Using only 0.5 years of data as input, the predictions with a starting age from 13 to 15.5 years in boys and from 9.5 to 14.5 years in girls were significantly better. Similar results were found for the predictions of the magnitude of the PGV. This model showed highly accurate results in predicting the individual age and magnitude of the PGV, which can be used in the treatment of patients with adolescent idiopathic scoliosis.

  2. Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates

    PubMed Central

    Chambert, Thierry; Rotella, Jay J; Higgs, Megan D

    2014-01-01

    The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in

  3. Can the theory of planned behaviour predict the physical activity behaviour of individuals?

    PubMed

    Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual.

  4. Striatal structure and function predict individual biases in learning to avoid pain.

    PubMed

    Eldar, Eran; Hauser, Tobias U; Dayan, Peter; Dolan, Raymond J

    2016-04-26

    Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants' predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior.

  5. Striatal structure and function predict individual biases in learning to avoid pain

    PubMed Central

    Eldar, Eran; Hauser, Tobias U.; Dayan, Peter; Dolan, Raymond J.

    2016-01-01

    Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants’ predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior. PMID:27071092

  6. Driving Green: Toward the Prediction and Influence of Efficient Driving Behavior

    NASA Astrophysics Data System (ADS)

    Newsome, William D.

    Sub-optimal efficiency in activities involving the consumption of fossil fuels, such as driving, contribute to a miscellany of negative environmental, political, economic and social externalities. Demonstrations of the effectiveness of feedback interventions can be found in countless organizational settings, as can demonstrations of individual differences in sensitivity to feedback interventions. Mechanisms providing feedback to drivers about fuel economy are becoming standard equipment in most new vehicles, but vary considerably in their constitution. A keystone of Radical Behaviorism is the acknowledgement that verbal behavior appears to play a role in mediating apparent susceptibility to influence by contingencies of varying delay. In the current study, samples of verbal behavior (rules) were collected in the context of a feedback intervention to improve driving efficiency. In an analysis of differences in individual responsiveness to the feedback intervention, the rate of novel rules per week generated by drivers is revealed to account for a substantial proportion of the variability in relative efficiency gains across participants. The predictive utility of conceptual tools, such as the basic distinction among contingency-shaped and rule governed behavior, the elaboration of direct-acting and indirect-acting contingencies, and the psychological flexibility model, is bolstered by these findings.

  7. Introducing efficiency into the analysis of individual lifetime performance variability: a key to assess herd management.

    PubMed

    Puillet, L; Martin, O; Sauvant, D; Tichit, M

    2011-01-01

    Lifetime performance variability is a powerful tool for evaluating herd management. Although efficiency is a key aspect of performance, it has not been integrated into existing studies on the variability of lifetime performance. The goal of the present article is to analyse the effects of various herd management options on the variability of lifetime performance by integrating criteria relative to feed efficiency. A herd model developed for dairy goat systems was used in three virtual experiments to test the effects of the diet energy level, the segmentation of the feeding plan and the mean production potential of the herd on the variability of lifetime performance. Principal component analysis showed that the variability of lifetime performance was structured around the first axis related to longevity and production and the second related to the variables used in feed efficiency calculation. The intra-management variability was expressed on the first axis (longevity and production), whereas the inter-management variability was expressed on the second axis (feed efficiency) and was mainly influenced by the combination of the diet energy level and the mean production potential. Similar feed efficiencies were attained with different management options. Still, such combinations relied on different biological bases and, at the level of the individual, contrasting results were observed in the relationship between the obtained pattern of performance (in response to diet energy) and the reference pattern of performance (defined by the production potential). Indeed, our results showed that over-feeding interacted with the feeding plan segmentation: a high level of feeding plan segmentation generated a low proportion of individuals at equilibrium with their production potential, whereas a single ration generated a larger proportion. At the herd level, the diet energy level and the herd production potential had marked effects on production and efficiency due to dilution of

  8. Individualized relapse prediction: personality measures and striatal and insular activity during reward-processing robustly predict relapse*

    PubMed Central

    Gowin, Joshua L.; Ball, Tali M.; Wittmann, Marc; Tapert, Susan F.; Paulus, Martin P.

    2015-01-01

    Background Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. Methods 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. Results 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. Conclusions These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders. PMID:25977206

  9. Brain ERP components predict which individuals progress to Alzheimer’s disease and which do not

    PubMed Central

    Chapman, Robert M.; McCrary, John W.; Gardner, Margaret N.; Sandoval, Tiffany C.; Guillily, Maria D.; Reilly, Lindsey A.; DeGrush, Elizabeth

    2009-01-01

    Predicting which individuals will progress to Alzheimer’s disease (AD) is important in both clinical and research settings. We used brain Event-Related Potentials (ERPs) obtained in a perceptual/cognitive paradigm with various processing demands to predict which individual Mild Cognitive Impairment (MCI) subjects will develop AD versus which will not. ERP components, including P3, memory “storage” component, and other earlier and later components, were identified and measured by Principal Components Analysis. When measured for particular task conditions, a weighted set of eight ERP component_conditions performed well in discriminant analysis at predicting later AD progression with good accuracy, sensitivity, and specificity. The predictions for most individuals (79%) had high posterior probabilities and were accurate (88%). This method, supported by a cross-validation where the prediction accuracy was 70–78%, features the posterior probability for each individual as a method of determining the likelihood of progression to AD. Empirically obtained prediction accuracies rose to 94% when the computed posterior probabilities for individuals were 0.90 or higher (which was found for 40% of our MCI sample). PMID:20005599

  10. Task-free MRI predicts individual differences in brain activity during task performance.

    PubMed

    Tavor, I; Parker Jones, O; Mars, R B; Smith, S M; Behrens, T E; Jbabdi, S

    2016-04-08

    When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

  11. Efficient Reduction and Analysis of Model Predictive Error

    NASA Astrophysics Data System (ADS)

    Doherty, J.

    2006-12-01

    Most groundwater models are calibrated against historical measurements of head and other system states before being used to make predictions in a real-world context. Through the calibration process, parameter values are estimated or refined such that the model is able to reproduce historical behaviour of the system at pertinent observation points reasonably well. Predictions made by the model are deemed to have greater integrity because of this. Unfortunately, predictive integrity is not as easy to achieve as many groundwater practitioners would like to think. The level of parameterisation detail estimable through the calibration process (especially where estimation takes place on the basis of heads alone) is strictly limited, even where full use is made of modern mathematical regularisation techniques such as those encapsulated in the PEST calibration package. (Use of these mechanisms allows more information to be extracted from a calibration dataset than is possible using simpler regularisation devices such as zones of piecewise constancy.) Where a prediction depends on aspects of parameterisation detail that are simply not inferable through the calibration process (which is often the case for predictions related to contaminant movement, and/or many aspects of groundwater/surface water interaction), then that prediction may be just as much in error as it would have been if the model had not been calibrated at all. Model predictive error arises from two sources. These are (a) the presence of measurement noise within the calibration dataset through which linear combinations of parameters spanning the "calibration solution space" are inferred, and (b) the sensitivity of the prediction to members of the "calibration null space" spanned by linear combinations of parameters which are not inferable through the calibration process. The magnitude of the former contribution depends on the level of measurement noise. The magnitude of the latter contribution (which often

  12. Anytime Prediction: Efficient Ensemble Methods for Any Computational Budget

    DTIC Science & Technology

    2014-01-21

    graphical model. For example, the message passing behavior of Loopy Belief Propagation [ Pearl , 1988] can be described by this iterative decoding approach...message passing approach commonly used for graphical model prediction [ Pearl , 1988]. 129 130 CHAPTER 7. ANYTIME STRUCTURED PREDICTION As we did before...regression. Annals of Statistics, 28:681–712, 2000. S. Karayev, T. Baumgartner, M. Fritz , and T. Darrell. Timely object recognition. In NIPS, 2012. S

  13. Assessment of the genomic prediction accuracy for feed efficiency traits in meat-type chickens

    PubMed Central

    Wang, Jie; Ma, Jie; Shu, Dingming; Lund, Mogens Sandø; Su, Guosheng; Qu, Hao

    2017-01-01

    Feed represents the major cost of chicken production. Selection for improving feed utilization is a feasible way to reduce feed cost and greenhouse gas emissions. The objectives of this study were to investigate the efficiency of genomic prediction for feed conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG) and average daily feed intake (ADFI) and to assess the impact of selection for feed efficiency traits FCR and RFI on eviscerating percentage (EP), breast muscle percentage (BMP) and leg muscle percentage (LMP) in meat-type chickens. Genomic prediction was assessed using a 4-fold cross-validation for two validation scenarios. The first scenario was a random family sampling validation (CVF), and the second scenario was a random individual sampling validation (CVR). Variance components were estimated based on the genomic relationship built with single nucleotide polymorphism markers. Genomic estimated breeding values (GEBV) were predicted using a genomic best linear unbiased prediction model. The accuracies of GEBV were evaluated in two ways: the correlation between GEBV and corrected phenotypic value divided by the square root of heritability, i.e., the correlation-based accuracy, and model-based theoretical accuracy. Breeding values were also predicted using a conventional pedigree-based best linear unbiased prediction model in order to compare accuracies of genomic and conventional predictions. The heritability estimates of FCR and RFI were 0.29 and 0.50, respectively. The heritability estimates of ADG, ADFI, EP, BMP and LMP ranged from 0.34 to 0.53. In the CVF scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR were slightly higher than those for RFI. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.360, 0.284, 0.574 and 0.520, respectively, and the model-based theoretical accuracies were 0.420, 0.414, 0.401 and 0.382, respectively. In the CVR scenario, the correlation

  14. Assessment of the genomic prediction accuracy for feed efficiency traits in meat-type chickens.

    PubMed

    Liu, Tianfei; Luo, Chenglong; Wang, Jie; Ma, Jie; Shu, Dingming; Lund, Mogens Sandø; Su, Guosheng; Qu, Hao

    2017-01-01

    Feed represents the major cost of chicken production. Selection for improving feed utilization is a feasible way to reduce feed cost and greenhouse gas emissions. The objectives of this study were to investigate the efficiency of genomic prediction for feed conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG) and average daily feed intake (ADFI) and to assess the impact of selection for feed efficiency traits FCR and RFI on eviscerating percentage (EP), breast muscle percentage (BMP) and leg muscle percentage (LMP) in meat-type chickens. Genomic prediction was assessed using a 4-fold cross-validation for two validation scenarios. The first scenario was a random family sampling validation (CVF), and the second scenario was a random individual sampling validation (CVR). Variance components were estimated based on the genomic relationship built with single nucleotide polymorphism markers. Genomic estimated breeding values (GEBV) were predicted using a genomic best linear unbiased prediction model. The accuracies of GEBV were evaluated in two ways: the correlation between GEBV and corrected phenotypic value divided by the square root of heritability, i.e., the correlation-based accuracy, and model-based theoretical accuracy. Breeding values were also predicted using a conventional pedigree-based best linear unbiased prediction model in order to compare accuracies of genomic and conventional predictions. The heritability estimates of FCR and RFI were 0.29 and 0.50, respectively. The heritability estimates of ADG, ADFI, EP, BMP and LMP ranged from 0.34 to 0.53. In the CVF scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR were slightly higher than those for RFI. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.360, 0.284, 0.574 and 0.520, respectively, and the model-based theoretical accuracies were 0.420, 0.414, 0.401 and 0.382, respectively. In the CVR scenario, the correlation

  15. Individualized prediction of lung-function decline in chronic obstructive pulmonary disease

    PubMed Central

    Zafari, Zafar; Sin, Don D.; Postma, Dirkje S.; Löfdahl, Claes-Göran; Vonk, Judith; Bryan, Stirling; Lam, Stephen; Tammemagi, C. Martin; Khakban, Rahman; Man, S.F. Paul; Tashkin, Donald; Wise, Robert A.; Connett, John E.; McManus, Bruce; Ng, Raymond; Hollander, Zsuszanna; Sadatsafavi, Mohsen

    2016-01-01

    Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being −124 to −15 mL/yr for smokers and −83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD. Trial registration: Lung Health Study — ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study — ClinicalTrials.gov, no. NCT00751660 PMID:27486205

  16. Pharmacometabolomics in Endogenous Drugs: A New Approach for Predicting the Individualized Pharmacokinetics of Cholic Acid.

    PubMed

    Zhang, Zhixin; Gu, Hao; Zhao, Huizhen; Liu, Yuehong; Fu, Shuang; Wang, Meiling; Zhou, Wenjuan; Xie, Ziye; Yu, Honghong; Huang, Zhenghai; Gao, Xiaoyan

    2017-09-01

    The evaluation of individual variability in endogenous drugs' metabolism and disposition is a very challenging task. We developed and validated a metabotype to pharmacokinetics (PK) matching approach by taking cholic acid as an example to predict the individualized PK of endogenous drugs. The stable isotope-labeled cholic acid was selected as the substitute analyte of cholic acid to ensure the accurate measurement of blood concentration. First, large-scale metabolite profiling studies were performed on the predose urine samples of 28 rats. Then, to examine the individualized PK of deuterium 4-cholic acid (d4-cholic acid) in these rats, we determined its plasma concentrations and calculated the differential AUC values. Subsequently, we conducted a two-stage partial least-squares analysis in which 31 baseline metabolites were screened initially for predicting the individualized AUC values of d4-cholic acid using the data of predose urine metabolites. Finally, network biology analysis was applied to give the biological interpretation of the individual variances in cholic acid metabolism and disposition, and the result further narrowed the selection of baseline metabolites from 31 to 2 (sarcosine and S-adenosyl-l-homocysteine) for such prediction. Collectively, this pharmacometabolomics research provided a new strategy for predicting individualized PK of endogenous drugs.

  17. Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity

    PubMed Central

    Vo, Loan T. K.; Walther, Dirk B.; Kramer, Arthur F.; Erickson, Kirk I.; Boot, Walter R.; Voss, Michelle W.; Prakash, Ruchika S.; Lee, Hyunkyu; Fabiani, Monica; Gratton, Gabriele; Simons, Daniel J.; Sutton, Bradley P.; Wang, Michelle Y.

    2011-01-01

    Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2*-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2*-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as task-switching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills. PMID:21264257

  18. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    PubMed

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Internalizing and externalizing traits predict changes in sleep efficiency in emerging adulthood: an actigraphy study

    PubMed Central

    Yaugher, Ashley C.; Alexander, Gerianne M.

    2015-01-01

    Research on psychopathology and experimental studies of sleep restriction support a relationship between sleep disruption and both internalizing and externalizing disorders. The objective of the current study was to extend this research by examining sleep, impulsivity, antisocial personality traits, and internalizing traits in a university sample. Three hundred and eighty six individuals (161 males) between the ages of 18 and 27 years (M = 18.59, SD = 0.98) wore actigraphs for 7 days and completed established measures of disorder-linked personality traits and sleep quality (i.e., Personality Assessment Inventory (PAI), Triarchic Psychopathy Measure, Barratt Impulsiveness Scale-11, and the Pittsburgh Sleep Quality Index). As expected, sleep measures and questionnaire scores fell within the normal range of values and sex differences in sleep and personality were consistent with previous research results. Similar to findings in predominantly male forensic psychiatric settings, higher levels of impulsivity predicted poorer subjective sleep quality in both women and men. Consistent with well-established associations between depression and sleep, higher levels of depression in both sexes predicted poorer subjective sleep quality. Bidirectional analyses showed that better sleep efficiency decreases depression. Finally, moderation analyses showed that gender does have a primary role in sleep efficiency and marginal effects were found. The observed relations between sleep and personality traits in a typical university sample add to converging evidence of the relationship between sleep and psychopathology and may inform our understanding of the development of psychopathology in young adulthood. PMID:26500575

  20. Predicting high harmonic ion cyclotron heating efficiency in Tokamak plasmas.

    PubMed

    Green, D L; Berry, L A; Chen, G; Ryan, P M; Canik, J M; Jaeger, E F

    2011-09-30

    Observations of improved radio frequency (rf) heating efficiency in ITER relevant high-confinement (H-)mode plasmas on the National Spherical Tokamak Experiment are investigated by whole-device linear simulation. The steady-state rf electric field is calculated for various antenna spectra and the results examined for characteristics that correlate with observations of improved or reduced rf heating efficiency. We find that launching toroidal wave numbers that give fast-wave propagation in the scrape-off plasma excites large amplitude (∼kV m(-1)) coaxial standing modes between the confined plasma density pedestal and conducting vessel wall. Qualitative comparison with measurements of the stored plasma energy suggests that these modes are a probable cause of degraded heating efficiency.

  1. An efficient link prediction index for complex military organization

    NASA Astrophysics Data System (ADS)

    Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

    2017-03-01

    Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

  2. Identification of individuals by trait prediction using whole-genome sequencing data.

    PubMed

    Lippert, Christoph; Sabatini, Riccardo; Maher, M Cyrus; Kang, Eun Yong; Lee, Seunghak; Arikan, Okan; Harley, Alena; Bernal, Axel; Garst, Peter; Lavrenko, Victor; Yocum, Ken; Wong, Theodore; Zhu, Mingfu; Yang, Wen-Yun; Chang, Chris; Lu, Tim; Lee, Charlie W H; Hicks, Barry; Ramakrishnan, Smriti; Tang, Haibao; Xie, Chao; Piper, Jason; Brewerton, Suzanne; Turpaz, Yaron; Telenti, Amalio; Roby, Rhonda K; Och, Franz J; Venter, J Craig

    2017-09-05

    Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.

  3. Efficient prediction strategies for disturbance compensation in stochastic MPC

    NASA Astrophysics Data System (ADS)

    Kouvaritakis, Basil; Cannon, Mark; Muñoz-Carpintero, Diego

    2013-07-01

    The optimisation of predicted control policies in model predictive control (MPC) enables the use of information on uncertainty that, though not available at current time, will be so at a future point on the prediction horizon. Optimisation over feedback laws is however prohibitively computationally expensive. The so-called affine-in-the-disturbance strategies provide a compromise and this article considers the use of disturbance compensation in the context of stochastic MPC. Unlike the earlier approaches, compensation here is applied over the entire prediction horizon (extending to infinity) thereby leading to a significant constraint relaxation which makes more control authority available for the optimisation of performance. In addition, our compensation has a striped lower triangular dependence on the uncertainty on account of which the relevant gains can be obtained sequentially, thereby reducing computational complexity. Further reduction in computation is achieved by performing this computation offline. Simulation results show that this reduction can be gained at a negligible cost in terms of closed-loop performance.

  4. Anthelmintic efficiency of doramectin, fenbendazole, and nitroxynil, in combination or individually, in sheep worm control.

    PubMed

    Holsback, Luciane; Luppi, Pedro Alex Ramsey; Silva, Camile Sanches; Negrão, Gustavo Kremer; Conde, Gabriel; Gabriel, Hugo Vinícius; Balestrieri, João Vitor; Tomazella, Lucas

    2016-01-01

    The anthelmintic efficiency of doramectin, fenbendazole, and nitroxynil, used individually or in combination, was determined by the Fecal Egg Count Reduction (FECR) test and cultivation of larvae of anthelminthic-treated sheep grouped as follows: G1 (doramectin), G2 (fenbendazole), G3 (nitroxynil), G4 (doramectin + fenbendazole), G5 (doramectin + nitroxynil), G6 (fenbendazole + nitroxynil), G7 (doramectin + nitroxynil + fenbendazole), G8 (untreated). In addition to individually used doramectin and fenbendazole, the helminths were also resistant to the combination of doramectin + fenbendazole; nitroxynil + fenbendazole; and doramectin + nitroxynil + fenbendazole, with their FECR rates ranging from 62-83%. The helminths showed possible nitroxynil-resistance, but had low resistance when the drug was administered in combination with doramectin. The evaluation of individual helminth species revealed that fenbendazole was fully effective against Cooperia; doramectin (G1), moderately effective against Haemonchus and insufficiently active against Cooperia; nitroxynil, effective against Haemonchus and insufficiently active against Cooperia. It was concluded from the results that herd nematodes are resistant to doramectin, fenbendazole, and nitroxynil, and that the combined use of the drugs not only fails to significantly improve the anthelmintic efficiency against Haemonchus and Cooperia, but is also cost-ineffective.

  5. Clinical Neurochemistry of Subarachnoid Hemorrhage: Toward Predicting Individual Outcomes via Biomarkers of Brain Energy Metabolism.

    PubMed

    Tholance, Yannick; Barcelos, Gleicy; Dailler, Frederic; Perret-Liaudet, Armand; Renaud, Bernard

    2015-12-16

    The functional outcome of patients with subarachnoid hemorrhage is difficult to predict at the individual level. The monitoring of brain energy metabolism has proven to be useful in improving the pathophysiological understanding of subarachnoid hemorrhage. Nonetheless, brain energy monitoring has not yet clearly been included in official guidelines for the management of subarachnoid hemorrhage patients, likely because previous studies compared only biological data between two groups of patients (unfavorable vs favorable outcomes) and did not determine decision thresholds that could be useful in clinical practice. Therefore, this Viewpoint discusses recent findings suggesting that monitoring biomarkers of brain energy metabolism at the level of individuals can be used to predict the outcomes of subarachnoid hemorrhage patients. Indeed, by taking into account specific neurochemical patterns obtained by local or global monitoring of brain energy metabolism, it may become possible to predict routinely, and with sufficient sensitivity and specificity, the individual outcomes of subarachnoid hemorrhage patients. Moreover, combining both local and global monitoring improves the overall performance of individual outcome prediction. Such a combined neurochemical monitoring approach may become, after prospective clinical validation, an important component in the management of subarachnoid hemorrhage patients to adapt individualized therapeutic interventions.

  6. Individualized conditioning regimes in cord blood transplantation: Towards improved and predictable safety and efficacy.

    PubMed

    Admiraal, R; Boelens, J J

    2016-06-01

    The conditioning regimen used in cord blood transplantation (CBT) may significantly impact the outcomes. Variable pharmacokinetics (PK) of drugs used may further influence outcome. Individualized dosing takes inter-patient differences in PK into account, tailoring drug dose for each individual patient in order to reach optimal exposure. Dose individualization may result in a better predictable regimen in terms of safety and efficacy, including timely T cell reconstitution, which may result in improved survival chances. Conditioning regimens used in CBT varies significantly between and within centres. For busulfan, individualized dosing with therapeutic drug monitoring has resulted in better outcomes. Anti-thymocyte globulin (ATG), used to prevent rejection and GvHD, significantly hampers early T-cell reconstitution (IR). Timely IR is crucial in preventing viral reactivations and relapse. By individudalizing ATG, IR is better predicted and may prevent morbidity and mortality. Individualization of agents used in the conditioning regimen in CBT has proven its added value. Further fine-tuning, including new drugs and/or comprehensive models for all drugs, may result in better predictable conditioning regimens. A predictable conditioning regimen is also of interest/importance when studying adjuvant therapies, including immunotherapies (e.g. cellular vaccines or engineered T-cell) in a harmonized clinical trial design setting.

  7. Prediction of daily sea surface temperature using efficient neural networks

    NASA Astrophysics Data System (ADS)

    Patil, Kalpesh; Deo, Makaranad Chintamani

    2017-02-01

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

  8. Prediction of daily sea surface temperature using efficient neural networks

    NASA Astrophysics Data System (ADS)

    Patil, Kalpesh; Deo, Makaranad Chintamani

    2017-04-01

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

  9. Genome-Wide Prediction of Traits with Different Genetic Architecture Through Efficient Variable Selection

    PubMed Central

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-01-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits. PMID:23934883

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

    PubMed

    Eksborg, Staffan

    2013-01-01

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

  11. Prediction Formulas for Individual Opioid Analgesic Requirements Based on Genetic Polymorphism Analyses

    PubMed Central

    Yoshida, Kaori; Nishizawa, Daisuke; Ichinomiya, Takashi; Ichinohe, Tatsuya; Hayashida, Masakazu; Fukuda, Ken-ichi; Ikeda, Kazutaka

    2015-01-01

    Background The analgesic efficacy of opioids is well known to vary widely among individuals, and various factors related to individual differences in opioid sensitivity have been identified. However, a prediction model to calculate appropriate opioid analgesic requirements has not yet been established. The present study sought to construct prediction formulas for individual opioid analgesic requirements based on genetic polymorphisms and clinical data from patients who underwent cosmetic orthognathic surgery and validate the utility of the prediction formulas in patients who underwent major open abdominal surgery. Methods To construct the prediction formulas, we performed multiple linear regression analyses using data from subjects who underwent cosmetic orthognathic surgery. The dependent variable was 24-h postoperative or perioperative fentanyl use, and the independent variables were age, gender, height, weight, pain perception latencies (PPL), and genotype data of five single-nucleotide polymorphisms (SNPs). To examine the utility of the prediction formulas, we performed simple linear regression analyses using subjects who underwent major open abdominal surgery. Actual 24-h postoperative or perioperative analgesic use and the predicted values that were calculated using the multiple regression equations were incorporated as dependent and independent variables, respectively. Results Multiple linear regression analyses showed that the four SNPs, PPL, and weight were retained as independent predictors of 24-h postoperative fentanyl use (R2 = 0.145, P = 5.66 × 10-10) and the two SNPs and weight were retained as independent predictors of perioperative fentanyl use (R2 = 0.185, P = 1.99 × 10-15). Simple linear regression analyses showed that the predicted values were retained as an independent predictor of actual 24-h postoperative analgesic use (R2 = 0.033, P = 0.030) and perioperative analgesic use (R2 = 0.100, P = 1.09 × 10-4), respectively. Conclusions We

  12. Predicting efficiency of solar cells based on transparent conducting electrodes

    NASA Astrophysics Data System (ADS)

    Kumar, Ankush

    2017-01-01

    Efficiency of a solar cell is directly correlated with the performance of its transparent conducting electrodes (TCEs) which dictates its two core processes, viz., absorption and collection efficiencies. Emerging designs of a TCE involve active networks of carbon nanotubes, silver nanowires and various template-based techniques providing diverse structures; here, voids are transparent for optical transmittance while the conducting network acts as a charge collector. However, it is still not well understood as to which kind of network structure leads to an optimum solar cell performance; therefore, mostly an arbitrary network is chosen as a solar cell electrode. Herein, we propose a new generic approach for understanding the role of TCEs in determining the solar cell efficiency based on analysis of shadowing and recombination losses. A random network of wires encloses void regions of different sizes and shapes which permit light transmission; two terms, void fraction and equivalent radius, are defined to represent the TCE transmittance and wire spacings, respectively. The approach has been applied to various literature examples and their solar cell performance has been compared. To obtain high-efficiency solar cells, optimum density of the wires and their aspect ratio as well as active layer thickness are calculated. Our findings show that a TCE well suitable for one solar cell may not be suitable for another. For high diffusion length based solar cells, the void fraction of the network should be low while for low diffusion length based solar cells, the equivalent radius should be lower. The network with less wire spacing compared to the diffusion length behaves similar to continuous film based TCEs (such as indium tin oxide). The present work will be useful for architectural as well as material engineering of transparent electrodes for improvisation of solar cell performance.

  13. Energy-efficient neural information processing in individual neurons and neuronal networks.

    PubMed

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  14. Predicting high harmonic ion cyclotron heating efficiency in Tokamak plasmas

    SciTech Connect

    Green, David L; Jaeger, E. F.; Berry, Lee A; Chen, Guangye; Ryan, Philip Michael; Canik, John

    2011-01-01

    Observations of improved radio frequency (RF) heating efficiency in high-confinement (H-) mode plasmas on the National Spherical Tokamak Experiment (NSTX) are investigated by whole-device linear simulation. We present the first full-wave simulation to couple kinetic physics of the well confined core plasma to the poorly confined scrape-off plasma. The new simulation is used to scan the launched fast-wave spectrum and examine the steady-state electric wave field structure for experimental scenarios corresponding to both reduced, and improved RF heating efficiency. We find that launching toroidal wave-numbers that required for fast-wave propagation excites large amplitude (kVm 1 ) coaxial standing modes in the wave electric field between the confined plasma density pedestal and conducting vessel wall. Qualitative comparison with measurements of the stored plasma energy suggest these modes are a probable cause of degraded heating efficiency. Also, the H-mode density pedestal and fast-wave cutoff within the confined plasma allow for the excitation of whispering gallery type eigenmodes localised to the plasma edge.

  15. Predicting Efficient Antenna Ligands for Tb(III) Emission

    SciTech Connect

    Samuel, Amanda P.S.; Xu, Jide; Raymond, Kenneth

    2008-10-06

    A series of highly luminescent Tb(III) complexes of para-substituted 2-hydroxyisophthalamide ligands (5LI-IAM-X) has been prepared (X = H, CH{sub 3}, (C=O)NHCH{sub 3}, SO{sub 3}{sup -}, NO{sub 2}, OCH{sub 3}, F, Cl, Br) to probe the effect of substituting the isophthalamide ring on ligand and Tb(III) emission in order to establish a method for predicting the effects of chromophore modification on Tb(III) luminescence. The energies of the ligand singlet and triplet excited states are found to increase linearly with the {pi}-withdrawing ability of the substituent. The experimental results are supported by time-dependent density functional theory (TD-DFT) calculations performed on model systems, which predict ligand singlet and triplet energies within {approx}5% of the experimental values. The quantum yield ({Phi}) values of the Tb(III) complex increases with the triplet energy of the ligand, which is in part due to the decreased non-radiative deactivation caused by thermal repopulation of the triplet. Together, the experimental and theoretical results serve as a predictive tool that can be used to guide the synthesis of ligands used to sensitize lanthanide luminescence.

  16. Highly efficient exfoliation of individual single-walled carbon nanotubes by biocompatible phenoxylated dextran.

    PubMed

    Kwon, Taeyun; Lee, Gyudo; Choi, Hyerim; Strano, Michael S; Kim, Woo-Jae

    2013-08-07

    Highly efficient exfoliation of individual single-walled carbon nanotubes (SWNTs) was successfully demonstrated by utilizing biocompatible phenoxylated dextran, a kind of polysaccharide, as a SWNT dispersion agent. Phenoxylated dextran shows greater ability in producing individual SWNTs from raw materials than any other dispersing agent, including anionic surfactants and another polysaccharide. Furthermore, with this novel polymer, SWNT bundles or impurities present in raw materials are removed under much milder processing conditions compared to those of ultra-centrifugation procedures. There exists an optimal composition of phenoxy groups (∼13.6 wt%) that leads to the production of high-quality SWNT suspensions, as confirmed by UV-vis-nIR absorption and nIR fluorescence spectroscopy. Furthermore, phenoxylated dextran strongly adsorbs onto SWNTs, enabling SWNT fluorescence even in solid-state films in which metallic SWNTs co-exist. By bypassing ultra-centrifugation, this low-energy dispersion scheme can potentially be scaled up to industrial production levels.

  17. Disrupted Topologic Efficiency of White Matter Structural Connectome in Individuals with Subjective Cognitive Decline.

    PubMed

    Shu, Ni; Wang, Xiaoni; Bi, Qiuhui; Zhao, Tengda; Han, Ying

    2017-08-11

    Purpose To determine whether individuals with subjective cognitive decline (SCD), which is defined by memory complaints with normal performance at objective neuropsychologic examinations, exhibit disruptions of white matter (WM) connectivity and topologic alterations of the brain structural connectome. Materials and Methods Diffusion-tensor magnetic resonance imaging and graph theory approaches were used to investigate the topologic organization of the brain structural connectome in 36 participants with SCD (21 women: mean age, 62.0 years ± 8.6 [standard deviation]; age range, 42-76 years; 15 men: mean age, 65.5 years ± 8.9; age range, 51-80 years) and 51 age-, sex-, and years of education-matched healthy control participants (33 women: mean age, 63.7 years ± 8.8; age range, 46-83 years; 18 men: mean age, 59.4 years ± 9.3; age range, 43-75 years). Individual WM networks were constructed for each participant, and the network properties between two groups were compared with a linear regression model. Results Graph theory analyses revealed that the participants with SCD had less global efficiency (P = .001) and local efficiency (P = .008) compared with the healthy control participants. Lower regional efficiency was mainly distributed in the bilateral prefrontal regions and left thalamus (P < .05, corrected). Furthermore, a disrupted subnetwork was observed that consisted of widespread anatomic connections (P < .05, corrected), which has the potential to discriminate individuals with SCD from control participants. Moreover, similar hub distributions and less connection strength between the hub regions (P = .023) were found in SCD. Importantly, diminished strength of the rich-club and local connections was correlated with the impaired memory performance in patients with SCD (rich-club connection: r = 0.43, P = .011; local connection: r = 0.36, P = .037). Conclusion This study demonstrated disrupted topologic efficiency of the brain's structural connectome in

  18. Predicting patriarchy: using individual and contextual factors to examine patriarchal endorsement in communities.

    PubMed

    Crittenden, Courtney A; Wright, Emily M

    2013-04-01

    In much feminist literature, patriarchy has often been studied as a predictive variable for attitudes toward or acts of violence against women. However, rarely has patriarchy been examined as an outcome across studies. The current study works toward filling this gap by examining several individual-and neighborhood-level factors that might influence patriarchy. Specifically, this research seeks to determine if neighborhood-level attributes related to socioeconomic status, family composition, and demographic information affect patriarchal views after individual-level correlates of patriarchy were controlled. Findings suggest that factors at both the individual- and neighborhood levels, particularly familial characteristics and dynamics, do influence the endorsement of patriarchal views.

  19. Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

    PubMed Central

    Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

    2014-01-01

    This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

  20. [The functional ability and efficiency of motor skills evaluation of individuals admitted into nursing homes in Poland].

    PubMed

    Pruszyński, Jacek J; Cicha-Mikołajczyk, Alicja; Gebska-Kuczerowska, Anita

    2006-01-01

    The objective of the study was to evaluate the functional ability and efficiency of motor skills of Individuals admitted into nursing homes. The study took place between the years of 1997-2004 in a group of 122 individuals. The evaluation was based on two scales: ADL and IADL. The fall-related injury scale was used to evaluate the functionality ability and efficiency of motor skills. The Tinneti Scale of fall-related accident risk assessment was used to evaluate the functional ability and efficiency of motor skills. The study concluded that a majority of the individuals revealed a decrease in their functional ability and efficiency of motor skills. This is most relevant to individuals admitted directly from hospitals. The organization and development of new nursing home facilities must meet the needs of the individuals. The individuals admitted directly from the hospital require the best care due to their critical health status.

  1. On-Line Individual Differences in Statistical Learning Predict Language Processing

    PubMed Central

    Misyak, Jennifer B.; Christiansen, Morten H.; Tomblin, J. Bruce

    2010-01-01

    Considerable individual differences in language ability exist among normally developing children and adults. Whereas past research have attributed such differences to variations in verbal working memory or experience with language, we test the hypothesis that individual differences in statistical learning may be associated with differential language performance. We employ a novel paradigm for studying statistical learning on-line, combining a serial-reaction time task with artificial grammar learning. This task offers insights into both the timecourse of and individual differences in statistical learning. Experiment 1 charts the micro-level trajectory for statistical learning of nonadjacent dependencies and provides an on-line index of individual differences therein. In Experiment 2, these differences are then shown to predict variations in participants’ on-line processing of long-distance dependencies involving center-embedded relative clauses. The findings suggest that individual differences in the ability to learn from experience through statistical learning may contribute to variations in linguistic performance. PMID:21833201

  2. On-line individual differences in statistical learning predict language processing.

    PubMed

    Misyak, Jennifer B; Christiansen, Morten H; Tomblin, J Bruce

    2010-01-01

    Considerable individual differences in language ability exist among normally developing children and adults. Whereas past research have attributed such differences to variations in verbal working memory or experience with language, we test the hypothesis that individual differences in statistical learning may be associated with differential language performance. We employ a novel paradigm for studying statistical learning on-line, combining a serial-reaction time task with artificial grammar learning. This task offers insights into both the timecourse of and individual differences in statistical learning. Experiment 1 charts the micro-level trajectory for statistical learning of nonadjacent dependencies and provides an on-line index of individual differences therein. In Experiment 2, these differences are then shown to predict variations in participants' on-line processing of long-distance dependencies involving center-embedded relative clauses. The findings suggest that individual differences in the ability to learn from experience through statistical learning may contribute to variations in linguistic performance.

  3. Predicting Achievement in Mathematics in Adolescent Students: The Role of Individual and Social Factors

    ERIC Educational Resources Information Center

    Levpuscek, Melita Puklek; Zupancic, Maja; Socan, Gregor

    2013-01-01

    The study examined individual factors and social factors that influence adolescent students' achievement in mathematics. The predictive model suggested direct positive effects of student intelligence, self-rated openness and parental education on achievement in mathematics, whereas direct effects of extraversion on measures of achievement were…

  4. An Individual-Tree Growth and Yield Prediction System for Uneven-Aged Shortleaf Pine Stands

    Treesearch

    Michael M. Huebschmann; Lawrence R. Gering; Thomas B. Lynch; Onesphore Bitoki; Paul A. Murphy

    2000-01-01

    A system of equations modeling the growth and development of uneven-aged shortleaf pine (Pinus echinata Mill.) stands is described. The prediction system consists of two main components: (1) a distance-independent, individual-tree simulator containing equations that forecast ingrowth, basal-area growth, probability of survival, total and...

  5. Predicting Teen Motherhood and Teen Fatherhood: Individual Characteristics and Peer Affiliations.

    ERIC Educational Resources Information Center

    Xie, Hongling; Cairns, Beverley D.; Cairns, Robert B.

    2001-01-01

    Examined 475 adolescents from Grade 7 through early adulthood to identify antecedents and pathways of teen parenthood. Found that teen fatherhood and motherhood were predicted by individual and peer configurations such as a combination of high aggression, low academic competence, low popularity, and low family SES. Peer characteristics, race, and…

  6. Student personality traits predicting individuation in relation to mothers and fathers.

    PubMed

    Zupančič, Maja; Kavčič, Tina

    2014-07-01

    The role of personality traits in 674 emerging adult students' (aged 18 to 28; 80% female) individuation in relation to parents was investigated cross-sectionally. Self-reports were obtained by the Big Five Inventory and the Individuation Test for Emerging Adults. Personality was predictive of measures of individuation, over and above the students' background characteristics, suggesting that personality can be viewed as an inner resource shaping experiences of individuation. Agreeableness contributed to support seeking, and connectedness with both parents, and Extraversion predicted connectedness with mothers. Conscientiousness was related negatively to both perceptions of parental intrusiveness and fear of disappointing the mother, whereas Neuroticism was predictive of perceptions of maternal intrusiveness, and fear of disappointing the parents. Openness was associated with self-reliance in relationships with both parents, and demonstrated negative links with support seeking and connectedness with mothers. Few moderating effects of age and gender on Extraversion-individuation associations were revealed. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  7. Making Predictions in a Changing World: The Benefits of Individual-Based Ecology

    PubMed Central

    Stillman, Richard A.; Railsback, Steven F.; Giske, Jarl; Berger, Uta; Grimm, Volker

    2014-01-01

    Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions—fitness maximization by individual organisms—is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research. PMID:26955076

  8. RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS

    SciTech Connect

    John F. Schabron; A. Troy Pauli; Joseph F. Rovani Jr.

    2002-05-01

    The dispersed particle solution model of petroleum residua structure was used to develop predictors for pyrolytic coke formation. Coking Indexes were developed in prior years that measure how near a pyrolysis system is to coke formation during the coke formation induction period. These have been demonstrated to be universally applicable for residua regardless of the source of the material. Coking onset is coincidental with the destruction of the ordered structure and the formation of a multiphase system. The amount of coke initially formed appears to be a function of the free solvent volume of the original residua. In the current work, three-dimensional coke make predictability maps were developed at 400 C, 450 C, and 500 C (752 F, 842 F, and 932 F). These relate residence time and free solvent volume to the amount of coke formed at a particular pyrolysis temperature. Activation energies for two apparent types of zero-order coke formation reactions were estimated. The results provide a new tool for ranking residua, gauging proximity to coke formation, and predicting initial coke make tendencies.

  9. Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

    NASA Technical Reports Server (NTRS)

    Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.

    2008-01-01

    This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.

  10. Performance of a Portable Sleep Monitoring Device in Individuals with High Versus Low Sleep Efficiency

    PubMed Central

    Markwald, Rachel R.; Bessman, Sara C.; Reini, Seth A.; Drummond, Sean P.A.

    2016-01-01

    Study Objectives: Portable and automated sleep monitoring technology is becoming widely available to consumers, and one wireless system (WS) has recently surfaced as a research tool for sleep and sleep staging assessment outside the hospital/laboratory; however, previous research findings indicate low sensitivity for wakefulness detection. Because difficulty discriminating between wake and sleep is likely to affect staging performance, we sought to further evaluate the WS by comparing it to the gold-standard polysomnography (PSG) and actigraphy (ACT) for overall sleep/wakefulness detection and sleep staging, within high and low sleep efficiency sleepers. Methods: Twenty-nine healthy adults (eight females) underwent concurrent WS, PSG, and ACT assessment in an overnight laboratory study. Epoch-by-epoch agreement was determined by comparing sleep/wakefulness decisions between the WS to both PSG and ACT, and for detection of light, deep, and rapid eye movement (REM) sleep stages between the WS and PSG. Results: Sensitivity for wakefulness was low (40%), and an overestimation of total sleep time and underestimation of wake after sleep onset was observed. Prevalence and bias adjusted kappa statistic indicated moderate-to-high agreement between the WS and PSG for sleep staging. However, upon further inspection, WS performance varied by sleep efficiency, with the best performance during high sleep efficiency. Conclusions: The benefit of the WS as a sleep monitoring device over ACT is the ability to assess sleep stages, and our findings suggest this benefit is only realized within high sleep efficiency. Care should be taken to collect data under conditions where this is expected. Citation: Markwald RR, Bessman SC, Reini SA, Drummond SP. Performance of a portable sleep monitoring device in individuals with high versus low sleep efficiency. J Clin Sleep Med 2016;12(1):95–103. PMID:26285110

  11. Predicting with confidence the efficiency of new dyes in dye sensitized solar cells.

    PubMed

    Ip, Chung Man; Eleuteri, Antonio; Troisi, Alessandro

    2014-09-28

    We ask whether it is possible to predict the efficiency of a new dye in dye sensitized solar cells (DSSCs) on the basis of the known performance of existing dyes in the same type of device. We evaluate a number of computable predictors of the efficiency for a large set of dyes whose experimental efficiency is known. We have then used statistical regression methods to establish the relation between the predictors and the efficiency. Our predictions are associated with a rigorously determined confidence level. For a new dye of the same family we are able to predict the probability that its efficiency in a DSSC is larger than a certain threshold. This method is useful for accelerating the discovery of new dyes and establishing more rigorously the existence of specific correlations between structure and properties. Within the properties considered we find that the dye efficiency correlates more strongly with its oxidation potential and reorganization energy.

  12. Predictive models of alcohol use based on attitudes and individual values.

    PubMed

    García del Castillo Rodríguez, José A; López-Sánchez, Carmen; Quiles Soler, M Carmen; García del Castillo-López, Alvaro; Gázquez Pertusa, Mónica; Marzo Campos, Juan Carlos; Inglés, Candido J

    2013-01-01

    Two predictive models are developed in this article: the first is designed to predict people's attitudes to alcoholic drinks, while the second sets out to predict the use of alcohol in relation to selected individual values. University students (N = 1,500) were recruited through stratified sampling based on sex and academic discipline. The questionnaire used obtained information on participants' alcohol use, attitudes and personal values. The results show that the attitudes model correctly classifies 76.3% of cases. Likewise, the model for level of alcohol use correctly classifies 82% of cases. According to our results, we can conclude that there are a series of individual values that influence drinking and attitudes to alcohol use, which therefore provides us with a potentially powerful instrument for developing preventive intervention programs.

  13. Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

    PubMed Central

    Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R.; Meda-Campaña, M. E.

    2012-01-01

    Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment. PMID:23226305

  14. Genetic programming as alternative for predicting development effort of individual software projects.

    PubMed

    Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R; Meda-Campaña, M E

    2012-01-01

    Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment.

  15. Behavior pattern (innate action) of individuals in fish schools generating efficient collective evasion from predation.

    PubMed

    Zheng, M; Kashimori, Y; Hoshino, O; Fujita, K; Kambara, T

    2005-07-21

    The schooling of fishes is one typical animal social behavior. One primary function of fish school is to protect members when attacked by predators. One main way that the school reduces the predator's chance of making a successful kill is to confuse the predator as it makes its strike. This may be accomplished by collective evasion behaviors organized through integration of motions of individual fish made based on their innate actions (behavior patterns). In order to investigate what kind of behavior pattern of individuals can generate the efficient collective evasion of a school, we present a model of evasion behavior pattern which consists of three component behavior patterns, schooling, cooperative escape, and selfish escape behavior patterns and the rule for choice of one among them with proper timing. Each fish determines its movement direction taking into account simultaneously three kinds of elemental motions, mimicking its neighbors, avoiding collisions with its nearest neighbors, and escaping from an approaching predator. The weights of three elemental motions are changed depending on which component behavior pattern the fish carries out. The values of the weights for three component behavior patterns can be definitively determined under the condition that the collective evasion of the school becomes the most efficient, that is, the probability that any member is eaten by the predator becomes minimum.

  16. Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations.

    PubMed

    Rincent, R; Charcosset, A; Moreau, L

    2017-08-09

    We propose a criterion to predict genomic selection efficiency for structured populations. This criterion is useful to define optimal calibration set and to estimate prediction reliability for multiparental populations. Genomic selection refers to the use of genotypic information for predicting the performance of selection candidates. It has been shown that prediction accuracy depends on various parameters including the composition of the calibration set (CS). Assessing the level of accuracy of a given prediction scenario is of highest importance because it can be used to optimize CS sampling before collecting phenotypes, and once the breeding values are predicted it informs the breeders about the reliability of these predictions. Different criteria were proposed to optimize CS sampling in highly diverse panels, which can be useful to screen collections of genotypes. But plant breeders often work on structured material such as biparental or multiparental populations, for which these criteria are less adapted. We derived from the generalized coefficient of determination (CD) theory different criteria to optimize CS sampling and to assess the reliability associated to predictions in structured populations. These criteria were evaluated on two nested association mapping (NAM) populations and two highly diverse panels of maize. They were efficient to sample optimized CS in most situations. They could also estimate at least partly the reliability associated to predictions between NAM families, but they could not estimate differences in the reliability associated to the predictions of NAM families using the highly diverse panels as calibration sets. We illustrated that the CD criteria could be adapted to various prediction scenarios including inter and intra-family predictions, resulting in higher prediction accuracies.

  17. A progressively predictive image pyramid for efficient lossless coding.

    PubMed

    Qiu, G

    1999-01-01

    A low entropy pyramidal image data structure suited for lossless coding and progressive transmission is proposed in this work. The new coder, called the progressively predictive pyramid (PPP) is based on the well-known Laplacian pyramid. By introducing inter-resolution predictors into the original Laplacian pyramid, we show that the entropy level in the original pyramid can be reduced significantly. To take full advantage of progressive transmission, a scheme is introduced to create the predictor adaptively, thus eliminating the need to transmit the predictor and reducing the coding overheads. A method for designing the predictor is presented. Numerical results show that PPP is superior to traditional approaches to pyramid generation in the sense that the pyramids generated by PPP always have significantly lower entropy values.

  18. Efficient Reconstruction of Predictive Consensus Metabolic Network Models

    PubMed Central

    Martins dos Santos, Vitor A. P.; Stelling, Joerg

    2016-01-01

    Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions. PMID:27563720

  19. Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis.

    PubMed

    Mechelli, Andrea; Lin, Ashleigh; Wood, Stephen; McGorry, Patrick; Amminger, Paul; Tognin, Stefania; McGuire, Philip; Young, Jonathan; Nelson, Barnaby; Yung, Alison

    2016-12-04

    Recent studies have reported an association between psychopathology and subsequent clinical and functional outcomes in people at ultra-high risk (UHR) for psychosis. This has led to the suggestion that psychopathological information could be used to make prognostic predictions in this population. However, because the current literature is based on inferences at group level, the translational value of the findings for everyday clinical practice is unclear. Here we examined whether psychopathological information could be used to make individualized predictions about clinical and functional outcomes in people at UHR. Participants included 416 people at UHR followed prospectively at the Personal Assessment and Crisis Evaluation (PACE) Clinic in Melbourne, Australia. The data were analysed using Support Vector Machine (SVM), a supervised machine learning technique that allows inferences at the individual level. SVM predicted transition to psychosis with a specificity of 60.6%, a sensitivity of 68.6% and an accuracy of 64.6% (p<0.001). In addition, SVM predicted functioning with a specificity of 62.5%, a sensitivity of 62.5% and an accuracy of 62.5% (p=0.008). Prediction of transition was driven by disorder of thought content, attenuated positive symptoms and functioning, whereas functioning was best predicted by attention disturbances, anhedonia-asociality and disorder of thought content. These results indicate that psychopathological information allows individualized prognostic predictions with statistically significant accuracy. However, this level of accuracy may not be sufficient for clinical translation in real-world clinical practice. Accuracy might be improved by combining psychopathological information with other types of data using a multivariate machine learning framework.

  20. Evaluation of the efficiency of artificial neural networks for genetic value prediction.

    PubMed

    Silva, G N; Tomaz, R S; Sant'Anna, I C; Carneiro, V Q; Cruz, C D; Nascimento, M

    2016-03-28

    Artificial neural networks have shown great potential when applied to breeding programs. In this study, we propose the use of artificial neural networks as a viable alternative to conventional prediction methods. We conduct a thorough evaluation of the efficiency of these networks with respect to the prediction of breeding values. Therefore, we considered eight simulated scenarios, and for the purpose of genetic value prediction, seven statistical parameters in addition to the phenotypic mean in a network designed as a multilayer perceptron. After an evaluation of different network configurations, the results demonstrated the superiority of neural networks compared to estimation procedures based on linear models, and indicated high predictive accuracy and network efficiency.

  1. Personality predicts individual responsiveness to the risks of starvation and predation

    PubMed Central

    Quinn, J. L.; Cole, E. F.; Bates, J.; Payne, R. W.; Cresswell, W.

    2012-01-01

    Theory suggests that individual personality is tightly linked to individual life histories and to environmental variation. The reactive–proactive axis, for example, is thought to reflect whether individuals prioritize productivity or survival, mutually exclusive options that can be caused by conflicts between foraging and anti-predation behaviour. Evidence for this trade-off hypothesis, however, is limited. Here, we tested experimentally whether exploration behaviour (EB), an assay of proactivity, could explain how great tits (Parus major) respond to changes in starvation and predation risk. Individuals were presented with two feeders, holding good or poor quality food, which interchanged between safe and dangerous positions 10 m apart, across two 24 h treatments. Starvation risk was assumed to be highest in the morning and lowest in the afternoon. The proportion of time spent feeding on good quality food (PTG) rather than poor quality food was repeatable within treatments, but individuals varied in how PTG changed with respect to predation- and starvation-risk across treatments. This individual plasticity variation in foraging behaviour was linked to EB, as predicted by the reactive–proactive axis, but only among individuals in dominant social classes. Our results support the trade-off hypothesis at the level of individuals in a wild population, and suggest that fine-scale temporal and spatial variation may play important roles in the evolution of personality. PMID:22179807

  2. Personality predicts individual responsiveness to the risks of starvation and predation.

    PubMed

    Quinn, J L; Cole, E F; Bates, J; Payne, R W; Cresswell, W

    2012-05-22

    Theory suggests that individual personality is tightly linked to individual life histories and to environmental variation. The reactive-proactive axis, for example, is thought to reflect whether individuals prioritize productivity or survival, mutually exclusive options that can be caused by conflicts between foraging and anti-predation behaviour. Evidence for this trade-off hypothesis, however, is limited. Here, we tested experimentally whether exploration behaviour (EB), an assay of proactivity, could explain how great tits (Parus major) respond to changes in starvation and predation risk. Individuals were presented with two feeders, holding good or poor quality food, which interchanged between safe and dangerous positions 10 m apart, across two 24 h treatments. Starvation risk was assumed to be highest in the morning and lowest in the afternoon. The proportion of time spent feeding on good quality food (PTG) rather than poor quality food was repeatable within treatments, but individuals varied in how PTG changed with respect to predation- and starvation-risk across treatments. This individual plasticity variation in foraging behaviour was linked to EB, as predicted by the reactive-proactive axis, but only among individuals in dominant social classes. Our results support the trade-off hypothesis at the level of individuals in a wild population, and suggest that fine-scale temporal and spatial variation may play important roles in the evolution of personality.

  3. PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

    PubMed

    Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

    2016-01-01

    We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

  4. An efficient genetic algorithm for structure prediction at the nanoscale.

    PubMed

    Lazauskas, Tomas; Sokol, Alexey A; Woodley, Scott M

    2017-03-17

    We have developed and implemented a new global optimization technique based on a Lamarckian genetic algorithm with the focus on structure diversity. The key process in the efficient search on a given complex energy landscape proves to be the removal of duplicates that is achieved using a topological analysis of candidate structures. The careful geometrical prescreening of newly formed structures and the introduction of new mutation move classes improve the rate of success further. The power of the developed technique, implemented in the Knowledge Led Master Code, or KLMC, is demonstrated by its ability to locate and explore a challenging double funnel landscape of a Lennard-Jones 38 atom system (LJ38). We apply the redeveloped KLMC to investigate three chemically different systems: ionic semiconductor (ZnO)1-32, metallic Ni13 and covalently bonded C60. All four systems have been systematically explored on the energy landscape defined using interatomic potentials. The new developments allowed us to successfully locate the double funnels of LJ38, find new local and global minima for ZnO clusters, extensively explore the Ni13 and C60 (the buckminsterfullerene, or buckyball) potential energy surfaces.

  5. Individual preparedness and mitigation actions for a predicted earthquake in Istanbul.

    PubMed

    Tekeli-Yeşil, Sıdıka; Dedeoğlu, Necati; Tanner, Marcel; Braun-Fahrlaender, Charlotte; Obrist, Birgit

    2010-10-01

    This study investigated the process of taking action to mitigate damage and prepare for an earthquake at the individual level. Its specific aim was to identify the factors that promote or inhibit individuals in this process. The study was conducted in Istanbul, Turkey--where an earthquake is expected soon--in May and June 2006 using qualitative methods. Within our conceptual framework, three different patterns emerged among the study subjects. Outcome expectancy, helplessness, a low socioeconomic level, a culture of negligence, a lack of trust, onset time/poor predictability, and normalisation bias inhibit individuals in this process, while location, direct personal experience, a higher education level, and social interaction promote them. Drawing on these findings, the paper details key points for better disaster communication, including whom to mobilise to reach target populations, such as individuals with direct earthquake experience and women. © 2010 The Author(s). Journal compilation © Overseas Development Institute, 2010.

  6. Combining information from ancestors and personal experiences to predict individual differences in developmental trajectories.

    PubMed

    Stamps, Judy A; Krishnan, V V

    2014-11-01

    A persistent question in biology is how information from ancestors combines with personal experiences over the lifetime to affect the developmental trajectories of phenotypic traits. We address this question by modeling individual differences in behavioral developmental trajectories on the basis of two assumptions: (1) differences among individuals in the behavior expressed at birth or hatching are based on information from their ancestors (via genes, epigenes, and prenatal maternal effects), and (2) information from ancestors is combined with information from personal experiences over ontogeny via Bayesian updating. The model predicts relationships between the means and the variability of the behavior expressed by neonates and the subsequent developmental trajectories of their behavior when every individual is reared under the same environmental conditions. Several predictions of the model are supported by data from previous studies of behavioral development, for example, that the temporal stability of personality will increase with age and that the intercepts and slopes of developmental trajectories for boldness will be negatively correlated across individuals or genotypes when subjects are raised in safe environments. We describe how other specific predictions of the model can be used to test the hypothesis that information from ancestors and information from personal experiences are combined via nonadditive, Bayesian-like processes.

  7. Doing It Your Way: How Individual Movement Styles Affect Action Prediction

    PubMed Central

    Koul, Atesh; Ansuini, Caterina; Becchio, Cristina

    2016-01-01

    Individuals show significant variations in performing a motor act. Previous studies in the action observation literature have largely ignored this ubiquitous, if often unwanted, characteristic of motor performance, assuming movement patterns to be highly similar across repetitions and individuals. In the present study, we examined the possibility that individual variations in motor style directly influence the ability to understand and predict others’ actions. To this end, we first recorded grasping movements performed with different intents and used a two-step cluster analysis to identify quantitatively ‘clusters’ of movements performed with similar movement styles (Experiment 1). Next, using videos of the same movements, we proceeded to examine the influence of these styles on the ability to judge intention from action observation (Experiments 2 and 3). We found that motor styles directly influenced observers’ ability to ‘read’ others’ intention, with some styles always being less ‘readable’ than others. These results provide experimental support for the significance of motor variability for action prediction, suggesting that the ability to predict what another person is likely to do next directly depends on her individual movement style. PMID:27780259

  8. Restructuring the navigational field: individual predisposition towards field independence predicts preferred navigational strategy.

    PubMed

    Boccia, Maddalena; Piccardi, Laura; D'Alessandro, Adele; Nori, Raffaella; Guariglia, Cecilia

    2017-06-01

    To successfully navigate within an environment, individuals have to organize the spatial information in terms of salient landmarks, paths and general layout of the navigational environment. They may differ in the strategy they adopt to orientate themselves, with some individuals preferring to use salient landmarks (landmark spatial style, L-SS), others preferring to plan routes or paths through an egocentric strategy in which landmarks are connected with each other (route spatial style, R-SS) and others still create a global map-like configuration of the environment regardless of their own position in the environment (survey spatial style, S-SS). Here, we assessed whether Field independence (FI), that is the extent to which the individual perceives part of a field as discrete from the surrounding field rather than embedded in the field, predicted the individual's spatial style. We assessed the individual's spatial style using the spatial cognitive style test (SCST) and measured FI using the group embedded figure test (GEFT). We found that FI predicted general spatial ability, with a higher level of FI being associated with better performances on the SCST. Also, Field-independent individuals showed a marked preference for an S-SS. These results suggest that a higher level of FI is associated with better performance on higher level spatial tasks (i.e. R-SS and S-SS) that is tasks requiring individuals to restructure the "navigational field" according to the navigational goal. The results also suggest that a higher level of FI makes individuals more prone to use a global and complex map-like representation of the environment.

  9. Efficient Helicopter Aerodynamic and Aeroacoustic Predictions on Parallel Computers

    NASA Technical Reports Server (NTRS)

    Wissink, Andrew M.; Lyrintzis, Anastasios S.; Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

    1996-01-01

    This paper presents parallel implementations of two codes used in a combined CFD/Kirchhoff methodology to predict the aerodynamics and aeroacoustics properties of helicopters. The rotorcraft Navier-Stokes code, TURNS, computes the aerodynamic flowfield near the helicopter blades and the Kirchhoff acoustics code computes the noise in the far field, using the TURNS solution as input. The overall parallel strategy adds MPI message passing calls to the existing serial codes to allow for communication between processors. As a result, the total code modifications required for parallel execution are relatively small. The biggest bottleneck in running the TURNS code in parallel comes from the LU-SGS algorithm that solves the implicit system of equations. We use a new hybrid domain decomposition implementation of LU-SGS to obtain good parallel performance on the SP-2. TURNS demonstrates excellent parallel speedups for quasi-steady and unsteady three-dimensional calculations of a helicopter blade in forward flight. The execution rate attained by the code on 114 processors is six times faster than the same cases run on one processor of the Cray C-90. The parallel Kirchhoff code also shows excellent parallel speedups and fast execution rates. As a performance demonstration, unsteady acoustic pressures are computed at 1886 far-field observer locations for a sample acoustics problem. The calculation requires over two hundred hours of CPU time on one C-90 processor but takes only a few hours on 80 processors of the SP2. The resultant far-field acoustic field is analyzed with state of-the-art audio and video rendering of the propagating acoustic signals.

  10. The role of pre-morbid intelligence and cognitive reserve in predicting cognitive efficiency in a sample of Italian elderly.

    PubMed

    Caffò, Alessandro O; Lopez, Antonella; Spano, Giuseppina; Saracino, Giuseppe; Stasolla, Fabrizio; Ciriello, Giuseppe; Grattagliano, Ignazio; Lancioni, Giulio E; Bosco, Andrea

    2016-12-01

    Models of cognitive reserve in aging suggest that individual's life experience (education, working activity, and leisure) can exert a neuroprotective effect against cognitive decline and may represent an important contribution to successful aging. The objective of the present study is to investigate the role of cognitive reserve, pre-morbid intelligence, age, and education level, in predicting cognitive efficiency in a sample of healthy aged individuals and with probable mild cognitive impairment. Two hundred and eight aging participants recruited from the provincial region of Bari (Apulia, Italy) took part in the study. A battery of standardized tests was administered to them to measure cognitive reserve, pre-morbid intelligence, and cognitive efficiency. Protocols for 10 participants were excluded since they did not meet inclusion criteria, and statistical analyses were conducted on data from the remaining 198 participants. A path analysis was used to test the following model: age, education level, and intelligence directly influence cognitive reserve and cognitive efficiency; cognitive reserve mediates the influence of age, education level, and intelligence on cognitive efficiency. Cognitive reserve fully mediates the relationship between pre-morbid intelligence and education level and cognitive efficiency, while age maintains a direct effect on cognitive efficiency. Cognitive reserve appears to exert a protective effect regarding cognitive decline in normal and pathological populations, thus masking, at least in the early phases of neurodegeneration, the decline of memory, orientation, attention, language, and reasoning skills. The assessment of cognitive reserve may represent a useful evaluation supplement in neuropsychological screening protocols of cognitive decline.

  11. Cortical Response Similarities Predict which Audiovisual Clips Individuals Viewed, but Are Unrelated to Clip Preference

    PubMed Central

    Bridwell, David A.; Roth, Cullen; Gupta, Cota Navin; Calhoun, Vince D.

    2015-01-01

    Cortical responses to complex natural stimuli can be isolated by examining the relationship between neural measures obtained while multiple individuals view the same stimuli. These inter-subject correlation’s (ISC’s) emerge from similarities in individual’s cortical response to the shared audiovisual inputs, which may be related to their emergent cognitive and perceptual experience. Within the present study, our goal is to examine the utility of using ISC’s for predicting which audiovisual clips individuals viewed, and to examine the relationship between neural responses to natural stimuli and subjective reports. The ability to predict which clips individuals viewed depends on the relationship of the EEG response across subjects and the nature in which this information is aggregated. We conceived of three approaches for aggregating responses, i.e. three assignment algorithms, which we evaluated in Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33%) and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%), with accuracies ranging from 52.9% (Silver Linings Playbook) to 11.75% (Seinfeld) within individual clips. ISC’s were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0-4 Hz) primarily contributed to response similarities across subjects. Interestingly, there was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. Overall these results demonstrate the utility of using ISC’s for prediction, and further characterize the relationship between ISC magnitudes and subjective reports. PMID:26030422

  12. Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets

    NASA Astrophysics Data System (ADS)

    Eom, Cheoljun; Choi, Sunghoon; Oh, Gabjin; Jung, Woo-Sung

    2008-07-01

    We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the directions of future price changes. We used 60 market indexes of various countries. We empirically discovered that the relationship between the degree of efficiency (the Hurst exponent) and the predictability (the hit rate) is strongly positive. That is, a market index with a higher Hurst exponent tends to have a higher hit rate. These results suggested that the Hurst exponent is useful for predicting future price changes. Furthermore, we also discovered that the Hurst exponent and the hit rate are useful as standards that can distinguish emerging capital markets from mature capital markets.

  13. Labour-efficient in vitro lymphocyte population tracking and fate prediction using automation and manual review.

    PubMed

    Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R; Wellard, Cameron; Zhou, Jie H S; Hodgkin, Philip D

    2014-01-01

    Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information.

  14. Labour-Efficient In Vitro Lymphocyte Population Tracking and Fate Prediction Using Automation and Manual Review

    PubMed Central

    Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R.; Wellard, Cameron; Zhou, Jie H. S.; Hodgkin, Philip D.

    2014-01-01

    Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information. PMID:24404133

  15. Personality traits and individual differences predict threat-induced changes in postural control.

    PubMed

    Zaback, Martin; Cleworth, Taylor W; Carpenter, Mark G; Adkin, Allan L

    2015-04-01

    This study explored whether specific personality traits and individual differences could predict changes in postural control when presented with a height-induced postural threat. Eighty-two healthy young adults completed questionnaires to assess trait anxiety, trait movement reinvestment (conscious motor processing, movement self-consciousness), physical risk-taking, and previous experience with height-related activities. Tests of static (quiet standing) and anticipatory (rise to toes) postural control were completed under low and high postural threat conditions. Personality traits and individual differences significantly predicted height-induced changes in static, but not anticipatory postural control. Individuals less prone to taking physical risks were more likely to lean further away from the platform edge and sway at higher frequencies and smaller amplitudes. Individuals more prone to conscious motor processing were more likely to lean further away from the platform edge and sway at larger amplitudes. Individuals more self-conscious about their movement appearance were more likely to sway at smaller amplitudes. Evidence is also provided that relationships between physical risk-taking and changes in static postural control are mediated through changes in fear of falling and physiological arousal. Results from this study may have indirect implications for balance assessment and treatment; however, further work exploring these factors in patient populations is necessary. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Individual-level trait diversity predicts phytoplankton community properties better than species richness or evenness.

    PubMed

    Fontana, Simone; Thomas, Mridul Kanianthara; Moldoveanu, Mirela; Spaak, Piet; Pomati, Francesco

    2017-10-03

    Understanding how microbial diversity influences ecosystem properties is of paramount importance. Cellular traits-which determine responses to the abiotic and biotic environment-may help us rigorously link them. However, our capacity to measure traits in natural communities has thus far been limited. Here we compared the predictive power of trait richness (trait space coverage), evenness (regularity in trait distribution) and divergence (prevalence of extreme phenotypes) derived from individual-based measurements with two species-level metrics (taxonomic richness and evenness) when modelling the productivity of natural phytoplankton communities. Using phytoplankton data obtained from 28 lakes sampled at different spatial and temporal scales, we found that the diversity in individual-level morphophysiological traits strongly improved our ability to predict community resource-use and biomass yield. Trait evenness-the regularity in distribution of individual cells/colonies within the trait space-was the strongest predictor, exhibiting a robust negative relationship across scales. Our study suggests that quantifying individual microbial phenotypes in trait space may help us understand how to link physiology to ecosystem-scale processes. Elucidating the mechanisms scaling individual-level trait variation to microbial community dynamics could there improve our ability to forecast changes in ecosystem properties across environmental gradients.The ISME Journal advance online publication, 3 October 2017; doi:10.1038/ismej.2017.160.

  17. In vivo prediction of the nutrient status of individual microalgal cells using Raman microspectroscopy.

    PubMed

    Heraud, Philip; Beardall, John; McNaughton, Don; Wood, Bayden R

    2007-10-01

    An in vivo method for predicting the nutrient status of individual algal cells using Raman microspectroscopy is described. Raman spectra of cells using 780 nm laser excitation show enhanced bands mainly attributable to chlorophyll a and beta-carotene. The relative intensities of chlorophyll a and beta-carotene bands changed under nitrogen limitation, with chlorophyll a bands becoming less intense and beta-carotene bands more prominent. Although spectra from N-replete and N-starved cell populations varied, each distribution was distinct enough such that multivariate classification methods, such as partial least squares discriminant analysis, could accurately predict the nutrient status of the cells from the Raman spectral data.

  18. Predicting Efficiency of Travel in Young, Visually Impaired Children from Their Other Spatial Skills.

    ERIC Educational Resources Information Center

    Hill, Anita; And Others

    1985-01-01

    To test ways of predicting how efficiently visually impaired children learn travel skills, a criteria checklist of spatial skills was developed for close-body space, local space, and geographical/travel space. Comparison was made between predictors of efficient learning including subjective ratings of teachers, personal qualities and factors of…

  19. Predicting Efficiency of Travel in Young, Visually Impaired Children from Their Other Spatial Skills.

    ERIC Educational Resources Information Center

    Hill, Anita; And Others

    1985-01-01

    To test ways of predicting how efficiently visually impaired children learn travel skills, a criteria checklist of spatial skills was developed for close-body space, local space, and geographical/travel space. Comparison was made between predictors of efficient learning including subjective ratings of teachers, personal qualities and factors of…

  20. Efficient removal of chromate and arsenate from individual and mixed system by malachite nanoparticles.

    PubMed

    Saikia, Jiban; Saha, Bedabrata; Das, Gopal

    2011-02-15

    Malachite nanoparticles of 100-150 nm have been efficiently and for the first time used as an adsorbent for the removal of toxic arsenate and chromate. We report a high adsorption capacity for chromate and arsenate on malachite nanoparticle from both individual and mixed solution in pH ∼4-5. However, the adsorption efficiency decreases with the increase of solution pH. Batch studies revealed that initial pH, temperature, malachite nanoparticles dose and initial concentration of chromate and arsenate were important parameters for the adsorption process. Thermodynamic analysis showed that adsorption of chromate and arsenate on malachite nanoparticles is endothermic and spontaneous. The adsorption of these anions has also been investigated quantitatively with the help of adsorption kinetics, isotherm, and selectivity coefficient (K) analysis. The adsorption data for both chromate and arsenate were fitted well in Langmuir isotherm and preferentially followed the second order kinetics. The binding affinity of chromate is found to be slightly higher than arsenate in a competitive adsorption process which leads to the comparatively higher adsorption of chromate on malachite nanoparticles surface.

  1. Efficient Method of Achieving Agreements between Individuals and Organizations about RFID Privacy

    NASA Astrophysics Data System (ADS)

    Cha, Shi-Cho

    This work presents novel technical and legal approaches that address privacy concerns for personal data in RFID systems. In recent years, to minimize the conflict between convenience and the privacy risk of RFID systems, organizations have been requested to disclose their policies regarding RFID activities, obtain customer consent, and adopt appropriate mechanisms to enforce these policies. However, current research on RFID typically focuses on enforcement mechanisms to protect personal data stored in RFID tags and prevent organizations from tracking user activity through information emitted by specific RFID tags. A missing piece is how organizations can obtain customers' consent efficiently and flexibly. This study recommends that organizations obtain licenses automatically or semi-automatically before collecting personal data via RFID technologies rather than deal with written consents. Such digitalized and standard licenses can be checked automatically to ensure that collection and use of personal data is based on user consent. While individuals can easily control who has licenses and license content, the proposed framework provides an efficient and flexible way to overcome the deficiencies in current privacy protection technologies for RFID systems.

  2. Using Subject Test Scores Efficiently to Predict Teacher Value-Added

    ERIC Educational Resources Information Center

    Lefgren, Lars; Sims, David

    2012-01-01

    This article develops a simple model of teacher value-added to show how efficient use of information across subjects can improve the predictive ability of value-added models. Using matched student-teacher data from North Carolina, we show that the optimal use of math and reading scores improves the fit of prediction models of overall future…

  3. Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.

    PubMed

    McGregor, Heather R; Gribble, Paul L

    2017-08-01

    Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning.NEW & NOTEWORTHY We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke. Copyright © 2017 the American Physiological Society.

  4. A simple and efficient total genomic DNA extraction method for individual zooplankton.

    PubMed

    Fazhan, Hanafiah; Waiho, Khor; Shahreza, Md Sheriff

    2016-01-01

    Molecular approaches are widely applied in species identification and taxonomic studies of minute zooplankton. One of the most focused zooplankton nowadays is from Subclass Copepoda. Accurate species identification of all life stages of the generally small sized copepods through molecular analysis is important, especially in taxonomic and systematic assessment of harpacticoid copepod populations and to understand their dynamics within the marine community. However, total genomic DNA (TGDNA) extraction from individual harpacticoid copepods can be problematic due to their small size and epibenthic behavior. In this research, six TGDNA extraction methods done on individual harpacticoid copepods were compared. The first new simple, feasible, efficient and consistent TGDNA extraction method was designed and compared with the commercial kit and modified available TGDNA extraction methods. The newly described TGDNA extraction method, "Incubation in PCR buffer" method, yielded good and consistent results based on the high success rate of PCR amplification (82%) compared to other methods. Coupled with its relatively consistent and economical method the "Incubation in PCR buffer" method is highly recommended in the TGDNA extraction of other minute zooplankton species.

  5. Collective Prediction of Individual Mobility Traces for Users with Short Data History

    PubMed Central

    Sitko, Izabela; Kazakopoulos, Pavlos; Beinat, Euro

    2017-01-01

    We present and test a sequential learning algorithm for the prediction of human mobility that leverages large datasets of sequences to improve prediction accuracy, in particular for users with a short and non-repetitive data history such as tourists in a foreign country. The algorithm compensates for the difficulty of predicting the next location when there is limited evidence of past behavior by leveraging the availability of sequences of other users in the same system that provide redundant records of typical behavioral patterns. We test the method on a dataset of 10 million roaming mobile phone users in a European country. The average prediction accuracy is significantly higher than that of individual sequence prediction algorithms, primarily constant order Markov models derived from the user’s own data, that have been shown to achieve high accuracy in previous studies of human mobility. The proposed algorithm is generally applicable to improve any sequential prediction when there is a sufficiently rich and diverse dataset of sequences. PMID:28135289

  6. A network of amygdala connections predict individual differences in trait anxiety.

    PubMed

    Greening, Steven G; Mitchell, Derek G V

    2015-12-01

    In this study we demonstrate that the pattern of an amygdala-centric network contributes to individual differences in trait anxiety. Individual differences in trait anxiety were predicted using maximum likelihood estimates of amygdala structural connectivity to multiple brain targets derived from diffusion-tensor imaging (DTI) and probabilistic tractography on 72 participants. The prediction was performed using a stratified sixfold cross validation procedure using a regularized least square regression model. The analysis revealed a reliable network of regions predicting individual differences in trait anxiety. Higher trait anxiety was associated with stronger connections between the amygdala and dorsal anterior cingulate cortex, an area implicated in the generation of emotional reactions, and inferior temporal gyrus and paracentral lobule, areas associated with perceptual and sensory processing. In contrast, higher trait anxiety was associated with weaker connections between amygdala and regions implicated in extinction learning such as medial orbitofrontal cortex, and memory encoding and environmental context recognition, including posterior cingulate cortex and parahippocampal gyrus. Thus, trait anxiety is not only associated with reduced amygdala connectivity with prefrontal areas associated with emotion modulation, but also enhanced connectivity with sensory areas. This work provides novel anatomical insight into potential mechanisms behind information processing biases observed in disorders of emotion.

  7. Quantitative prediction of individual psychopathology in trauma survivors using resting-state FMRI.

    PubMed

    Gong, Qiyong; Li, Lingjiang; Du, Mingying; Pettersson-Yeo, William; Crossley, Nicolas; Yang, Xun; Li, Jing; Huang, Xiaoqi; Mechelli, Andrea

    2014-02-01

    Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level. Resting-state functional MRI data was acquired for 121 survivors of the 2008 Sichuan earthquake each of whom was assessed for symptoms of post-traumatic stress disorder (PTSD) using the 17-item PTSD Checklist (PCL). Using a multivariate analytical method known as relevance vector regression (RVR), we examined the relationship between resting-state functional MRI data and symptom scores. We found that the use of RVR allowed quantitative prediction of clinical scores with statistically significant accuracy (correlation=0.32, P=0.006; mean squared error=176.88, P=0.001). Accurate prediction was based on functional activation in a number of prefrontal, parietal, and occipital regions. This is the first evidence that neuroimaging techniques may inform the clinical assessment of trauma-exposed individuals by providing an accurate and objective quantitative estimation of psychopathology. Furthermore, the significant contribution of parietal and occipital regions to such estimation challenges the traditional view of PTSD as a disorder specific to the fronto-limbic network.

  8. Quantitative Prediction of Individual Psychopathology in Trauma Survivors Using Resting-State fMRI

    PubMed Central

    Gong, Qiyong; Li, Lingjiang; Du, Mingying; Pettersson-Yeo, William; Crossley, Nicolas; Yang, Xun; Li, Jing; Huang, Xiaoqi; Mechelli, Andrea

    2014-01-01

    Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level. Resting-state functional MRI data was acquired for 121 survivors of the 2008 Sichuan earthquake each of whom was assessed for symptoms of post-traumatic stress disorder (PTSD) using the 17-item PTSD Checklist (PCL). Using a multivariate analytical method known as relevance vector regression (RVR), we examined the relationship between resting-state functional MRI data and symptom scores. We found that the use of RVR allowed quantitative prediction of clinical scores with statistically significant accuracy (correlation=0.32, P=0.006; mean squared error=176.88, P=0.001). Accurate prediction was based on functional activation in a number of prefrontal, parietal, and occipital regions. This is the first evidence that neuroimaging techniques may inform the clinical assessment of trauma-exposed individuals by providing an accurate and objective quantitative estimation of psychopathology. Furthermore, the significant contribution of parietal and occipital regions to such estimation challenges the traditional view of PTSD as a disorder specific to the fronto-limbic network. PMID:24064470

  9. Prediction of the period of psychotic episode in individual schizophrenics by simulation-data construction approach.

    PubMed

    Huang, Chun-Jung; Wang, Hsiao-Fan; Chiu, Hsien-Jane; Lan, Tsuo-Hung; Hu, Tsung-Ming; Loh, El-Wui

    2010-10-01

    Although schizophrenia can be treated, most patients still experience inevitable psychotic episodes from time to time. Precautious actions can be taken if the next onset can be predicted. However, sufficient information is always lacking in the clinical scenario. A possible solution is to use the virtual data generated from limited of original data. Data construction method (DCM) has been shown to generate the virtual felt earthquake data effectively and used in the prediction of further events. Here we investigated the performance of DCM in deriving the membership functions and discrete-event simulations (DES) in predicting the period embracing the initiation and termination time-points of the next psychotic episode of 35 individual schizophrenic patients. The results showed that 21 subjects had a success of simulations (RSS) ≥70%. Further analysis demonstrated that the co-morbidity of coronary heart diseases (CHD), risks of CHD, and the frequency of previous psychotic episodes increased the RSS.

  10. Modelling and Bayesian adaptive prediction of individual patients' tumour volume change during radiotherapy.

    PubMed

    Tariq, Imran; Chen, Tao; Kirkby, Norman F; Jena, Rajesh

    2016-03-07

    The aim of this study is to develop a mathematical modelling method that can predict individual patients’ response to radiotherapy, in terms of tumour volume change during the treatment. The main concept is to start from a population-average model, which is subsequently updated from an individual’s tumour volume measurement. The model becomes increasingly personalized and so too does the prediction it produces. This idea of adaptive prediction was realised by using a Bayesian approach for updating the model parameters. The feasibility of the developed method was demonstrated on the data from 25 non-small cell lung cancer patients treated with helical tomotherapy, during which tumour volume was measured from daily imaging as part of the image-guided radiotherapy. The method could provide useful information for adaptive treatment planning and dose scheduling based on the patient’s personalised response.

  11. An individual-specific gait pattern prediction model based on generalized regression neural networks.

    PubMed

    Luu, Trieu Phat; Low, K H; Qu, Xingda; Lim, H B; Hoon, K H

    2014-01-01

    Robotics is gaining its popularity in gait rehabilitation. Gait pattern planning is important to ensure that the gait patterns induced by robotic systems are tailored to each individual and varying walking speed. Most research groups planned gait patterns for their robotics systems based on Clinical Gait Analysis (CGA) data. The major problem with the method using the CGA data is that it cannot accommodate inter-subject differences. In addition, CGA data is limited to only one walking speed as per the published data. The objective of this work was to develop an individual-specific gait pattern prediction model for gait pattern planning in the robotic gait rehabilitation systems. The waveforms of lower limb joint angles in the sagittal plane during walking were obtained with a motion capture system. Each waveform was represented and reconstructed by a Fourier coefficient vector which consisted of eleven elements. Generalized regression neural networks (GRNNs) were designed to predict Fourier coefficient vectors from given gait parameters and lower limb anthropometric data. The generated waveforms from the predicted Fourier coefficient vectors were compared to the actual waveforms and CGA waveforms by using the assessment parameters of correlation coefficients, mean absolute deviation (MAD) and threshold absolute deviation (TAD). The results showed that lower limb joint angle waveforms generated by the gait pattern prediction model were closer to the actual waveforms compared to the CGA waveforms. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Prediction of individual response to antidepressants and antipsychotics: an integrated concept

    PubMed Central

    Preskorn, Sheldon H.

    2014-01-01

    In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response—whether beneficial or adverse—to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed. PMID:25733958

  13. Biomarkers of cardiovascular disease: contributions to risk prediction in individuals with diabetes.

    PubMed

    Bachmann, Katherine N; Wang, Thomas J

    2017-09-28

    Cardiovascular disease is a leading cause of death, especially in individuals with diabetes mellitus, whose risk of morbidity and mortality due to cardiovascular disease is markedly increased compared with the general population. There has been growing interest in the identification of biomarkers of cardiovascular disease in people with diabetes. The present review focuses on the current and potential contributions of these biomarkers to predicting cardiovascular risk in individuals with diabetes. At present, certain biomarkers and biomarker combinations can lead to modest improvements in the prediction of cardiovascular disease in diabetes beyond traditional cardiovascular risk factors. Emerging technologies may enable the discovery of novel biomarkers and generate new information about known biomarkers (such as new combinations of biomarkers), which could lead to significant improvements in cardiovascular disease risk prediction. A critical question, however, is whether improvements in risk prediction will affect processes of care and decision making in clinical practice, as this will be required to achieve the ultimate goal of improving clinical outcomes in diabetes.

  14. Prediction of individual response to antidepressants and antipsychotics: an integrated concept.

    PubMed

    Preskorn, Sheldon H

    2014-12-01

    In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response--whether beneficial or adverse--to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed.

  15. Individual differences in electrophysiological responses to performance feedback predict AB magnitude.

    PubMed

    MaClean, Mary H; Arnell, Karen M

    2013-06-01

    The attentional blink (AB) is observed when report accuracy for a second target (T2) is reduced if T2 is presented within approximately 500 ms of a first target (T1), but accuracy is relatively unimpaired at longer T1-T2 separations. The AB is thought to represent a transient cost of attending to a target, and reliable individual differences have been observed in its magnitude. Some models of the AB have suggested that cognitive control contributes to production of the AB, such that greater cognitive control is associated with larger AB magnitudes. Performance-monitoring functions are thought to modulate the strength of cognitive control, and those functions are indexed by event-related potentials in response to both endogenous and exogenous performance evaluation. Here we examined whether individual differences in the amplitudes to internal and external response feedback predict individual AB magnitudes. We found that electrophysiological responses to externally provided performance feedback, measured in two different tasks, did predict individual differences in AB magnitude, such that greater feedback-related N2 amplitudes were associated with larger AB magnitudes, regardless of the valence of the feedback.

  16. Gut Microbiota Signatures Predict Host and Microbiota Responses to Dietary Interventions in Obese Individuals

    PubMed Central

    Korpela, Katri; Flint, Harry J.; Johnstone, Alexandra M.; Lappi, Jenni; Poutanen, Kaisa; Dewulf, Evelyne; Delzenne, Nathalie; de Vos, Willem M.; Salonen, Anne

    2014-01-01

    Background Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host. Methodology Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set – test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters. Principal Findings Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77–1; predicted vs. observed correlation  =  0.67–0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health. Conclusion This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of

  17. Explaining growth of individual trees: Light interception and efficiency of light use by Eucalyptus at four sites in Brazil

    Treesearch

    Dan Binkley; Jose Luiz Stape; William L. Bauerle; Michael G. Ryan

    2010-01-01

    The growth of wood in trees and forests depends on the acquisition of resources (light, water, and nutrients), the efficiency of using resources for photosynthesis, and subsequent partitioning to woody tissues. Patterns of efficiency over time for individual trees, or between trees at one time, result from changes in rates photosynthesis and shifts in...

  18. Early Improvements in Individual Symptoms to Predict Later Remission in Major Depressive Disorder Treated With Mirtazapine.

    PubMed

    Funaki, Kei; Nakajima, Shinichiro; Suzuki, Takefumi; Mimura, Masaru; Uchida, Hiroyuki

    2016-09-01

    Few studies, to our knowledge, have examined whether early improvements in individual, instead of overall, depressive symptoms predict remission in major depressive disorder (MDD). This post hoc analysis used data from 194 patients with MDD enrolled in a 6-week double-blind, placebo-controlled, randomized trial of mirtazapine, to identify improvements in specific individual depressive symptoms in the early phase that are associated with subsequent remission. Trajectories of individual depressive symptoms over 6 weeks were compared between remitters and nonremitters. Early improvement was defined as a ≥20% decrease in the Hamilton Rating Scale for Depression 17 items (HAM-D17) total score in weeks 1 and 2, and remission was defined as a HAM-D17 final score of ≤7. Reliability parameters were calculated for early improvements in predicting later remission. Whether improvement in each of the HAM-D17 symptoms in weeks 1 or 2 predicted remission was examined, using binary logistic regression analyses. As a result, improvements in weeks 1 and 2 were associated with sensitivity of 0.82 and 0.99 and specificity of 0.54 and 0.44, respectively, in predicting remission in week 6. Improvements in insomnia late (P = .04) and insight (P = .007) in week 1 and somatic symptoms general (P = .002) and insight (P = .04) in week 2 were associated with remission in week 6. In conclusion, early improvements in insight, insomnia late, and somatic symptoms general, as well as overall depressive symptoms, may serve as specific clinical indicators of subsequent remission in patients with MDD receiving mirtazapine. © 2016, The American College of Clinical Pharmacology.

  19. Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data

    NASA Astrophysics Data System (ADS)

    Kandare, Kaja; Ørka, Hans Ole; Dalponte, Michele; Næsset, Erik; Gobakken, Terje

    2017-08-01

    Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI

  20. Human brain structure predicts individual differences in preconscious evaluation of facial dominance and trustworthiness

    PubMed Central

    Kanai, Ryota; Bahrami, Bahador; Rees, Geraint

    2015-01-01

    Social cues conveyed by the human face, such as eye gaze direction, are evaluated even before they are consciously perceived. While there is substantial individual variability in such evaluation, its neural basis is unknown. Here we asked whether individual differences in preconscious evaluation of social face traits were associated with local variability in brain structure. Adult human participants (n = 36) monocularly viewed faces varying in dominance and trustworthiness, which were suppressed from awareness by a dynamic noise pattern shown to the other eye. The time taken for faces to emerge from suppression and become visible (t2e) was used as a measure of potency in competing for visual awareness. Both dominant and untrustworthy faces resulted in slower t2e than neutral faces, with substantial individual variability in these effects. Individual differences in t2e were correlated with gray matter volume in right insula for dominant faces, and with gray matter volume in medial prefrontal cortex, right temporoparietal junction and bilateral fusiform face area for untrustworthy faces. Thus, individual differences in preconscious social processing can be predicted from local brain structure, and separable correlates for facial dominance and untrustworthiness suggest distinct mechanisms of preconscious processing. PMID:25193945

  1. Human brain structure predicts individual differences in preconscious evaluation of facial dominance and trustworthiness.

    PubMed

    Getov, Spas; Kanai, Ryota; Bahrami, Bahador; Rees, Geraint

    2015-05-01

    Social cues conveyed by the human face, such as eye gaze direction, are evaluated even before they are consciously perceived. While there is substantial individual variability in such evaluation, its neural basis is unknown. Here we asked whether individual differences in preconscious evaluation of social face traits were associated with local variability in brain structure. Adult human participants (n = 36) monocularly viewed faces varying in dominance and trustworthiness, which were suppressed from awareness by a dynamic noise pattern shown to the other eye. The time taken for faces to emerge from suppression and become visible (t2e) was used as a measure of potency in competing for visual awareness. Both dominant and untrustworthy faces resulted in slower t2e than neutral faces, with substantial individual variability in these effects. Individual differences in t2e were correlated with gray matter volume in right insula for dominant faces, and with gray matter volume in medial prefrontal cortex, right temporoparietal junction and bilateral fusiform face area for untrustworthy faces. Thus, individual differences in preconscious social processing can be predicted from local brain structure, and separable correlates for facial dominance and untrustworthiness suggest distinct mechanisms of preconscious processing. © The Author (2014). Published by Oxford University Press.

  2. Probing photo-carrier collection efficiencies of individual silicon nanowire diodes on a wafer substrate

    NASA Astrophysics Data System (ADS)

    Schmitt, S. W.; Brönstrup, G.; Shalev, G.; Srivastava, S. K.; Bashouti, M. Y.; Döhler, G. H.; Christiansen, S. H.

    2014-06-01

    Vertically aligned silicon nanowire (SiNW) diodes are promising candidates for the integration into various opto-electronic device concepts for e.g. sensing or solar energy conversion. Individual SiNW p-n diodes have intensively been studied, but to date an assessment of their device performance once integrated on a silicon substrate has not been made. We show that using a scanning electron microscope (SEM) equipped with a nano-manipulator and an optical fiber feed-through for tunable (wavelength, power using a tunable laser source) sample illumination, the dark and illuminated current-voltage (I-V) curve of individual SiNW diodes on the substrate wafer can be measured. Surprisingly, the I-V-curve of the serially coupled system composed of SiNW/wafers is accurately described by an equivalent circuit model of a single diode and diode parameters like series and shunting resistivity, diode ideality factor and photocurrent can be retrieved from a fit. We show that the photo-carrier collection efficiency (PCE) of the integrated diode illuminated with variable wavelength and intensity light directly gives insight into the quality of the device design at the nanoscale. We find that the PCE decreases for high light intensities and photocurrent densities, due to the fact that considerable amounts of photo-excited carriers generated within the substrate lead to a decrease in shunting resistivity of the SiNW diode and deteriorate its rectification. The PCE decreases systematically for smaller wavelengths of visible light, showing the possibility of monitoring the effectiveness of the SiNW device surface passivation using the shown measurement technique. The integrated device was pre-characterized using secondary ion mass spectrometry (SIMS), TCAD simulations and electron beam induced current (EBIC) measurements to validate the properties of the characterized material at the single SiNW diode level.Vertically aligned silicon nanowire (SiNW) diodes are promising candidates for

  3. Predicting energy expenditure through hand rim propulsion power output in individuals who use wheelchairs.

    PubMed

    Conger, Scott A; Scott, Stacy N; Bassett, David R

    2014-07-01

    To examine the relationship between hand rim propulsion power and energy expenditure (EE) during wheelchair wheeling and to investigate whether adding other variables to the model could improve on the prediction of EE. Individuals who use manual wheelchairs (n=14) performed five different wheeling activities in a wheelchair with a PowerTap power meter hub built into the right rear wheel. Activities included wheeling on a smooth, level surface at three different speeds (4.5, 5.5 and 6.5 km/h), wheeling on a rubberised track at one speed (5.5 km/h) and wheeling on a sidewalk course that included uphill and downhill segments at a self-selected speed. EE was measured using a portable indirect calorimetry system. Stepwise linear regression was performed to predict EE from power output variables. A repeated-measures analysis of variance was used to compare the measured EE to the estimates from the power models. Bland-Altman plots were used to assess the agreement between the criterion values and the predicted values. EE and power were significantly correlated (r=0.694, p<0.001). Regression analysis yielded three significant prediction models utilising measured power; measured power and speed; and measured power, speed and heart rate. No significant differences were found between measured EE and any of the prediction models. EE can be accurately and precisely estimated based on hand rim propulsion power. These results indicate that power could be used as a method to assess EE in individuals who use wheelchairs. 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.

  4. Developing and validating risk prediction models in an individual participant data meta-analysis

    PubMed Central

    2014-01-01

    Background Risk prediction models estimate the risk of developing future outcomes for individuals based on one or more underlying characteristics (predictors). We review how researchers develop and validate risk prediction models within an individual participant data (IPD) meta-analysis, in order to assess the feasibility and conduct of the approach. Methods A qualitative review of the aims, methodology, and reporting in 15 articles that developed a risk prediction model using IPD from multiple studies. Results The IPD approach offers many opportunities but methodological challenges exist, including: unavailability of requested IPD, missing patient data and predictors, and between-study heterogeneity in methods of measurement, outcome definitions and predictor effects. Most articles develop their model using IPD from all available studies and perform only an internal validation (on the same set of data). Ten of the 15 articles did not allow for any study differences in baseline risk (intercepts), potentially limiting their model’s applicability and performance in some populations. Only two articles used external validation (on different data), including a novel method which develops the model on all but one of the IPD studies, tests performance in the excluded study, and repeats by rotating the omitted study. Conclusions An IPD meta-analysis offers unique opportunities for risk prediction research. Researchers can make more of this by allowing separate model intercept terms for each study (population) to improve generalisability, and by using ‘internal-external cross-validation’ to simultaneously develop and validate their model. Methodological challenges can be reduced by prospectively planned collaborations that share IPD for risk prediction. PMID:24397587

  5. Predicting individual contrast sensitivity functions from acuity and letter contrast sensitivity measurements

    PubMed Central

    Thurman, Steven M.; Davey, Pinakin Gunvant; McCray, Kaydee Lynn; Paronian, Violeta; Seitz, Aaron R.

    2016-01-01

    Contrast sensitivity (CS) is widely used as a measure of visual function in both basic research and clinical evaluation. There is conflicting evidence on the extent to which measuring the full contrast sensitivity function (CSF) offers more functionally relevant information than a single measurement from an optotype CS test, such as the Pelli–Robson chart. Here we examine the relationship between functional CSF parameters and other measures of visual function, and establish a framework for predicting individual CSFs with effectively a zero-parameter model that shifts a standard-shaped template CSF horizontally and vertically according to independent measurements of high contrast acuity and letter CS, respectively. This method was evaluated for three different CSF tests: a chart test (CSV-1000), a computerized sine-wave test (M&S Sine Test), and a recently developed adaptive test (quick CSF). Subjects were 43 individuals with healthy vision or impairment too mild to be considered low vision (acuity range of −0.3 to 0.34 logMAR). While each test demands a slightly different normative template, results show that individual subject CSFs can be predicted with roughly the same precision as test–retest repeatability, confirming that individuals predominantly differ in terms of peak CS and peak spatial frequency. In fact, these parameters were sufficiently related to empirical measurements of acuity and letter CS to permit accurate estimation of the entire CSF of any individual with a deterministic model (zero free parameters). These results demonstrate that in many cases, measuring the full CSF may provide little additional information beyond letter acuity and contrast sensitivity. PMID:28006065

  6. Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

    PubMed Central

    Mourao-Miranda, J.; Reinders, A. A. T. S.; Rocha-Rego, V.; Lappin, J.; Rondina, J.; Morgan, C.; Morgan, K. D.; Fearon, P.; Jones, P. B.; Doody, G. A.; Murray, R. M.; Kapur, S.; Dazzan, P.

    2012-01-01

    Background To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. Method One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. Results At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). Conclusions We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data. PMID:22059690

  7. Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

    PubMed

    Mourao-Miranda, J; Reinders, A A T S; Rocha-Rego, V; Lappin, J; Rondina, J; Morgan, C; Morgan, K D; Fearon, P; Jones, P B; Doody, G A; Murray, R M; Kapur, S; Dazzan, P

    2012-05-01

    To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.

  8. Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach

    NASA Astrophysics Data System (ADS)

    Rockne, R.; Rockhill, J. K.; Mrugala, M.; Spence, A. M.; Kalet, I.; Hendrickson, K.; Lai, A.; Cloughesy, T.; Alvord, E. C., Jr.; Swanson, K. R.

    2010-06-01

    Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as gliomas. They proliferate and invade extensively and yield short life expectancies despite aggressive treatment. Response to treatment is usually measured in terms of the survival of groups of patients treated similarly, but this statistical approach misses the subgroups that may have responded to or may have been injured by treatment. Such statistics offer scant reassurance to individual patients who have suffered through these treatments. Furthermore, current imaging-based treatment response metrics in individual patients ignore patient-specific differences in tumor growth kinetics, which have been shown to vary widely across patients even within the same histological diagnosis and, unfortunately, these metrics have shown only minimal success in predicting patient outcome. We consider nine newly diagnosed GBM patients receiving diagnostic biopsy followed by standard-of-care external beam radiation therapy (XRT). We present and apply a patient-specific, biologically based mathematical model for glioma growth that quantifies response to XRT in individual patients in vivo. The mathematical model uses net rates of proliferation and migration of malignant tumor cells to characterize the tumor's growth and invasion along with the linear-quadratic model for the response to radiation therapy. Using only routinely available pre-treatment MRIs to inform the patient-specific bio-mathematical model simulations, we find that radiation response in these patients, quantified by both clinical and model-generated measures, could have been predicted prior to treatment with high accuracy. Specifically, we find that the net proliferation rate is correlated with the radiation response parameter (r = 0.89, p = 0.0007), resulting in a predictive relationship that is tested with a leave-one-out cross-validation technique. This relationship predicts the tumor size post-therapy to within inter

  9. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell

    2011-01-01

    Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

  10. Stereotyped behaviors predicting self-injurious behavior in individuals with intellectual disabilities.

    PubMed

    Barnard-Brak, Lucy; Rojahn, Johannes; Richman, David M; Chesnut, Steven R; Wei, Tianlan

    2014-11-11

    We examined the relation between stereotyped behavior and self-injurious behavior (SIB) for 1871 individuals with intellectual disabilities who had a score of >0 on the Behavior Problem Inventory (BPI-01; Rojahn et al., 2001). We report three main findings: First, structural equation modeling techniques (SEM) revealed that the BPI-01stereotyped behavior subscale scores predicted BPI-01 SIB subscale scores. Second, when stereotyped behavior was modeled as a predictor of SIB, mixture-modeling techniques revealed two groups of individuals: one in which stereotyped behavior was a strong, statistically significant predictor of SIB (69% of the sample), and another one in which stereotyped behavior was not a predictor of SIB (31%). Finally, two specific stereotyped behavior topographies (i.e., body rocking and yelling) were identified that significantly predicted five different SIB topographies (i.e., self-biting, head hitting, body hitting, self-pinching, and hair pulling). Results are discussed in terms of future research needed to identify bio-behavioral variables correlated with cases of SIB that can, and cannot, be predicted by the presence of stereotyped behavior.

  11. Assessing Risk Prediction Models Using Individual Participant Data From Multiple Studies

    PubMed Central

    Pennells, Lisa; Kaptoge, Stephen; White, Ian R.; Thompson, Simon G.; Wood, Angela M.; Tipping, Robert W.; Folsom, Aaron R.; Couper, David J.; Ballantyne, Christie M.; Coresh, Josef; Goya Wannamethee, S.; Morris, Richard W.; Kiechl, Stefan; Willeit, Johann; Willeit, Peter; Schett, Georg; Ebrahim, Shah; Lawlor, Debbie A.; Yarnell, John W.; Gallacher, John; Cushman, Mary; Psaty, Bruce M.; Tracy, Russ; Tybjærg-Hansen, Anne; Price, Jackie F.; Lee, Amanda J.; McLachlan, Stela; Khaw, Kay-Tee; Wareham, Nicholas J.; Brenner, Hermann; Schöttker, Ben; Müller, Heiko; Jansson, Jan-Håkan; Wennberg, Patrik; Salomaa, Veikko; Harald, Kennet; Jousilahti, Pekka; Vartiainen, Erkki; Woodward, Mark; D'Agostino, Ralph B.; Bladbjerg, Else-Marie; Jørgensen, Torben; Kiyohara, Yutaka; Arima, Hisatomi; Doi, Yasufumi; Ninomiya, Toshiharu; Dekker, Jacqueline M.; Nijpels, Giel; Stehouwer, Coen D. A.; Kauhanen, Jussi; Salonen, Jukka T.; Meade, Tom W.; Cooper, Jackie A.; Cushman, Mary; Folsom, Aaron R.; Psaty, Bruce M.; Shea, Steven; Döring, Angela; Kuller, Lewis H.; Grandits, Greg; Gillum, Richard F.; Mussolino, Michael; Rimm, Eric B.; Hankinson, Sue E.; Manson, JoAnn E.; Pai, Jennifer K.; Kirkland, Susan; Shaffer, Jonathan A.; Shimbo, Daichi; Bakker, Stephan J. L.; Gansevoort, Ron T.; Hillege, Hans L.; Amouyel, Philippe; Arveiler, Dominique; Evans, Alun; Ferrières, Jean; Sattar, Naveed; Westendorp, Rudi G.; Buckley, Brendan M.; Cantin, Bernard; Lamarche, Benoît; Barrett-Connor, Elizabeth; Wingard, Deborah L.; Bettencourt, Richele; Gudnason, Vilmundur; Aspelund, Thor; Sigurdsson, Gunnar; Thorsson, Bolli; Kavousi, Maryam; Witteman, Jacqueline C.; Hofman, Albert; Franco, Oscar H.; Howard, Barbara V.; Zhang, Ying; Best, Lyle; Umans, Jason G.; Onat, Altan; Sundström, Johan; Michael Gaziano, J.; Stampfer, Meir; Ridker, Paul M.; Michael Gaziano, J.; Ridker, Paul M.; Marmot, Michael; Clarke, Robert; Collins, Rory; Fletcher, Astrid; Brunner, Eric; Shipley, Martin; Kivimäki, Mika; Ridker, Paul M.; Buring, Julie; Cook, Nancy; Ford, Ian; Shepherd, James; Cobbe, Stuart M.; Robertson, Michele; Walker, Matthew; Watson, Sarah; Alexander, Myriam; Butterworth, Adam S.; Angelantonio, Emanuele Di; Gao, Pei; Haycock, Philip; Kaptoge, Stephen; Pennells, Lisa; Thompson, Simon G.; Walker, Matthew; Watson, Sarah; White, Ian R.; Wood, Angela M.; Wormser, David; Danesh, John

    2014-01-01

    Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous. PMID:24366051

  12. A physiologically-based model to predict individual pharmacokinetics and pharmacodynamics of remifentanil.

    PubMed

    Cascone, Sara; Lamberti, Gaetano; Piazza, Ornella; Abbiati, Roberto Andrea; Manca, Davide

    2017-09-20

    Remifentanil based anesthesia is nowadays spread worldwide. This drug is characterized by a rapid onset of the analgesic effects, but also by a rapid onset of the side effects. For this reason, the knowledge of the remifentanil concentration in the human body is a key topic in anesthesiology. The aims of this work are to propose and validate a physiologically based pharmacokinetic model capable to predict both the pharmacokinetics and pharmacodynamics of remifentanil, and to take into account the inter-individual differences among the patients (such as height and body mass). The blood concentration of remifentanil has been successfully simulated and compared with experimental literature data. The pharmacodynamics, in terms of effect of remifentanil on minute ventilation and electroencephalogram, has been implemented in this model. Moreover, the remifentanil concentration in various organs and tissues is predicted, which is a significant improvement with respect to the traditional compartmental models. The availability of the model makes possible the prediction of the effects of remifentanil administration, also accounting for individual parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Assessing risk prediction models using individual participant data from multiple studies.

    PubMed

    Pennells, Lisa; Kaptoge, Stephen; White, Ian R; Thompson, Simon G; Wood, Angela M

    2014-03-01

    Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

  14. A data envelope analysis to assess factors affecting technical and economic efficiency of individual broiler breeder hens.

    PubMed

    Romero, L F; Zuidhof, M J; Jeffrey, S R; Naeima, A; Renema, R A; Robinson, F E

    2010-08-01

    This study evaluated the effect of feed allocation and energetic efficiency on technical and economic efficiency of broiler breeder hens using the data envelope analysis methodology and quantified the effect of variables affecting technical efficiency. A total of 288 Ross 708 pullets were placed in individual cages at 16 wk of age and assigned to 1 of 4 feed allocation groups. Three of them had feed allocated on a group basis with divergent BW targets: standard, high (standard x 1.1), and low (standard x 0.9). The fourth group had feed allocated on an individual bird basis following the standard BW target. Birds were classified in 3 energetic efficiency categories: low, average, and high, based on estimated maintenance requirements. Technical efficiency considered saleable chicks as output and cumulative ME intake and time as inputs. Economic efficiency of feed allocation treatments was analyzed under different cost scenarios. Birds with low feed allocation exhibited a lower technical efficiency (69.4%) than standard (72.1%), which reflected a reduced egg production rate. Feed allocation of the high treatment could have been reduced by 10% with the same chick production as the standard treatment. The low treatment exhibited reduced economic efficiency at greater capital costs, whereas high had reduced economic efficiency at greater feed costs. The average energetic efficiency hens had a lower technical efficiency in the low compared with the standard feed allocation. A 1% increment in estimated maintenance requirement changed technical efficiency by -0.23%, whereas a 1% increment in ME intake had a -0.47% effect. The negative relationship between technical efficiency and ME intake was counterbalanced by a positive correlation of ME intake and egg production. The negative relationship of technical efficiency and maintenance requirements was synergized by a negative correlation of hen maintenance and egg production. Economic efficiency methodologies are effective

  15. Individual differences in cognitive style and strategy predict similarities in the patterns of brain activity between individuals.

    PubMed

    Miller, Michael B; Donovan, Christa-Lynn; Bennett, Craig M; Aminoff, Elissa M; Mayer, Richard E

    2012-01-02

    Neuroimaging is being used increasingly to make inferences about an individual. Yet, those inferences are often confounded by the fact that topographical patterns of task-related brain activity can vary greatly from person to person. This study examined two factors that may contribute to the variability across individuals in a memory retrieval task: individual differences in cognitive style and individual differences in encoding strategy. Cognitive style was probed using a battery of assessments focused on the individual's tendency to visualize or verbalize written material. Encoding strategy was probed using a series of questions designed to assess typical strategies that an individual might utilize when trying to remember a list of words. Similarity in brain activity was assessed by cross-correlating individual t-statistic maps contrasting the BOLD response during retrieval to the BOLD response during fixation. Individual differences in cognitive style and encoding strategy accounted for a significant portion of the variance in similarity. This was true above and beyond individual differences in anatomy and memory performance. These results demonstrate the need for a multidimensional approach in the use of fMRI to make inferences about an individual.

  16. Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

    PubMed

    Will, Sebastian; Jabbari, Hosna

    2016-01-01

    RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

  17. Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.

    PubMed

    Redlich, Ronny; Opel, Nils; Grotegerd, Dominik; Dohm, Katharina; Zaremba, Dario; Bürger, Christian; Münker, Sandra; Mühlmann, Lisa; Wahl, Patricia; Heindel, Walter; Arolt, Volker; Alferink, Judith; Zwanzger, Peter; Zavorotnyy, Maxim; Kugel, Harald; Dannlowski, Udo

    2016-06-01

    Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified. To investigate whether certain factors identified by structural magnetic resonance imaging (MRI) techniques are able to predict ECT response. In this nonrandomized prospective study, gray matter structure was assessed twice at approximately 6 weeks apart using 3-T MRI and voxel-based morphometry. Patients were recruited through the inpatient service of the Department of Psychiatry, University of Muenster, from March 11, 2010, to March 27, 2015. Two patient groups with acute major depressive disorder were included. One group received an ECT series in addition to antidepressants (n = 24); a comparison sample was treated solely with antidepressants (n = 23). Both groups were compared with a sample of healthy control participants (n = 21). Binary pattern classification was used to predict ECT response by structural MRI that was performed before treatment. In addition, univariate analysis was conducted to predict reduction of the Hamilton Depression Rating Scale score by pretreatment gray matter volumes and to investigate ECT-related structural changes. One participant in the ECT sample was excluded from the analysis, leaving 67 participants (27 men and 40 women; mean [SD] age, 43.7 [10.6] years). The binary pattern classification yielded a successful prediction of ECT response, with accuracy rates of 78.3% (18 of 23 patients in the ECT sample) and sensitivity rates of 100% (13 of 13 who responded to ECT). Furthermore, a support vector regression yielded a significant prediction of relative reduction in the Hamilton Depression Rating Scale score. The principal findings of the univariate model indicated a positive association between pretreatment subgenual cingulate volume and individual ECT response (Montreal Neurological Institute [MNI] coordinates x = 8, y = 21, z = -18

  18. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

    PubMed Central

    Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

    2015-01-01

    As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras. PMID:26370997

  19. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

    PubMed

    Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

    2015-09-08

    As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

  20. Can the prognosis of individual patients with glioblastoma be predicted using an online calculator?

    PubMed Central

    Parks, Christopher; Heald, James; Hall, Gregory; Kamaly-Asl, Ian

    2013-01-01

    Background In an exploratory subanalysis of the European Organisation for Research and Treatment of Cancer and National Cancer Institute of Canada (EORTC/NCIC) trial data, Gorlia et al. identified a variety of factors that were predictive of overall survival, including therapy administered, age, extent of surgery, mini-mental score, administration of corticosteroids, World Health Organization (WHO) performance status, and O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Gorlia et al. developed 3 nomograms, each intended to predict the survival times of patients with newly diagnosed glioblastoma on the basis of individual-specific combinations of prognostic factors. These are available online as a “GBM Calculator” and are intended for use in patient counseling. This study is an external validation of this calculator. Method One hundred eighty-seven patients from 2 UK neurosurgical units who had histologically confirmed glioblastoma (WHO grade IV) had their information at diagnosis entered into the GBM calculator. A record was made of the actual and predicted median survival time for each patient. Statistical analysis was performed to assess the accuracy, precision, correlation, and discrimination of the calculator. Results The calculator gives both inaccurate and imprecise predictions. Only 23% of predictions were within 25% of the actual survival, and the percentage bias is 140% in our series. The coefficient of variance is 76%, where a smaller percentage would indicate greater precision. There is only a weak positive correlation between the predicted and actual survival among patients (R2 of 0.07). Discrimination is inadequate as measured by a C-index of 0.62. Conclusions The authors would not recommend the use of this tool in patient counseling. If departments were considering its use, we would advise that a similar validating exercise be undertaken. PMID:23543729

  1. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

    PubMed

    Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

    2015-01-01

    Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

  2. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy

    PubMed Central

    Barron, Daniel S.; Fox, Peter T.; Pardoe, Heath; Lancaster, Jack; Price, Larry R.; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E.; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

    2014-01-01

    Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses. PMID:25610790

  3. Amygdala subregional structure and intrinsic functional connectivity predicts individual differences in anxiety during early childhood.

    PubMed

    Qin, Shaozheng; Young, Christina B; Duan, Xujun; Chen, Tianwen; Supekar, Kaustubh; Menon, Vinod

    2014-06-01

    Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during a period in early childhood when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety. We combined structural and functional magnetic resonance imaging with neuropsychological assessments of anxiety based on daily life experiences to investigate the effects of anxiety on the brain in 76 young children. We then used machine learning algorithms with balanced cross-validation to examine brain-based predictors of individual differences in childhood anxiety. Even in children as young as ages 7 to 9, high childhood anxiety is associated with enlarged amygdala volume and this enlargement is localized specifically to the basolateral amygdala. High childhood anxiety is also associated with increased connectivity between the amygdala and distributed brain systems involved in attention, emotion perception, and regulation, and these effects are most prominent in basolateral amygdala. Critically, machine learning algorithms revealed that levels of childhood anxiety could be reliably predicted by amygdala morphometry and intrinsic functional connectivity, with the left basolateral amygdala emerging as the strongest predictor. Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age. Our study provides important new insights into the neurodevelopmental origins of anxiety and has significant implications for the development of predictive biomarkers to identify children at risk for anxiety disorders. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

  4. Amgydala subregional structure and intrinsic functional connectivity predicts individual differences in anxiety during early childhood

    PubMed Central

    Qin, Shaozheng; Young, Christina B; Duan, Xujun; Chen, Tianwen; Supekar, Kaustubh; Menon, Vinod

    2013-01-01

    Background Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during early childhood – a period when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety. Methods We combined structural and functional magnetic resonance imaging (fMRI) with neuropsychological assessment of anxiety based on daily life experiences to investigate the effects of anxiety on the brain in seventy-six young children. We then used machine learning algorithms with balanced cross-validation to examine brain-based predictors of individual differences in childhood anxiety. Results Even in children as young as ages 7–9, high childhood anxiety is associated with enlarged amygdala volume and this enlargement is localized specifically to the basolateral amygdala. High childhood anxiety is also associated with increased connectivity between the amygdala and distributed brain systems involved in attention, emotion perception and regulation, and these effects are most prominent effect in basolateral amygdala. Critically, machine learning algorithms revealed that levels of childhood anxiety could be reliably predicted by amygdala morphometry and intrinsic functional connectivity, with the left basolateral amygdala emerging again as the strongest predictor. Conclusions Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age. Our study provides important new insights into the neurodevelopmental origins of anxiety, and has significant implications for the development of predictive biomarkers to identify children at-risk for anxiety disorders. PMID:24268662

  5. Lower than predicted resting metabolic rate is associated with severely impaired cardiorespiratory fitness in obese individuals.

    PubMed

    Miller, Wendy M; Spring, Thomas J; Zalesin, Kerstyn C; Kaeding, Kaylee R; Nori Janosz, Katherine E; McCullough, Peter A; Franklin, Barry A

    2012-03-01

    Obese individuals have reduced cardiorespiratory fitness as compared with leaner counterparts. Regular exercise maintains or increases fitness and lean body mass. Lean body mass, in turn, has a direct impact on resting metabolic rate (RMR). Given these relationships, we sought to evaluate the association between RMR and cardiorespiratory fitness in obese individuals. We evaluated 64 obese individuals (78% female) with direct assessment of RMR and cardiorespiratory fitness via breath-by-breath measurement of oxygen consumption and carbon dioxide production at rest and during exercise. The mean age and BMI were 47.4 ± 12.2 years and 47.2 ± 9.2 kg/m(2), respectively. The majority of subjects, 69%, had a measured RMR above that predicted by the Harris-Benedict equation. Compared with the higher RMR group, those with a lower than predicted RMR had increased BMI, with values of 52.9 vs. 44.7 kg/m(2), P = 0.001, respectively. Analysis of those demonstrating significant effort during cardiopulmonary exercise testing (peak respiratory exchange ratio ≥1.10) revealed a significantly higher peak oxygen uptake (VO(2) peak) in the higher RMR group (17.3 ± 3.5 ml/min/kg) compared with the lower RMR group (13.6 ± 1.9 ml/min/kg), P = 0.003. In summary, a lower than predicted RMR was associated with a severely reduced VO(2) peak and a higher BMI in this cohort. These data suggest that morbid obesity may be a vicious cycle of increasing BMI, reduced cardiorespiratory fitness, muscle deconditioning, and lower RMR. Collectively, these responses may, over time, exacerbate the imbalance between energy intake and expenditure, resulting in progressive increases in body weight and fat stores.

  6. The predictive nature of individual differences in early associative learning and emerging social behavior.

    PubMed

    Reeb-Sutherland, Bethany C; Levitt, Pat; Fox, Nathan A

    2012-01-01

    Across the first year of life, infants achieve remarkable success in their ability to interact in the social world. The hierarchical nature of circuit and skill development predicts that the emergence of social behaviors may depend upon an infant's early abilities to detect contingencies, particularly socially-relevant associations. Here, we examined whether individual differences in the rate of associative learning at one month of age is an enduring predictor of social, imitative, and discriminative behaviors measured across the human infant's first year. One-month learning rate was predictive of social behaviors at 5, 9, and 12 months of age as well as face-evoked discriminative neural activity at 9 months of age. Learning was not related to general cognitive abilities. These results underscore the importance of early contingency learning and suggest the presence of a basic mechanism underlying the ontogeny of social behaviors.

  7. Prediction Equations Overestimate the Energy Requirements More for Obesity-Susceptible Individuals.

    PubMed

    McLay-Cooke, Rebecca T; Gray, Andrew R; Jones, Lynnette M; Taylor, Rachael W; Skidmore, Paula M L; Brown, Rachel C

    2017-09-13

    Predictive equations to estimate resting metabolic rate (RMR) are often used in dietary counseling and by online apps to set energy intake goals for weight loss. It is critical to know whether such equations are appropriate for those susceptible to obesity. We measured RMR by indirect calorimetry after an overnight fast in 26 obesity susceptible (OSI) and 30 obesity resistant (ORI) individuals, identified using a simple 6-item screening tool. Predicted RMR was calculated using the FAO/WHO/UNU (Food and Agricultural Organisation/World Health Organisation/United Nations University), Oxford and Miflin-St Jeor equations. Absolute measured RMR did not differ significantly between OSI versus ORI (6339 vs. 5893 kJ·d(-1), p = 0.313). All three prediction equations over-estimated RMR for both OSI and ORI when measured RMR was ≤5000 kJ·d(-1). For measured RMR ≤7000 kJ·d(-1) there was statistically significant evidence that the equations overestimate RMR to a greater extent for those classified as obesity susceptible with biases ranging between around 10% to nearly 30% depending on the equation. The use of prediction equations may overestimate RMR and energy requirements particularly in those who self-identify as being susceptible to obesity, which has implications for effective weight management.

  8. Ten problems and solutions when predicting individual outcome from lesion site after stroke.

    PubMed

    Price, Cathy J; Hope, Thomas M; Seghier, Mohamed L

    2017-01-15

    In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Individual differences in response of dorsomedial prefrontal cortex predict daily social behavior

    PubMed Central

    Chavez, Robert S.; Heatherton, Todd F.

    2016-01-01

    The capacity to accurately infer the thoughts and intentions of other people is critical for effective social interaction, and neural activity in dorsomedial prefrontal cortex (dmPFC) has long been linked with the extent to which people engage in mental state attribution. In this study, we combined functional neuroimaging and experience sampling methodologies to test the predictive value of this neural response for daily social behaviors. We found that individuals who displayed greater activity in dmPFC when viewing social scenes spent more time around other people on a daily basis. These findings suggest a specific role for the neural mechanisms that support the capacity to mentalize in guiding individuals toward situations containing valuable social outcomes. PMID:26206505

  10. Verbal working memory predicts co-speech gesture: evidence from individual differences.

    PubMed

    Gillespie, Maureen; James, Ariel N; Federmeier, Kara D; Watson, Duane G

    2014-08-01

    Gesture facilitates language production, but there is debate surrounding its exact role. It has been argued that gestures lighten the load on verbal working memory (VWM; Goldin-Meadow, Nusbaum, Kelly, & Wagner, 2001), but gestures have also been argued to aid in lexical retrieval (Krauss, 1998). In the current study, 50 speakers completed an individual differences battery that included measures of VWM and lexical retrieval. To elicit gesture, each speaker described short cartoon clips immediately after viewing. Measures of lexical retrieval did not predict spontaneous gesture rates, but lower VWM was associated with higher gesture rates, suggesting that gestures can facilitate language production by supporting VWM when resources are taxed. These data also suggest that individual variability in the propensity to gesture is partly linked to cognitive capacities. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Verbal working memory predicts co-speech gesture: Evidence from individual differences

    PubMed Central

    Gillespie, Maureen; James, Ariel N.; Federmeier, Kara D.; Watson, Duane G.

    2014-01-01

    Gesture facilitates language production, but there is debate surrounding its exact role. It has been argued that gestures lighten the load on verbal working memory (VWM; Goldin-Meadow et al., 2001), but gestures have also been argued to aid in lexical retrieval (Krauss, 1998). In the current study, 50 speakers completed an individual differences battery that included measures of VWM and lexical retrieval. To elicit gesture, each speaker described short cartoon clips immediately after viewing. Measures of lexical retrieval did not predict spontaneous gesture rates, but lower VWM was associated with higher gesture rates, suggesting that gestures can facilitate language production by supporting VWM when resources are taxed. These data also suggest that individual variability in the propensity to gesture is partly linked to cognitive capacities. PMID:24813571

  12. Individual differences in (non-visual) processing style predict the face inversion effect.

    PubMed

    Wyer, Natalie A; Martin, Douglas; Pickup, Tracey; Macrae, C Neil

    2012-03-01

    Recent research suggests that individuals with relatively weak global precedence (i.e., a smaller propensity to view visual stimuli in a configural manner) show a reduced face inversion effect (FIE). Coupled with such findings, a number of recent studies have demonstrated links between an advantage for feature-based processing and the presentation of traits associated with autism among the general population. The present study sought to bridge these findings by investigating whether a relationship exists between the possession of autism-associated traits (i.e., as indicated by individuals'"autism quotient" [(AQ) and the size of the FIE. Participants completed an on-line study in which the AQ was measured prior to a standard face recognition task where half of the faces were inverted at test. The results confirmed that higher AQ levels were predictive of smaller FIEs. Implications for a common underlying factor relating to processing orientation are discussed.

  13. Pre-trauma individual differences in extinction learning predict posttraumatic stress.

    PubMed

    Lommen, Miriam J J; Engelhard, Iris M; Sijbrandij, Marit; van den Hout, Marcel A; Hermans, Dirk

    2013-02-01

    In the aftermath of a traumatic event, many people suffer from psychological distress, but only a minority develops posttraumatic stress disorder (PTSD). Pre-trauma individual differences in fear conditioning, most notably reduced extinction learning, have been proposed as playing an important role in the etiology of PTSD. However, prospective data are lacking. In this study, we prospectively tested whether reduced extinction was a predictor for later posttraumatic stress. Dutch soldiers (N = 249) were administered a conditioning task before their four-month deployment to Afghanistan to asses individual differences in extinction learning. After returning home, posttraumatic stress was measured. Results showed that reduced extinction learning before deployment predicted subsequent PTSD symptom severity, over and beyond degree of pre-deployment stress symptoms, neuroticism, and exposure to stressors on deployment. The findings suggest that reduced extinction learning may play a role in the development of PTSD.

  14. Acceleration response spectrum for prediction of structural vibration due to individual bouncing

    NASA Astrophysics Data System (ADS)

    Chen, Jun; Wang, Lei; Racic, Vitomir; Lou, Jiayue

    2016-08-01

    This study is designed to develop an acceleration response spectrum that can be used in vibration serviceability assessment of civil engineering structures, such as floors and grandstands those are dynamically excited by individual bouncing. The spectrum is derived from numerical simulations and statistical analysis of acceleration responses of a single degree of freedom system with variable natural frequency and damping under a large number of experimentally measured individual bouncing loads. Its mathematical representation is fit for fast yet reliable application in design practice and is comprised of three equations that describe three distinct frequency regions observed in the actual data: the first resonant plateau (2-3.5 Hz), the second resonant plateau (4-7 Hz) and a descension region (7-15 Hz). Finally, this paper verifies the proposed response spectrum approach to predict structural vibration by direct comparison against numerical simulations and experimental results.

  15. Resolving Anomalies in Predicting Electrokinetic Energy Conversion Efficiencies of Nanofluidic Devices

    PubMed Central

    Majumder, Sagardip; Dhar, Jayabrata; Chakraborty, Suman

    2015-01-01

    We devise a new approach for capturing complex interfacial interactions over reduced length scales, towards predicting electrokinetic energy conversion efficiencies of nanofluidic devices. By embedding several aspects of intermolecular interactions in continuum based formalism, we show that our simple theory becomes capable of representing complex interconnections between electro-mechanics and hydrodynamics over reduced length scales. The predictions from our model are supported by reported experimental data, and are in excellent quantitative agreement with molecular dynamics simulations. The present model, thus, may be employed to rationalize the discrepancies between low energy conversion efficiencies of nanofluidic channels that have been realized from experiments, and the impractically high energy conversion efficiencies that have been routinely predicted by the existing theories. PMID:26437925

  16. Individual Radiosensitivity Measured With Lymphocytes May Predict the Risk of Acute Reaction After Radiotherapy

    SciTech Connect

    Borgmann, Kerstin; Hoeller, Ulrike; Nowack, Sven; Bernhard, Michael; Roeper, Barbara; Brackrock, Sophie; Petersen, Cordula; Szymczak, Silke; Ziegler, Andreas; Feyer, Petra; Alberti, Winfried; Dikomey, Ekkehard

    2008-05-01

    Purpose: We tested whether the chromosomal radiosensitivity of in vitro irradiated lymphocytes could be used to predict the risk of acute reactions after radiotherapy. Methods and Materials: Two prospective studies were performed: study A with 51 patients included different tumor sites and study B included 87 breast cancer patients. Acute reaction was assessed using the Radiation Therapy Oncology Group score. In both studies, patients were treated with curative radiotherapy, and the mean tumor dose applied was 55 Gy (40-65) {+-} boost with 11 Gy (6-31) in study A and 50.4 Gy {+-} boost with 10 Gy in study B. Individual radiosensitivity was determined with lymphocytes irradiated in vitro with X-ray doses of either 3 or 6 Gy and scoring the number of chromosomal deletions. Results: Acute reactions displayed a typical spectrum with 57% in study A and 53% in study B showing an acute reaction of Grade 2-3. Individual radiosensitivity in both studies was characterized by a substantial variation and the fraction of patients with Grade 2-3 reaction was found to increase with increasing individual radiosensitivity measured at 6 Gy (study A, p = 0.238; study B, p = 0.023). For study B, this fraction increased with breast volume, and the impact of individual radiosensitivity on acute reaction was especially pronounced (p = 0.00025) for lower breast volume. No such clear association with acute reaction was observed when individual radiosensitivity was assessed at 3 Gy. Conclusion: Individual radiosensitivity determined at 6 Gy seems to be a good predictor for risk of acute effects after curative radiotherapy.

  17. Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability.

    PubMed

    Malik, Paul R V; Hamadeh, Abdullah; Phipps, Colin; Edginton, Andrea N

    2017-03-04

    In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 ([Formula: see text]), the convective flow rate of mAb through vascular pores ([Formula: see text]), the endocytic transport rate of mAb through vascular endothelium ([Formula: see text]), the degradation rate of mAb-HER2 complexes ([Formula: see text]) and the concentration of shed HER2 extracellular domain in circulation ([Formula: see text]). [Formula: see text] was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. [Formula: see text] was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability.

  18. Predicted Values of Cardiopulmonary Exercise Testing in Healthy Individuals (A Pilot Study)

    PubMed Central

    Mohammad, Majid Malek; Dadashpour, Shahdak

    2012-01-01

    Background Cardiopulmonary exercise testing evaluates the ability of one's cardiovascular and respiratory system in maximal exercise. This was a descriptive cross-sectional pilot study conducted at Masih Daneshvari Hospital in order to determine predicted values of cardiopulmonary exercise testing in individuals with normal physical activity patterns. Materials and Methods Thirty four individuals (14 women, 20 men) between 18-57 years of age were chosen using simple sampling method and evaluated with an incremental progressive cycle-ergometer test to a symptom-limited maximal tolerable work load. Subjects with a history of ischemic heart disease, pulmonary disease or neuromuscular disease were excluded from the study. Smokers were included but we made sure that all subjects had normal FEV1 and FEV1/FVC. This study aimed to compare measured values of VO2, VCO2, VO2/Kg, RER, O2pulse, HRR, HR, Load, Ant, BF, BR, VE, EQCO2, and EQO2 with previously published predicted values. Results We found that our obtained values for VO2 max, HRR max and HR max were different from standard tables but such difference was not observed for other understudy variables. Multiple linear regression analysis was done for height, weight and age (due to the small number of samples, no difference was detected between males and females). VO2 max and load max had reverse correlation with age and direct correlation with weight and height (P < 0.05) but the greatest correlation was observed for height. Conclusion Due to the small number of samples and poor correlations it was not possible to do regression analysis for other variables. In the next study with a larger sample size predicted values for all variables will be calculated. If the future study also indicates a significant difference between the predicted values and the reference values, we will need standard tables made specifically for our own country, Iran. PMID:25191396

  19. Predicted values of cardiopulmonary exercise testing in healthy individuals (a pilot study).

    PubMed

    Mohammad, Majid Malek; Dadashpour, Shahdak; Adimi, Parisa

    2012-01-01

    Cardiopulmonary exercise testing evaluates the ability of one's cardiovascular and respiratory system in maximal exercise. This was a descriptive cross-sectional pilot study conducted at Masih Daneshvari Hospital in order to determine predicted values of cardiopulmonary exercise testing in individuals with normal physical activity patterns. Thirty four individuals (14 women, 20 men) between 18-57 years of age were chosen using simple sampling method and evaluated with an incremental progressive cycle-ergometer test to a symptom-limited maximal tolerable work load. Subjects with a history of ischemic heart disease, pulmonary disease or neuromuscular disease were excluded from the study. Smokers were included but we made sure that all subjects had normal FEV1 and FEV1/FVC. This study aimed to compare measured values of VO2, VCO2, VO2/Kg, RER, O2pulse, HRR, HR, Load, Ant, BF, BR, VE, EQCO2, and EQO2 with previously published predicted values. We found that our obtained values for VO2 max, HRR max and HR max were different from standard tables but such difference was not observed for other understudy variables. Multiple linear regression analysis was done for height, weight and age (due to the small number of samples, no difference was detected between males and females). VO2 max and load max had reverse correlation with age and direct correlation with weight and height (P < 0.05) but the greatest correlation was observed for height. Due to the small number of samples and poor correlations it was not possible to do regression analysis for other variables. In the next study with a larger sample size predicted values for all variables will be calculated. If the future study also indicates a significant difference between the predicted values and the reference values, we will need standard tables made specifically for our own country, Iran.

  20. [Predicting individual risk of high healthcare cost to identify complex chronic patients].

    PubMed

    Coderch, Jordi; Sánchez-Pérez, Inma; Ibern, Pere; Carreras, Marc; Pérez-Berruezo, Xavier; Inoriza, José M

    2014-01-01

    To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

  1. Individual reactions to stress predict performance during a critical aviation incident.

    PubMed

    Vine, Samuel J; Uiga, Liis; Lavric, Aureliu; Moore, Lee J; Tsaneva-Atanasova, Krasimira; Wilson, Mark R

    2015-01-01

    Understanding the influence of stress on human performance is of theoretical and practical importance. An individual's reaction to stress predicts their subsequent performance; with a "challenge" response to stress leading to better performance than a "threat" response. However, this contention has not been tested in truly stressful environments with highly skilled individuals. Furthermore, the effect of challenge and threat responses on attentional control during visuomotor tasks is poorly understood. Thus, this study aimed to examine individual reactions to stress and their influence on attentional control, among a cohort of commercial pilots performing a stressful flight assessment. Sixteen pilots performed an "engine failure on take-off" scenario, in a high-fidelity flight simulator. Reactions to stress were indexed via self-report; performance was assessed subjectively (flight instructor assessment) and objectively (simulator metrics); gaze behavior data were captured using a mobile eye tracker, and measures of attentional control were subsequently calculated (search rate, stimulus driven attention, and entropy). Hierarchical regression analyses revealed that a threat response was associated with poorer performance and disrupted attentional control. The findings add to previous research showing that individual reactions to stress influence performance and shed light on the processes through which stress influences performance.

  2. Prediction of brain-computer interface aptitude from individual brain structure

    PubMed Central

    Halder, S.; Varkuti, B.; Bogdan, M.; Kübler, A.; Rosenstiel, W.; Sitaram, R.; Birbaumer, N.

    2013-01-01

    Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use. PMID:23565083

  3. Relationship among performance, carcass, and feed efficiency characteristics, and their ability to predict economic value in the feedlot.

    PubMed

    Retallick, K M; Faulkner, D B; Rodriguez-Zas, S L; Nkrumah, J D; Shike, D W

    2013-12-01

    A 4-yr study was conducted using 736 steers of known Angus, Simmental, or Simmental × Angus genetics to determine performance, carcass, and feed efficiency factors that explained variation in economic performance. Steers were pen fed and individual DMI was recorded using a GrowSafe automated feeding system (GrowSafe Systems Ltd., Airdrie, Alberta, Canada). Steers consumed a similar diet and received similar management each year. The objectives of this study were to: 1) determine current economic value of feed efficiency and 2) identify performance, carcass, and feed efficiency characteristics that predict: carcass value, profit, cost of gain, and feed costs. Economic data used were from 2011 values. Feed efficiency values investigated were: feed conversion ratio (FCR; feed to gain), residual feed intake (RFI), residual BW gain (RG), and residual intake and BW gain (RIG). Dependent variables were carcass value ($/steer), profit ($/steer), feed costs ($/steer • d(-1)), and cost of gain ($/kg). Independent variables were year, DMI, ADG, HCW, LM area, marbling, yield grade, dam breed, and sire breed. A 10% improvement in RG (P < 0.05) yielded the lowest cost of gain at $0.09/kg and highest carcass value at $17.92/steer. Carcass value increased (P < 0.05) as feed efficiency improved for FCR, RG, and RIG. Profit increased with a 10% improvement in feed efficiency (P < 0.05) with FCR at $34.65/steer, RG at $31.21/steer, RIG at $21.66/steer, and RFI at $11.47/steer. The carcass value prediction model explained 96% of the variation among carcasses and included HCW, marbling score, and yield grade. Average daily gain, marbling score, yield grade, DMI, HCW, and year born constituted 81% of the variation for prediction of profit. Eighty-five percent of the variation in cost of gain was explained by ADG, DMI, HCW, and year. Prediction equations were developed that excluded ADG and DMI, and included feed efficiency values. Using these equations, cost of gain was explained

  4. Individual Bayesian Information Matrix for Predicting Estimation Error and Shrinkage of Individual Parameters Accounting for Data Below the Limit of Quantification.

    PubMed

    Nguyen, Thi Huyen Tram; Nguyen, Thu Thuy; Mentré, France

    2017-06-28

    In mixed models, the relative standard errors (RSE) and shrinkage of individual parameters can be predicted from the individual Bayesian information matrix (MBF). We proposed an approach accounting for data below the limit of quantification (LOQ) in MBF. MBF is the sum of the expectation of the individual Fisher information (MIF) which can be evaluated by First-Order linearization and the inverse of random effect variance. We expressed the individual information as a weighted sum of predicted MIF for every possible design composing of measurements above and/or below LOQ. When evaluating MIF, we derived the likelihood expressed as the product of the likelihood of observed data and the probability for data to be below LOQ. The relevance of RSE and shrinkage predicted by MBF in absence or presence of data below LOQ were evaluated by simulations, using a pharmacokinetic/viral kinetic model defined by differential equations. Simulations showed good agreement between predicted and observed RSE and shrinkage in absence or presence of data below LOQ. We found that RSE and shrinkage increased with sparser designs and with data below LOQ. The proposed method based on MBF adequately predicted individual RSE and shrinkage, allowing for evaluation of a large number of scenarios without extensive simulations.

  5. [Predicting efficiency of selection on reproductive traits in the medicinal leech Hirudo medicinalis L].

    PubMed

    Utevskaia, O M; Atramentova, L A

    2002-03-01

    A set of selection measures for increasing reproduction efficiency in Hirudo medicinalis has been developed. The optimal values of reproductive traits corresponding to the highest progeny number were determined and recommended. The probability of correlated selection response in traits "number of threads in a cocoon" and "weight of threads" was estimated. Based on earlier results on phenotypic variation and heritability of reproductive traits in medicinal leech, efficiency of different selection modes was predicted.

  6. Comparison of Prediction Models for Lynch Syndrome Among Individuals With Colorectal Cancer

    PubMed Central

    Ojha, Rohit P.; Leenen, Celine; Alvero, Carmelita; Mercado, Rowena C.; Balmaña, Judith; Valenzuela, Irene; Balaguer, Francesc; Green, Roger; Lindor, Noralane M.; Thibodeau, Stephen N.; Newcomb, Polly; Win, Aung Ko; Jenkins, Mark; Buchanan, Daniel D.; Bertario, Lucio; Sala, Paola; Hampel, Heather; Syngal, Sapna; Steyerberg, Ewout W.

    2016-01-01

    Background: Recent guidelines recommend the Lynch Syndrome prediction models MMRPredict, MMRPro, and PREMM1,2,6 for the identification of MMR gene mutation carriers. We compared the predictive performance and clinical usefulness of these prediction models to identify mutation carriers. Methods: Pedigree data from CRC patients in 11 North American, European, and Australian cohorts (6 clinic- and 5 population-based sites) were used to calculate predicted probabilities of pathogenic MLH1, MSH2, or MSH6 gene mutations by each model and gene-specific predictions by MMRPro and PREMM1,2,6. We examined discrimination with area under the receiver operating characteristic curve (AUC), calibration with observed to expected (O/E) ratio, and clinical usefulness using decision curve analysis to select patients for further evaluation. All statistical tests were two-sided. Results: Mutations were detected in 539 of 2304 (23%) individuals from the clinic-based cohorts (237 MLH1, 251 MSH2, 51 MSH6) and 150 of 3451 (4.4%) individuals from the population-based cohorts (47 MLH1, 71 MSH2, 32 MSH6). Discrimination was similar for clinic- and population-based cohorts: AUCs of 0.76 vs 0.77 for MMRPredict, 0.82 vs 0.85 for MMRPro, and 0.85 vs 0.88 for PREMM1,2,6. For clinic- and population-based cohorts, O/E deviated from 1 for MMRPredict (0.38 and 0.31, respectively) and MMRPro (0.62 and 0.36) but were more satisfactory for PREMM1,2,6 (1.0 and 0.70). MMRPro or PREMM1,2,6 predictions were clinically useful at thresholds of 5% or greater and in particular at greater than 15%. Conclusions: MMRPro and PREMM1,2,6 can well be used to select CRC patients from genetics clinics or population-based settings for tumor and/or germline testing at a 5% or higher risk. If no MMR deficiency is detected and risk exceeds 15%, we suggest considering additional genetic etiologies for the cause of cancer in the family. PMID:26582061

  7. Predictability of the individual clinical outcome of extracorporeal shock wave therapy for cellulite

    PubMed Central

    Schlaudraff, Kai-Uwe; Kiessling, Maren C; Császár, Nikolaus BM; Schmitz, Christoph

    2014-01-01

    Background Extracorporeal shock wave therapy has been successfully introduced for the treatment of cellulite in recent years. However, it is still unknown whether the individual clinical outcome of cellulite treatment with extracorporeal shock wave therapy can be predicted by the patient’s individual cellulite grade at baseline, individual patient age, body mass index (BMI), weight, and/or height. Methods Fourteen Caucasian females with cellulite were enrolled in a prospective, single-center, randomized, open-label Phase II study. The mean (± standard error of the mean) cellulite grade at baseline was 2.5±0.09 and mean BMI was 22.8±1.17. All patients were treated with radial extracorporeal shock waves using the Swiss DolorClast® device (Electro Medical Systems, S.A., Nyon, Switzerland). Patients were treated unilaterally with 2 weekly treatments for 4 weeks on a randomly selected side (left or right), totaling eight treatments on the selected side. Treatment was performed at 3.5–4.0 bar, with 15,000 impulses per session applied at 15 Hz. Impulses were homogeneously distributed over the posterior thigh and buttock area (resulting in 7,500 impulses per area). Treatment success was evaluated after the last treatment and 4 weeks later by clinical examination, photographic documentation, contact thermography, and patient satisfaction questionnaires. Results The mean cellulite grade improved from 2.5±0.09 at baseline to 1.57±0.18 after the last treatment (ie, mean δ-1 was 0.93 cellulite grades) and 1.68±0.16 at follow-up (ie, mean δ-2 was 0.82 cellulite grades). Compared with baseline, no patient’s condition worsened, the treatment was well tolerated, and no unwanted side effects were observed. No statistically significant (ie, P<0.05) correlation was found between individual values for δ-1 and δ-2 and cellulite grade at baseline, BMI, weight, height, or age. Conclusion Radial shock wave therapy is a safe and effective treatment option for cellulite. The

  8. Predictability of the individual clinical outcome of extracorporeal shock wave therapy for cellulite.

    PubMed

    Schlaudraff, Kai-Uwe; Kiessling, Maren C; Császár, Nikolaus Bm; Schmitz, Christoph

    2014-01-01

    Extracorporeal shock wave therapy has been successfully introduced for the treatment of cellulite in recent years. However, it is still unknown whether the individual clinical outcome of cellulite treatment with extracorporeal shock wave therapy can be predicted by the patient's individual cellulite grade at baseline, individual patient age, body mass index (BMI), weight, and/or height. Fourteen Caucasian females with cellulite were enrolled in a prospective, single-center, randomized, open-label Phase II study. The mean (± standard error of the mean) cellulite grade at baseline was 2.5±0.09 and mean BMI was 22.8±1.17. All patients were treated with radial extracorporeal shock waves using the Swiss DolorClast(®) device (Electro Medical Systems, S.A., Nyon, Switzerland). Patients were treated unilaterally with 2 weekly treatments for 4 weeks on a randomly selected side (left or right), totaling eight treatments on the selected side. Treatment was performed at 3.5-4.0 bar, with 15,000 impulses per session applied at 15 Hz. Impulses were homogeneously distributed over the posterior thigh and buttock area (resulting in 7,500 impulses per area). Treatment success was evaluated after the last treatment and 4 weeks later by clinical examination, photographic documentation, contact thermography, and patient satisfaction questionnaires. The mean cellulite grade improved from 2.5±0.09 at baseline to 1.57±0.18 after the last treatment (ie, mean δ-1 was 0.93 cellulite grades) and 1.68±0.16 at follow-up (ie, mean δ-2 was 0.82 cellulite grades). Compared with baseline, no patient's condition worsened, the treatment was well tolerated, and no unwanted side effects were observed. No statistically significant (ie, P<0.05) correlation was found between individual values for δ-1 and δ-2 and cellulite grade at baseline, BMI, weight, height, or age. Radial shock wave therapy is a safe and effective treatment option for cellulite. The individual clinical outcome cannot be

  9. Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

    PubMed Central

    Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming

    2016-01-01

    Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427

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

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

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

  11. An efficient algorithm to integrate network and attribute data for gene function prediction.

    PubMed

    Vembu, Shankar; Morris, Quaid

    2014-01-01

    Label propagation methods are extremely well-suited for a variety of biomedical prediction tasks based on network data. However, these algorithms cannot be used to integrate feature-based data sources with networks. We propose an efficient learning algorithm to integrate these two types of heterogeneous data sources to perform binary prediction tasks on node features (e.g., gene prioritization, disease gene prediction). Our method, LMGraph, consists of two steps. In the first step, we extract a small set of "network features" from the nodes of networks that represent connectivity with labeled nodes in the prediction tasks. In the second step, we apply a simple weighting scheme in conjunction with linear classifiers to combine these network features with other feature data. This two-step procedure allows us to (i) learn highly scalable and computationally efficient linear classifiers, (ii) and seamlessly combine feature-based data sources with networks. Our method is much faster than label propagation which is already known to be computationally efficient on large-scale prediction problems. Experiments on multiple functional interaction networks from three species (mouse, y, C.elegans) with tens of thousands of nodes and hundreds of binary prediction tasks demonstrate the efficacy of our method.

  12. Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

    SciTech Connect

    Li, Dongsheng; Sun, Xin; Khaleel, Mohammad A.

    2011-09-28

    This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form.

  13. Age-related and individual differences in the use of prediction during language comprehension

    PubMed Central

    Federmeier, Kara D.; Kutas, Marta; Schul, Rina

    2010-01-01

    During sentence comprehension, older adults are less likely than younger adults to predict features of likely upcoming words. A pair of experiments assessed whether such differences would extend to tasks with reduced working memory demands and time pressures. In Experiment 1, event-related brain potentials were measured as younger and older adults read short phrases cuing antonyms or category exemplars, followed three seconds later by targets that were either congruent or incongruent and, for congruent category exemplars, of higher or lower typicality. When processing the less expected low typicality targets, younger – but not older – adults elicited a prefrontal positivity (500–900 ms) that has been linked to processing consequences of having predictions disconfirmed. Thus, age-related changes in prediction during comprehension generalize across task circumstances. Analyses of individual differences revealed that older adults with higher category fluency were more likely to show the young-like pattern. Experiment 2 showed that these age-related differences were not due to simple slowing of language production mechanisms, as older adults generated overt responses to the cues as quickly as – and more accurately than – younger adults. However, older adults who were relatively faster to produce category exemplars in Experiment 2 were more likely to have shown predictive processing patterns in Experiment 1. Taken together, the results link prediction during language comprehension to language production mechanisms and suggest that although older adults can produce speeded language output on demand, they are less likely to automatically recruit these mechanisms during comprehension unless top-down circuitry is particularly strong. PMID:20728207

  14. Predicting individual differences in autonomy-connectedness: the role of body awareness, alexithymia, and assertiveness.

    PubMed

    Bekker, Marrie H J; Croon, Marcel A; van Balkom, Esther G A; Vermee, Jennifer B G

    2008-06-01

    Autonomy-connectedness is the capacity for being on one's own as well as for satisfactorily engaging in interpersonal relationships. Associations have been shown between autonomy-connectedness components (self-awareness, sensitivity to others, and the capacity for managing new situations) and various indices of psychopathology. Both in a theoretical sense as well as for enhancing treatment and prevention, it is relevant to identify which factors most powerfully predict individual differences in autonomy-connectedness: body awareness, alexithymia, or assertiveness. The present study examined this question in a clinical sample of women who were diagnosed as having autonomy problems (N=52) and in a female nonclinical community sample (N=59). In line with expectations, assertiveness was a strong predictor of (all three components of) autonomy-connectedness, as was emotionalizing, one of the alexithymia-components, but the latter in an opposite direction than we had expected: the higher an individual's ability to emotionalize was, the less self-aware and capable to manage new situations that person was, and the more sensitive to others. Cognitive alexithymia contributed to self-awareness as well as to the capacity for managing new situations, and one of the components of body awareness appeared to predict capacity for managing new situations. Our results indicate that assertiveness training and the enhancement of emotion regulation are important elements of autonomy-connectedness targeted interventions. (c) 2008 Wiley Periodicals, Inc.

  15. Auditory skills and brain morphology predict individual differences in adaptation to degraded speech.

    PubMed

    Erb, Julia; Henry, Molly J; Eisner, Frank; Obleser, Jonas

    2012-07-01

    Noise-vocoded speech is a spectrally highly degraded signal, but it preserves the temporal envelope of speech. Listeners vary considerably in their ability to adapt to this degraded speech signal. Here, we hypothesised that individual differences in adaptation to vocoded speech should be predictable by non-speech auditory, cognitive, and neuroanatomical factors. We tested 18 normal-hearing participants in a short-term vocoded speech-learning paradigm (listening to 100 4-band-vocoded sentences). Non-speech auditory skills were assessed using amplitude modulation (AM) rate discrimination, where modulation rates were centred on the speech-relevant rate of 4 Hz. Working memory capacities were evaluated (digit span and nonword repetition), and structural MRI scans were examined for anatomical predictors of vocoded speech learning using voxel-based morphometry. Listeners who learned faster to understand degraded speech also showed smaller thresholds in the AM discrimination task. This ability to adjust to degraded speech is furthermore reflected anatomically in increased grey matter volume in an area of the left thalamus (pulvinar) that is strongly connected to the auditory and prefrontal cortices. Thus, individual non-speech auditory skills and left thalamus grey matter volume can predict how quickly a listener adapts to degraded speech. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Individual differences in white matter anatomy predict dissociable components of reading skill in adults.

    PubMed

    Welcome, Suzanne E; Joanisse, Marc F

    2014-08-01

    We used diffusion tensor imaging (DTI) to investigate relationships between white matter anatomy and different reading subskills in typical-reading adults. A series of analytic approaches revealed that phonological decoding ability is associated with anatomical markers that do not relate to other reading-related cognitive abilities. Thus, individual differences in phonological decoding might relate to connectivity between a network of cortical regions, while skills like sight word reading might rely less strongly on integration across regions. Specifically, manually-drawn ROIs and probabilistic tractography revealed an association between the volume and integrity of white matter underlying primary auditory cortex and nonword reading ability. In a related finding, more extensive cross-hemispheric connections through the isthmus of the corpus callosum predicted better phonological decoding. Atlas-based white matter ROIs demonstrated that relationships with nonword reading were strongest in the inferior fronto-occipital fasciculus and uncinate fasciculus that connect occipital and anterior temporal cortex with inferior frontal cortex. In contrast, tract volume underlying the left angular gyrus was related to nonverbal IQ. Finally, connectivity underlying functional ROIs that are differentially active during phonological and semantic processing predicted nonword reading and reading comprehension, respectively. Together, these results provide important insights into how white matter anatomy may relate to both typical reading subskills, and perhaps a roadmap for understanding neural connectivity in individuals with reading impairments. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Individual differences in bodily freezing predict emotional biases in decision making.

    PubMed

    Ly, Verena; Huys, Quentin J M; Stins, John F; Roelofs, Karin; Cools, Roshan

    2014-01-01

    Instrumental decision making has long been argued to be vulnerable to emotional responses. Literature on multiple decision making systems suggests that this emotional biasing might reflect effects of a system that regulates innately specified, evolutionarily preprogrammed responses. To test this hypothesis directly, we investigated whether effects of emotional faces on instrumental action can be predicted by effects of emotional faces on bodily freezing, an innately specified response to aversive relative to appetitive cues. We tested 43 women using a novel emotional decision making task combined with posturography, which involves a force platform to detect small oscillations of the body to accurately quantify postural control in upright stance. On the platform, participants learned whole body approach-avoidance actions based on monetary feedback, while being primed by emotional faces (angry/happy). Our data evidence an emotional biasing of instrumental action. Thus, angry relative to happy faces slowed instrumental approach relative to avoidance responses. Critically, individual differences in this emotional biasing effect were predicted by individual differences in bodily freezing. This result suggests that emotional biasing of instrumental action involves interaction with a system that controls innately specified responses. Furthermore, our findings help bridge (animal and human) decision making and emotion research to advance our mechanistic understanding of decision making anomalies in daily encounters as well as in a wide range of psychopathology.

  18. Individual differences in maternal response to immune challenge predict offspring behavior: Contribution of environmental factors

    PubMed Central

    Bronson, Stefanie L.; Ahlbrand, Rebecca; Horn, Paul S.; Kern, Joseph R.; Richtand, Neil M.

    2011-01-01

    Maternal infection during pregnancy elevates risk for schizophrenia and related disorders in offspring. Converging evidence suggests the maternal inflammatory response mediates the interaction between maternal infection, altered brain development, and behavioral outcome. The extent to which individual differences in the maternal response to immune challenge influence the development of these abnormalities is unknown. The present study investigated the impact of individual differences in maternal response to the viral mimic polyinosinic:polycytidylic acid (poly I:C) on offspring behavior. We observed significant variability in body weight alterations of pregnant rats induced by administration of poly I:C on gestational day 14. Furthermore, the presence or absence of maternal weight loss predicted MK-801 and amphetamine stimulated locomotor abnormalities in offspring. MK-801 stimulated locomotion was altered in offspring of all poly I:C treated dams; however, the presence or absence of maternal weight loss resulted in decreased and modestly increased locomotion, respectively. Adult offspring of poly I:C treated dams that lost weight exhibited significantly decreased amphetamine stimulated locomotion, while offspring of poly I:C treated dams without weight loss performed similarly to vehicle controls. Social isolation and increased maternal age predicted weight loss in response to poly I:C but not vehicle injection. In combination, these data identify environmental factors associated with the maternal response to immune challenge and functional outcome of offspring exposed to maternal immune activation. PMID:21255612

  19. Individual differences in bodily freezing predict emotional biases in decision making

    PubMed Central

    Ly, Verena; Huys, Quentin J. M.; Stins, John F.; Roelofs, Karin; Cools, Roshan

    2014-01-01

    Instrumental decision making has long been argued to be vulnerable to emotional responses. Literature on multiple decision making systems suggests that this emotional biasing might reflect effects of a system that regulates innately specified, evolutionarily preprogrammed responses. To test this hypothesis directly, we investigated whether effects of emotional faces on instrumental action can be predicted by effects of emotional faces on bodily freezing, an innately specified response to aversive relative to appetitive cues. We tested 43 women using a novel emotional decision making task combined with posturography, which involves a force platform to detect small oscillations of the body to accurately quantify postural control in upright stance. On the platform, participants learned whole body approach-avoidance actions based on monetary feedback, while being primed by emotional faces (angry/happy). Our data evidence an emotional biasing of instrumental action. Thus, angry relative to happy faces slowed instrumental approach relative to avoidance responses. Critically, individual differences in this emotional biasing effect were predicted by individual differences in bodily freezing. This result suggests that emotional biasing of instrumental action involves interaction with a system that controls innately specified responses. Furthermore, our findings help bridge (animal and human) decision making and emotion research to advance our mechanistic understanding of decision making anomalies in daily encounters as well as in a wide range of psychopathology. PMID:25071491

  20. Prediction Error Representation in Individuals With Generalized Anxiety Disorder During Passive Avoidance.

    PubMed

    White, Stuart F; Geraci, Marilla; Lewis, Elizabeth; Leshin, Joseph; Teng, Cindy; Averbeck, Bruno; Meffert, Harma; Ernst, Monique; Blair, James R; Grillon, Christian; Blair, Karina S

    2017-02-01

    Deficits in reinforcement-based decision making have been reported in generalized anxiety disorder. However, the pathophysiology of these deficits is largely unknown; published studies have mainly examined adolescents, and the integrity of core functional processes underpinning decision making remains undetermined. In particular, it is unclear whether the representation of reinforcement prediction error (PE) (the difference between received and expected reinforcement) is disrupted in generalized anxiety disorder. This study addresses these issues in adults with the disorder. Forty-six unmedicated individuals with generalized anxiety disorder and 32 healthy comparison subjects group-matched on IQ, gender, and age performed a passive avoidance task while undergoing functional MRI. Data analyses were performed using a computational modeling approach. Behaviorally, individuals with generalized anxiety disorder showed impaired reinforcement-based decision making. Imaging results revealed that during feedback, individuals with generalized anxiety disorder relative to healthy subjects showed a reduced correlation between PE and activity within the ventromedial prefrontal cortex, ventral striatum, and other structures implicated in decision making. In addition, individuals with generalized anxiety disorder relative to healthy participants showed a reduced correlation between punishment PEs, but not reward PEs, and activity within the left and right lentiform nucleus/putamen. This is the first study to identify computational impairments during decision making in generalized anxiety disorder. PE signaling is significantly disrupted in individuals with the disorder and may lead to their decision-making deficits and excessive worry about everyday problems by disrupting the online updating ("reality check") of the current relationship between the expected values of current response options and the actual received rewards and punishments.

  1. Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

    PubMed

    Ferket, Bart S; van Kempen, Bob J H; Heeringa, Jan; Spronk, Sandra; Fleischmann, Kirsten E; Nijhuis, Rogier L G; Hofman, Albert; Steyerberg, Ewout W; Hunink, M G Myriam

    2012-01-01

    Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks. A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk. We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their

  2. Personalized Prediction of Lifetime Benefits with Statin Therapy for Asymptomatic Individuals: A Modeling Study

    PubMed Central

    Ferket, Bart S.; van Kempen, Bob J. H.; Heeringa, Jan; Spronk, Sandra; Fleischmann, Kirsten E.; Nijhuis, Rogier L. G.; Hofman, Albert; Steyerberg, Ewout W.; Hunink, M. G. Myriam

    2012-01-01

    Background Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks. Methods and Findings A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk. Conclusions We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be

  3. The potential of Fourier transform infrared spectroscopy of milk samples to predict energy intake and efficiency in dairy cows.

    PubMed

    McParland, S; Berry, D P

    2016-05-01

    Knowledge of animal-level and herd-level energy intake, energy balance, and feed efficiency affect day-to-day herd management strategies; information on these traits at an individual animal level is also useful in animal breeding programs. A paucity of data (especially at the individual cow level), of feed intake in particular, hinders the inclusion of such attributes in herd management decision-support tools and breeding programs. Dairy producers have access to an individual cow milk sample at least once daily during lactation, and consequently any low-cost phenotyping strategy should consider exploiting measureable properties in this biological sample, reflecting the physiological status and performance of the cow. Infrared spectroscopy is the study of the interaction of an electromagnetic wave with matter and it is used globally to predict milk quality parameters on routinely acquired individual cow milk samples and bulk tank samples. Thus, exploiting infrared spectroscopy in next-generation phenotyping will ensure potentially rapid application globally with a negligible additional implementation cost as the infrastructure already exists. Fourier-transform infrared spectroscopy (FTIRS) analysis is already used to predict milk fat and protein concentrations, the ratio of which has been proposed as an indicator of energy balance. Milk FTIRS is also able to predict the concentration of various fatty acids in milk, the composition of which is known to change when body tissue is mobilized; that is, when the cow is in negative energy balance. Energy balance is mathematically very similar to residual energy intake (REI), a suggested measure of feed efficiency. Therefore, the prediction of energy intake, energy balance, and feed efficiency (i.e., REI) from milk FTIRS seems logical. In fact, the accuracy of predicting (i.e., correlation between predicted and actual values; root mean square error in parentheses) energy intake, energy balance, and REI from milk FTIRS in

  4. Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence

    PubMed Central

    Qazi, Emad-ul-Haq; Hussain, Muhammad; Aboalsamh, Hatim; Malik, Aamir Saeed; Amin, Hafeez Ullah; Bamatraf, Saeed

    2017-01-01

    Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual's fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0–1.875 Hz (delta low) and 1.875–3.75 Hz (delta high), resulted in the 100 and 98% prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system. PMID:28163676

  5. Factors Motivating Individuals to Consider Genetic Testing for Type 2 Diabetes Risk Prediction.

    PubMed

    Wessel, Jennifer; Gupta, Jyoti; de Groot, Mary

    2016-01-01

    The purpose of this study was to identify attitudes and perceptions of willingness to participate in genetic testing for type 2 diabetes (T2D) risk prediction in the general population. Adults (n = 598) were surveyed on attitudes about utilizing genetic testing to predict future risk of T2D. Participants were recruited from public libraries (53%), online registry (37%) and a safety net hospital emergency department (10%). Respondents were 37 ± 11 years old, primarily White (54%), female (69%), college educated (46%), with an annual income ≥$25,000 (56%). Half of participants were interested in genetic testing for T2D (52%) and 81% agreed/strongly agreed genetic testing should be available to the public. Only 57% of individuals knew T2D is preventable. A multivariate model to predict interest in genetic testing was adjusted for age, gender, recruitment location and BMI; significant predictors were motivation (high perceived personal risk of T2D [OR = 4.38 (1.76, 10.9)]; family history [OR = 2.56 (1.46, 4.48)]; desire to know risk prior to disease onset [OR = 3.25 (1.94, 5.42)]; and knowing T2D is preventable [OR = 2.11 (1.24, 3.60)], intention (if the cost is free [OR = 10.2 (4.27, 24.6)]; and learning T2D is preventable [OR = 5.18 (1.95, 13.7)]) and trust of genetic testing results [OR = 0.03 (0.003, 0.30)]. Individuals are interested in genetic testing for T2D risk which offers unique information that is personalized. Financial accessibility, validity of the test and availability of diabetes prevention programs were identified as predictors of interest in T2D testing.

  6. Development of a Risk Prediction Model to Individualize Risk Factors for Surgical Site Infection after Mastectomy

    PubMed Central

    Olsen, Margaret A.; Nickel, Katelin B.; Margenthaler, Julie A.; Fox, Ida K.; Ball, Kelly E.; Mines, Daniel; Wallace, Anna E.; Colditz, Graham A.; Fraser, Victoria J.

    2016-01-01

    Background Little data are available regarding individual patients’ risk of surgical site infection (SSI) following mastectomy with or without immediate reconstruction. Our objective was to develop a risk prediction model for mastectomy-related SSI. Methods We established a cohort of women < 65 years of age with mastectomy from 1/1/2004–12/31/2011 using commercial claims data. ICD-9-CM diagnosis codes were used to identify SSI within 180 days after surgery. SSI risk factors were determined with multivariable logistic regression using derivation data from 2004-2008 and validated with 2009–2011 data using discrimination and calibration measures. Results In the derivation cohort 595 SSIs were identified in 7,607 (7.8%) women, and 396 SSIs were coded in 4,366 (9.1%) women in the validation cohort. Independent risk factors for SSIs included rural residence, rheumatologic disease, depression, diabetes, hypertension, liver disease, obesity, preexisting pneumonia or urinary tract infection, tobacco use disorder, smoking-related diseases, bilateral mastectomy, and immediate reconstruction. Receipt of home health care was associated with lower risk. The model performed equally in the validation cohort per discrimination (C statistics 0.657 and 0.649) and calibration (Hosmer-Lemeshow P=0.091 and 0.462 for derivation and validation, respectively). Three risk strata were created based on predicted SSI risk, which demonstrated good correlation with the proportion of observed infections in the strata. Conclusions We developed and internally validated an SSI risk prediction model that can be used to counsel women concerning their individual risk of SSI post-mastectomy. Immediate reconstruction, diabetes, and smoking-related diseases were important risk factors for SSI in this nonelderly population of women undergoing mastectomy. PMID:26822880

  7. Individual differences in cortisol stress response predict increases in voice pitch during exam stress.

    PubMed

    Pisanski, Katarzyna; Nowak, Judyta; Sorokowski, Piotr

    2016-09-01

    Despite a long history of empirical research, the potential vocal markers of stress remain unclear. Previous studies examining speech under stress most consistently report an increase in voice pitch (the acoustic correlate of fundamental frequency, F0), however numerous studies have failed to replicate this finding. In the present study we tested the prediction that these inconsistencies are tied to variation in the severity of the stress response, wherein voice changes may be observed predominantly among individuals who show a cortisol stress response (i.e., an increase in free cortisol levels) above a critical threshold. Voice recordings and saliva samples were collected from university psychology students at baseline and again immediately prior to an oral examination. Voice recordings included both read and spontaneous speech, from which we measured mean, minimum, maximum, and the standard deviation in F0. We observed an increase in mean and minimum F0 under stress in both read and spontaneous speech, whereas maximum F0 and its standard deviation showed no systematic changes under stress. Our results confirmed that free cortisol levels increased by an average of 74% (ranging from 0 to 270%) under stress. Critically, increases in cortisol concentrations significantly predicted increases in mean F0 under stress for both speech types, but did not predict variation in F0 at baseline. On average, stress-induced increases in voice pitch occurred only when free cortisol levels more than doubled their baseline concentrations. Our results suggest that researchers examining speech under stress should control for individual differences in the magnitude of the stress response.

  8. Elevated heart rate predicts β cell function in non-diabetic individuals: the RISC cohort.

    PubMed

    Bonnet, Fabrice; Empana, Jean-Philippe; Natali, Andrea; Monti, Lucilla; Golay, Alain; Lalic, Katarina; Dekker, Jacqueline; Mari, Andrea; Balkau, Beverley

    2015-09-01

    Elevated heart rate has been associated with insulin resistance and incident type 2 diabetes but its relationship with β-cell function is not known. Our aim was to investigate whether baseline heart rate is associated with β-cell function and hyperglycaemia. We used the prospective RISC cohort with 1005 non-diabetic individuals who had an oral glucose tolerance test (OGTT) at baseline and after 3 years. Impaired glucose regulation was defined as a fasting plasma glucose ≥ 6.1 mmol/l or a 2-h plasma glucose ≥ 7.8 mmol/l. Insulin sensitivity was assessed by the OGIS index and insulin secretion and β-cell glucose sensitivity at both baseline and 3 years. Baseline heart rate was positively related to both fasting (P < 0.0001) and 2 h glucose levels (P = 0.02) at year 3 and predicted the presence of impaired glucose regulation at year 3 in a logistic regression model adjusting for insulin sensitivity at inclusion (OR/10 beats per min: 1.31; 95% CI (1.07-1.61); P = 0.01). Baseline heart rate was associated with lower insulin sensitivity (β = -0.11; P < .0001), a decrease in both β-cell glucose sensitivity (β = -0.11; P = 0.003) and basal insulin secretion rate (β = -0.11; P = 0.002) at 3 years in an adjusted multivariable regression model. Baseline heart rate predicted the 3-year decrease in β-cell glucose sensitivity (β = -0.10; P = 0.007) and basal insulin secretion (β = -0.12; P = 0.007). Heart rate predicts β-cell function and impaired glucose regulation at 3 years in non-diabetic individuals, independently of the level of insulin sensitivity. These findings suggest a possible effect of the sympathetic nervous system on β-cell dysfunction, which deserves further investigation. © 2015 European Society of Endocrinology.

  9. Continuous prediction of secondary progression in the individual course of multiple sclerosis.

    PubMed

    Skoog, Bengt; Tedeholm, Helen; Runmarker, Björn; Odén, Anders; Andersen, Oluf

    2014-09-01

    Prediction of the course of multiple sclerosis (MS) was traditionally based on features close to onset. To evaluate predictors of the individual risk of secondary progression (SP) identified at any time during relapsing-remitting MS. We analysed a database comprising an untreated MS incidence cohort (n=306) with five decades of follow-up. Data regarding predictors of all attacks (n=749) and demographics from patients (n=157) with at least one distinct second attack were included as covariates in a Poisson regression analysis with SP as outcome. The average hazard function of transition to SPMS was 0.046 events per patient year, showing a maximum at age 33. Three covariates were significant predictors: age, a descriptor of the most recent relapse, and the interaction between the descriptor and time since the relapse. A hazard function termed "prediction score" estimated the risk of SP as number of transition events per patient year (range <0.01 to >0.15). The insights gained from this study are that the risk of transition to SP varies over time in individual patients, that the risk of SP is linked to previous relapses, that predictors in the later stages of the course are more effective than the traditional onset predictors, and that the number of potential predictors can be reduced to a few (three in this study) essential items. This advanced simplification facilitates adaption of the "prediction score" to other (more recent, benign or treated) materials, and allows for compact web-based applications (http://msprediction.com). Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Do individualism and collectivism on three levels (country, individual, and situation) influence theory-of-mind efficiency? A cross-country study

    PubMed Central

    Finkenauer, Catrin; Huizinga, Mariette; Novin, Sheida; Krabbendam, Lydia

    2017-01-01

    This study investigated whether individualism and collectivism (IC) at country, individual, and situational level influence how quickly and accurately people can infer mental states (i.e. theory of mind, or ToM), indexed by accuracy and reaction time in a ToM task. We hypothesized that collectivism (having an interdependent self and valuing group concerns), compared to individualism (having an independent self and valuing personal concerns), is associated with greater accuracy and speed in recognizing and understanding the thoughts and feelings of others. Students (N = 207) from individualism-representative (the Netherlands) and collectivism-representative (Vietnam) countries (Country IC) answered an individualism-collectivism questionnaire (Individual IC) and were randomly assigned to an individualism-primed, collectivism-primed, or no-prime task (Situational IC) before performing a ToM task. The data showed vast differences between the Dutch and Vietnamese groups that might not be attributable to experimental manipulation. Therefore, we analyzed the data for the groups separately and found that Individual IC did not predict ToM accuracy or reaction time performance. Regarding Situational IC, when primed with individualism, the accuracy performance of Vietnamese participants in affective ToM trials decreased compared to when primed with collectivism and when no prime was used. However, an interesting pattern emerged: Dutch participants were least accurate in affective ToM trials, while Vietnamese participants were quickest in affective ToM trials. Our research also highlights a dilemma faced by cross-cultural researchers who use hard-to-reach populations but face the challenge of disentangling experimental effects from biases that might emerge due to an interaction between cultural differences and experimental settings. We propose suggestions for overcoming such challenges. PMID:28832602

  11. Do individualism and collectivism on three levels (country, individual, and situation) influence theory-of-mind efficiency? A cross-country study.

    PubMed

    Vu, Tuong-Van; Finkenauer, Catrin; Huizinga, Mariette; Novin, Sheida; Krabbendam, Lydia

    2017-01-01

    This study investigated whether individualism and collectivism (IC) at country, individual, and situational level influence how quickly and accurately people can infer mental states (i.e. theory of mind, or ToM), indexed by accuracy and reaction time in a ToM task. We hypothesized that collectivism (having an interdependent self and valuing group concerns), compared to individualism (having an independent self and valuing personal concerns), is associated with greater accuracy and speed in recognizing and understanding the thoughts and feelings of others. Students (N = 207) from individualism-representative (the Netherlands) and collectivism-representative (Vietnam) countries (Country IC) answered an individualism-collectivism questionnaire (Individual IC) and were randomly assigned to an individualism-primed, collectivism-primed, or no-prime task (Situational IC) before performing a ToM task. The data showed vast differences between the Dutch and Vietnamese groups that might not be attributable to experimental manipulation. Therefore, we analyzed the data for the groups separately and found that Individual IC did not predict ToM accuracy or reaction time performance. Regarding Situational IC, when primed with individualism, the accuracy performance of Vietnamese participants in affective ToM trials decreased compared to when primed with collectivism and when no prime was used. However, an interesting pattern emerged: Dutch participants were least accurate in affective ToM trials, while Vietnamese participants were quickest in affective ToM trials. Our research also highlights a dilemma faced by cross-cultural researchers who use hard-to-reach populations but face the challenge of disentangling experimental effects from biases that might emerge due to an interaction between cultural differences and experimental settings. We propose suggestions for overcoming such challenges.

  12. Individualized Prediction of Changes in 6-Minute Walk Distance for Patients with Duchenne Muscular Dystrophy

    PubMed Central

    Goemans, Nathalie; vanden Hauwe, Marleen; Signorovitch, James; Swallow, Elyse; Song, Jinlin

    2016-01-01

    Background Deficits in ambulatory function progress at heterogeneous rates among individuals with Duchenne muscular dystrophy (DMD). The resulting inherent variability in ambulatory outcomes has complicated the design of drug efficacy trials and clouded the interpretation of trial results. We developed a prediction model for 1-year change in the six minute walk distance (6MWD) among DMD patients, and compared its predictive value to that of commonly used prognostic factors (age, baseline 6MWD, and steroid use). Methods Natural history data were collected from DMD patients at routine follow up visits approximately every 6 months over the course of 2–5 years. Assessments included ambulatory function and steroid use. The annualized change in 6MWD (Δ6MWD) was studied between all pairs of visits separated by 8–16 months. Prediction models were developed using multivariable regression for repeated measures, and evaluated using cross-validation. Results Among n = 191 follow-up intervals (n = 39 boys), mean starting age was 9.4 years, mean starting 6MWD was 351.8 meters, and 75% had received steroids for at least one year. Over the subsequent 8–16 months, mean Δ6MWD was -37.0 meters with a standard deviation (SD) of 93.7 meters. Predictions based on a composite of age, baseline 6MWD, and steroid use explained 28% of variation in Δ6MWD (R2 = 0.28, residual SD = 79.4 meters). A broadened prognostic model, adding timed 10-meter walk/run, 4-stair climb, and rise from supine, as well as height and weight, significantly improved prediction, explaining 59% of variation in Δ6MWD after cross-validation (R2 = 0.59, residual SD = 59.7 meters). Conclusions A prognostic model incorporating timed function tests significantly improved prediction of 1-year changes in 6MWD. Explained variation was more than doubled compared to predictions based only on age, baseline 6MWD, and steroid use. There is significant potential for composite prognostic models to inform DMD clinical trials

  13. Sibling configuration predicts individual and descendant socioeconomic success in a modern post-industrial society.

    PubMed

    Lawson, David W; Makoli, Arijeta; Goodman, Anna

    2013-01-01

    Growing up with many siblings, at least in the context of modern post-industrial low fertility, low mortality societies, is predictive of relatively poor performance on school tests in childhood, lower levels of educational attainment, and lower income throughout adulthood. Recent studies further indicate these relationships hold across generations, so that the descendants of those who grow up with many siblings are also at an apparent socioeconomic disadvantage. In this paper we add to this literature by considering whether such relationships interact with the sex and relative age of siblings. To do this we utilise a unique Swedish multigenerational birth cohort study that provides sibling configuration data on over 10,000 individuals born in 1915-1929, plus all their direct genetic descendants to the present day. Adjusting for parental and birth characteristics, we find that the 'socioeconomic cost' of growing up in a large family is independent of both the sex of siblings and the sex of the individual. However, growing up with several older as opposed to several younger siblings is predictive of relatively poor performance on school tests and a lower likelihood of progression to tertiary education. This later-born disadvantage also holds across generations, with the children of those with many older siblings achieving lower levels of educational attainment. Despite these differences, we find that while individual and descendant income is negatively related to the number of siblings, it is not influenced by the relative age of siblings. Thus, our findings imply that the educational disadvantage of later-born children, demonstrated here and in numerous other studies, does not necessarily translate into reduced earnings in adulthood. We discuss potential explanations for this pattern of results, and consider some important directions for future research into sibling configuration and wellbeing in modern societies.

  14. Risk predictions for individual patients from logistic regression were visualized with bar-line charts.

    PubMed

    Björk, Jonas; Ekelund, Ulf; Ohlsson, Mattias

    2012-03-01

    The interface of a computerized decision support system is crucial for its acceptance among end users. We demonstrate how combined bar-line charts can be used to visualize predictions for individual patients from logistic regression models. Data from a previous diagnostic study aiming at predicting the immediate risk of acute coronary syndrome (ACS) among 634 patients presenting to an emergency department with chest pain were used. Risk predictions from the logistic regression model were presented for four hypothetical patients in bar-line charts with bars representing empirical Bayes adjusted likelihood ratios (LRs) and the line representing the estimated probability of ACS, sequentially updated from left to right after assessment of each risk factor. Two patients had similar low risk for ACS but quite different risk profiles according to the bar-line charts. Such differences in risk profiles could not be detected from the estimated ACS risk alone. The bar-line charts also highlighted important but counteracted risk factors in cases where the overall LR was less informative (close to one). The proposed graphical technique conveys additional information from the logistic model that can be important for correct diagnosis and classification of patients and appropriate medical management. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. A Predictive Model for Corticosteroid Response in Individual Patients with MS Relapses

    PubMed Central

    Rakusa, Martin; Cano, Stefan J.; Porter, Bernadette; Riazi, Afsane; Thompson, Alan J.; Chataway, Jeremy; Hardy, Todd A.

    2015-01-01

    Objectives To derive a simple predictive model to guide the use of corticosteroids in patients with relapsing remitting MS suffering an acute relapse. Materials and Methods We analysed individual patient randomised controlled trial data (n=98) using a binary logistic regression model based on age, gender, baseline disability scores [physician-observed: expanded disability status scale (EDSS) and patient reported: multiple sclerosis impact scale 29 (MSIS-29)], and the time intervals between symptom onset or referral and treatment. Results Based on two a priori selected cut-off points (improvement in EDSS ≥ 0.5 and ≥ 1.0), we found that variables which predicted better response to corticosteroids after 6 weeks were younger age and lower MSIS-29 physical score at the time of relapse (model fit 71.2% - 73.1%). Conclusions This pilot study suggests two clinical variables which may predict the majority of the response to corticosteroid treatment in patients undergoing an MS relapse. The study is limited in being able to clearly distinguish factors associated with treatment response or spontaneous recovery and needs to be replicated in a larger prospective study. PMID:25785460

  16. Individual differences in nonlinguistic event categorization predict later motion verb comprehension.

    PubMed

    Konishi, Haruka; Stahl, Aimee E; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathy

    2016-11-01

    This study probes how individual differences in early event perception predict later verb knowledge. At Time 1, when infants were 13 to 15months of age, they saw videotaped silent scenes performed by a human actor. The goal was to see whether infants could form categories of path (a figure's trajectory with respect to a ground object) and manner (how an action is performed). Infants either saw the same manner (e.g., jogging) taking place across three different paths (around, through, and behind) or saw the same path (e.g., around a tent) taking place across three different manners (running, crawling, and walking). After familiarization, either the path or the manner was changed and visual fixation was monitored using preferential looking. At Time 2, the same children were tested on their comprehension of verbs in a two-choice pointing task showing two simultaneous actions (e.g., running vs. jumping). Success at categorization of path and manner at Time 1 predicted verb comprehension at Time 2, even when taking language knowledge at both time points into account. These preliminary results represent headway in identifying the factors that may contribute to children's language learning. They suggest that skill in categorizing semantic components present in nonlinguistic events is predictive of children's later verb vocabulary. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Impairment variables predicting activity limitation in individuals with lower limb amputation.

    PubMed

    Raya, Michele A; Gailey, Robert S; Fiebert, Ira M; Roach, Kathyrn E

    2010-03-01

    The purpose of this study was to determine whether measures of impairment (i.e., muscle strength, balance), personal factors (i.e., comorbidities, demographic information) and amputation specific variables (i.e., time since amputation, cause of amputation, level of amputation) were able to predict performance on the six-minute walk test, a measure of activity limitation, in individuals with lower limb amputation. A total of 72 individuals with lower limb amputation ranging in age from 21-83 were tested for balance, limb muscle strength and function. Medical comorbidities were recorded and activity limitation was measured using the six-minute walk test. Data were analyzed and multivariate relationships were examined using multiple linear regression. Impairment variables of strength, balance, subject demographics, time since amputation, cause of amputation and level of amputation were all significant predictors and explained 72% of the variance in the outcome variable. Strength of the hip extensors was the strongest predictor, accounting for 30.9% of the total variance. Multiple factors impact six minute walk scores in individuals with lower limb amputation. Impairments in hip strength and balance appear to be the two most significant. The findings of this study support the use of the six-minute walk test to underscore impairments of the musculoskeletal system that can affect ambulation ability in the amputee.

  18. Individual differences in left parietal white matter predict math scores on the Preliminary Scholastic Aptitude Test.

    PubMed

    Matejko, Anna A; Price, Gavin R; Mazzocco, Michèle M M; Ansari, Daniel

    2013-02-01

    Mathematical skills are of critical importance, both academically and in everyday life. Neuroimaging research has primarily focused on the relationship between mathematical skills and functional brain activity. Comparatively few studies have examined which white matter regions support mathematical abilities. The current study uses diffusion tensor imaging (DTI) to test whether individual differences in white matter predict performance on the math subtest of the Preliminary Scholastic Aptitude Test (PSAT). Grades 10 and 11 PSAT scores were obtained from 30 young adults (ages 17-18) with wide-ranging math achievement levels. Tract based spatial statistics was used to examine the correlation between PSAT math scores, fractional anisotropy (FA), radial diffusivity (RD) and axial diffusivity (AD). FA in left parietal white matter was positively correlated with math PSAT scores (specifically in the left superior longitudinal fasciculus, left superior corona radiata, and left corticospinal tract) after controlling for chronological age and same grade PSAT critical reading scores. Furthermore, RD, but not AD, was correlated with PSAT math scores in these white matter microstructures. The negative correlation with RD further suggests that participants with higher PSAT math scores have greater white matter integrity in this region. Individual differences in FA and RD may reflect variability in experience dependent plasticity over the course of learning and development. These results are the first to demonstrate that individual differences in white matter are associated with mathematical abilities on a nationally administered scholastic aptitude measure.

  19. Predicting brain activation patterns associated with individual lexical concepts based on five sensory-motor attributes

    PubMed Central

    Fernandino, Leonardo; Humphries, Colin J.; Seidenberg, Mark S.; Gross, William L.; Conant, Lisa L.; Binder, Jeffrey R.

    2015-01-01

    While major advances have been made in uncovering the neural processes underlying perceptual representations, our grasp of how the brain gives rise to conceptual knowledge remains relatively poor. Recent work has provided strong evidence that concepts rely, at least in part, on the same sensory and motor neural systems through which they were acquired, but it is still unclear whether the neural code for concept representation uses information about sensory-motor features to discriminate between concepts. In the present study, we investigate this question by asking whether an encoding model based on five semantic attributes directly related to sensory-motor experience – sound, color, visual motion, shape, and manipulation – can successfully predict patterns of brain activation elicited by individual lexical concepts. We collected ratings on the relevance of these five attributes to the meaning of 820 words, and used these ratings as predictors in a multiple regression model of the fMRI signal associated with the words in a separate group of participants. The five resulting activation maps were then combined by linear summation to predict the distributed activation pattern elicited by a novel set of 80 test words. The encoding model predicted the activation patterns elicited by the test words significantly better than chance. As expected, prediction was successful for concrete but not for abstract concepts. Comparisons between encoding models based on different combinations of attributes indicate that all five attributes contribute to the representation of concrete concepts. Consistent with embodied theories of semantics, these results show, for the first time, that the distributed activation pattern associated with a concept combines information about different sensory-motor attributes according to their respective relevance. Future research should investigate how additional features of phenomenal experience contribute to the neural representation of conceptual

  20. Using individual patient anatomy to predict protocol compliance for prostate intensity-modulated radiotherapy

    SciTech Connect

    Caine, Hannah; Whalley, Deborah; Kneebone, Andrew; McCloud, Philip; Eade, Thomas

    2016-04-01

    If a prostate intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) plan has protocol violations, it is often a challenge knowing whether this is due to unfavorable anatomy or suboptimal planning. This study aimed to create a model to predict protocol violations based on patient anatomical variables and their potential relationship to target and organ at risk (OAR) end points in the setting of definitive, dose-escalated IMRT/VMAT prostate planning. Radiotherapy plans from 200 consecutive patients treated with definitive radiation for prostate cancer using IMRT or VMAT were analyzed. The first 100 patient plans (hypothesis-generating cohort) were examined to identify anatomical variables that predict for dosimetric outcome, in particular OAR end points. Variables that scored significance were further assessed for their ability to predict protocol violations using a Classification and Regression Tree (CART) analysis. These results were then validated in a second group of 100 patients (validation cohort). In the initial analysis of the hypothesis-generating cohort, percentage of rectum overlap in the planning target volume (PTV) (%OR) and percentage of bladder overlap in the PTV (%OB) were highlighted as significant predictors of rectal and bladder dosimetry. Lymph node treatment was also significant for bladder outcomes. For the validation cohort, CART analysis showed that %OR of < 6%, 6% to 9% and > 9% predicted a 13%, 63%, and 100% rate of rectal protocol violations respectively. For the bladder, %OB of < 9% vs > 9% is associated with 13% vs 88% rate of bladder constraint violations when lymph nodes were not treated. If nodal irradiation was delivered, plans with a %OB of < 9% had a 59% risk of violations. Percentage of rectum and bladder within the PTV can be used to identify individual plan potential to achieve dose-volume histogram (DVH) constraints. A model based on these factors could be used to reduce planning time, improve

  1. Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson’s Patients

    PubMed Central

    Przybyszewski, Andrzej W.; Kon, Mark; Szlufik, Stanislaw; Szymanski, Artur; Habela, Piotr; Koziorowski, Dariusz M.

    2016-01-01

    We still do not know how the brain and its computations are affected by nerve cell deaths and their compensatory learning processes, as these develop in neurodegenerative diseases (ND). Compensatory learning processes are ND symptoms usually observed at a point when the disease has already affected large parts of the brain. We can register symptoms of ND such as motor and/or mental disorders (dementias) and even provide symptomatic relief, though the structural effects of these are in most cases not yet understood. It is very important to obtain early diagnosis, which can provide several years in which we can monitor and partly compensate for the disease’s symptoms, with the help of various therapies. In the case of Parkinson’s disease (PD), in addition to classical neurological tests, measurements of eye movements are diagnostic. We have performed measurements of latency, amplitude, and duration in reflexive saccades (RS) of PD patients. We have compared the results of our measurement-based diagnoses with standard neurological ones. The purpose of our work was to classify how condition attributes predict the neurologist’s diagnosis. For n = 10 patients, the patient age and parameters based on RS gave a global accuracy in predictions of neurological symptoms in individual patients of about 80%. Further, by adding three attributes partly related to patient ‘well-being’ scores, our prediction accuracies increased to 90%. Our predictive algorithms use rough set theory, which we have compared with other classifiers such as Naïve Bayes, Decision Trees/Tables, and Random Forests (implemented in KNIME/WEKA). We have demonstrated that RS are powerful biomarkers for assessment of symptom progression in PD. PMID:27649187

  2. Individual differences in childhood sleep problems predict later cognitive executive control.

    PubMed

    Friedman, Naomi P; Corley, Robin P; Hewitt, John K; Wright, Kenneth P

    2009-03-01

    To determine whether individual differences in developmental patterns of general sleep problems are associated with 3 executive function abilities-inhibiting, updating working memory, and task shifting-in late adolescence. 916 twins (465 female, 451 male) and parents from the Colorado Longitudinal Twin Study. Parents reported their children's sleep problems at ages 4 years, 5 y, 7 y, and 9-16 y based on a 7-item scale from the Child-Behavior Checklist; a subset of children (n = 568) completed laboratory assessments of executive functions at age 17. Latent variable growth curve analyses were used to model individual differences in longitudinal trajectories of childhood sleep problems. Sleep problems declined over time, with approximately 70% of children having > or = 1 problem at age 4 and approximately 33% of children at age 16. However, significant individual differences in both the initial levels of problems (intercept) and changes across time (slope) were observed. When executive function latent variables were added to the model, the intercept did not significantly correlate with the later executive function latent variables; however, the slope variable significantly (P < 0.05) negatively correlated with inhibiting (r = -0.27) and updating (r = -0.21), but not shifting (r = -0.10) abilities. Further analyses suggested that the slope variable predicted the variance common to the 3 executive functions (r = -0.29). Early levels of sleep problems do not seem to have appreciable implications for later executive functioning. However, individuals whose sleep problems decrease more across time show better general executive control in late adolescence.

  3. Numerical flow simulation and efficiency prediction for axial turbines by advanced turbulence models

    NASA Astrophysics Data System (ADS)

    Jošt, D.; Škerlavaj, A.; Lipej, A.

    2012-11-01

    Numerical prediction of an efficiency of a 6-blade Kaplan turbine is presented. At first, the results of steady state analysis performed by different turbulence models for different operating regimes are compared to the measurements. For small and optimal angles of runner blades the efficiency was quite accurately predicted, but for maximal blade angle the discrepancy between calculated and measured values was quite large. By transient analysis, especially when the Scale Adaptive Simulation Shear Stress Transport (SAS SST) model with zonal Large Eddy Simulation (ZLES) in the draft tube was used, the efficiency was significantly improved. The improvement was at all operating points, but it was the largest for maximal discharge. The reason was better flow simulation in the draft tube. Details about turbulent structure in the draft tube obtained by SST, SAS SST and SAS SST with ZLES are illustrated in order to explain the reasons for differences in flow energy losses obtained by different turbulence models.

  4. Automated Irrigation System using Weather Prediction for Efficient Usage of Water Resources

    NASA Astrophysics Data System (ADS)

    Susmitha, A.; Alakananda, T.; Apoorva, M. L.; Ramesh, T. K.

    2017-08-01

    In agriculture the major problem which farmers face is the water scarcity, so to improve the usage of water one of the irrigation system using drip irrigation which is implemented is “Automated irrigation system with partition facility for effective irrigation of small scale farms” (AISPF). But this method has some drawbacks which can be improved and here we are with a method called “Automated irrigation system using weather prediction for efficient usage of water resources’ (AISWP), it solves the shortcomings of AISPF process. AISWP method helps us to use the available water resources more efficiently by sensing the moisture present in the soil and apart from that it is actually predicting the weather by sensing two parameters temperature and humidity thereby processing the measured values through an algorithm and releasing the water accordingly which is an added feature of AISWP so that water can be efficiently used.

  5. An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs

    DOE PAGES

    Zhu, Zizhong; Wu, Ping; Wu, Shunqing; ...

    2017-05-15

    An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has beenmore » applied to the case of LiFePO4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.« less

  6. Prediction and design of efficient exciplex emitters for high-efficiency, thermally activated delayed-fluorescence organic light-emitting diodes.

    PubMed

    Liu, Xiao-Ke; Chen, Zhan; Zheng, Cai-Jun; Liu, Chuan-Lin; Lee, Chun-Sing; Li, Fan; Ou, Xue-Mei; Zhang, Xiao-Hong

    2015-04-08

    High-efficiency, thermally activated delayed-fluorescence organic light-emitting diodes based on exciplex emitters are demonstrated. The best device, based on a TAPC:DPTPCz emitter, shows a high external quantum efficiency of 15.4%. Strategies for predicting and designing efficient exciplex emitters are also provided. This approach allow prediction and design of efficient exciplex emitters for achieving high-efficiency organic light-emitting diodes, for future use in displays and lighting applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Boldness predicts an individual's position along an exploration-exploitation foraging trade-off.

    PubMed

    Patrick, Samantha C; Pinaud, David; Weimerskirch, Henri

    2017-09-01

    Individuals do not have complete information about the environment and therefore they face a trade-off between gathering information (exploration) and gathering resources (exploitation). Studies have shown individual differences in components of this trade-off but how stable these strategies are in a population and the intrinsic drivers of these differences is not well understood. Top marine predators are expected to experience a particularly strong trade-off as many species have large foraging ranges and their prey often have a patchy distribution. This environment leads these species to exhibit pronounced exploration and exploitation phases but differences between individuals are poorly resolved. Personality differences are known to be important in foraging behaviour but also in the trade-off between exploration and exploitation. Here we test whether personality predicts an individual exploration-exploitation strategy using wide ranging wandering albatrosses (Diomedea exulans) as a model system. Using GPS tracking data from 276 wandering albatrosses, we extract foraging parameters indicative of exploration (searching) and exploitation (foraging) and show that foraging effort, time in patch and size of patch are strongly correlated, demonstrating these are indicative of an exploration-exploitation (EE) strategy. Furthermore, we show these are consistent within individuals and appear stable in the population, with no reproductive advantage. The searching and foraging behaviour of bolder birds placed them towards the exploration end of the trade-off, whereas shy birds showed greater exploitation. This result provides a mechanism through which individual foraging strategies may emerge. Age and sex affected components of the trade-off, but not the trade-off itself, suggesting these factors may drive behavioural compensation to maintain resource acquisition and this was supported by the evidence that there were no fitness consequence of any EE trait nor the trade

  8. Incremental Efficiency of WISC-III Factor Scores in Predicting Achievement: What Do They Tell Us?

    ERIC Educational Resources Information Center

    Glutting, Joseph J.; Youngstrom, Eric A.; Ward, Thomas; Ward, Sandra; Hale, Robert L.

    1997-01-01

    The incremental validity of factor scores from the Wechlser Intelligence Scale for Children-III (WISC-III) in predicting scores on the Wechsler Individual Achievement Test (WIAT) was studied in 283 nonreferred children and 636 referred for evaluation. The Full Scale IQ of the WISC-III was the best predictor of WIAT achievement. (SLD)

  9. Validation of spot urine in predicting 24-h sodium excretion at the individual level.

    PubMed

    Zhou, Long; Tian, Yu; Fu, Jun-Jie; Jiang, Ying-Ying; Bai, Ya-Min; Zhang, Zi-Hua; Hu, Xiao-He; Lian, Hong-Wu; Guo, Min; Yang, Zheng-Xiong; Zhao, Lian-Cheng

    2017-06-01

    Background: Evidence for the effect of dietary sodium intake on the risk of cardiovascular disease has been controversial. One of the main explanations for the conflicting results lies in the great variability associated with measurement methods for sodium intake. Spot urine collection is a convenient method commonly used for sodium estimation, but its validity for predicting 24-h urinary sodium excretion at the individual level has not been well evaluated among the general population.Objective: The aim of this study was to evaluate the validity of the Kawasaki, the International Cooperative Study on Salt, Other Factors, and Blood Pressure (INTERSALT), and the Tanaka formulas in predicting 24-h urinary sodium excretion by using spot urine samples in Chinese adults.Design: We analyzed the relative and absolute differences and misclassification at the individual level from 3 commonly used methods for estimating sodium intake among 141 Chinese community residents.Results: The mean measured 24-h sodium excretion was 220.8 mmol/d. The median (95% CIs) differences between measured sodium and those estimated from the Kawasaki, INTERSALT, and Tanaka methods were 6.4 mmol/d (-17.5, 36.8 mmol/d), -67.3 mmol/d (-96.5, -46.9 mmol/d), and -42.9 mmol/d (-59.1, -24.8 mmol/d), respectively. The proportions of relative differences >40% with the Kawasaki, INTERSALT, and Tanaka methods were 31.2%, 41.1%, and 22.0%, respectively; and the absolute difference for the 3 methods was >51.3 mmol/d (3 g salt) in approximately half of the participants. The misclassification rate was 63.1% for the Kawasaki method, 78.7% for the INTERSALT method, and 66.0% for the Tanaka method at the individual level.Conclusion: The results from our study do not support the use of spot urine to estimate 24-h urinary sodium excretion at the individual level because of its poor performance with respect to misclassification. This trial was registered at www.chictr.org.cn as ChiCTR-IOR-16010278. © 2017 American

  10. Predicting longitudinal change in language production and comprehension in individuals with Down syndrome: hierarchical linear modeling.

    PubMed

    Chapman, Robin S; Hesketh, Linda J; Kistler, Doris J

    2002-10-01

    Longitudinal change in syntax comprehension and production skill, measured four times across a 6-year period, was modeled in 31 individuals with Down syndrome who were between the ages of 5 and 20 years at the start of the study. Hierarchical Linear Modeling was used to fit individual linear growth curves to the measures of syntax comprehension (TACL-R) and mean length of spontaneous utterances obtained in 12-min narrative tasks (MLU-S), yielding two parameters for each participant's comprehension and production: performance at study start and growth trajectory. Predictor variables were obtained by fitting linear growth curves to each individual's concurrent measures of nonverbal visual cognition (Pattern Analysis subtest of the Stanford-Binet), visual short-term memory (Bead Memory subtest), and auditory short-term memory (digit span), yielding two individual predictor parameters for each measure: performance at study start and growth trajectory. Chronological age at study start (grand-mean centered), sex, and hearing status were also taken as predictors. The best-fitting HLM model of the comprehension parameters uses age at study start, visual short-term memory, and auditory short-term memory as predictors of initial status and age at study start as a predictor of growth trajectory. The model accounted for 90% of the variance in intercept parameters, 79% of the variance in slope parameters, and 24% of the variance at level 1. The some predictors were significant predictors of initial status in the best model for production, with no measures predicting slope. The model accounted for 81% of the intercept variance and 43% of the level 1 variance. When comprehension parameters are added to the predictor set, the best model, accounting for 94% of the intercept and 22% of the slope variance, uses only comprehension at study start as a predictor of initial status and comprehension slope as a predictor of production slope. These results reflect the fact that expressive

  11. Impact of microbial efficiency to predict MP supply when estimating protein requirements of growing beef cattle from performance.

    PubMed

    Watson, A K; Klopfenstein, T J; Erickson, G E; MacDonald, J C; Wilkerson, V A

    2017-07-01

    Data from 16 trials were compiled to calculate microbial CP (MCP) production and MP requirements of growing cattle on high-forage diets. All cattle were individually fed diets with 28% to 72% corn cobs in addition to either alfalfa, corn silage, or sorghum silage at 18% to 60% of the diet (DM basis). The remainder of the diet consisted of protein supplement. Source of protein within the supplement varied and included urea, blood meal, corn gluten meal, dry distillers grains, feather meal, meat and bone meal, poultry by-product meal, soybean meal, and wet distillers grains. All trials included a urea-only treatment. Intake of all cattle within an experiment was held constant, as a percentage of BW, established by the urea-supplemented group. In each trial the base diet (forage and urea supplement) was MP deficient. Treatments consisted of increasing amounts of test protein replacing the urea supplement. As protein in the diet increased, ADG plateaued. Among experiments, ADG ranged from 0.11 to 0.73 kg. Three methods of calculating microbial efficiency were used to determine MP supply. Gain was then regressed against calculated MP supply to determine MP requirement for maintenance and gain. Method 1 (based on a constant 13% microbial efficiency as used by the beef NRC model) predicted an MP maintenance requirement of 3.8 g/kg BW and 385 g MP/kg gain. Method 2 calculated microbial efficiency using low-quality forage diets and predicted MP requirements of 3.2 g/kg BW for maintenance and 448 g/kg for gain. Method 3 (based on an equation predicting MCP yield from TDN intake, proposed by the Beef Cattle Nutrient Requirements Model [BCNRM]) predicted MP requirements of 3.1 g/kg BW for maintenance and 342 g/kg for gain. The factorial method of calculating MP maintenance requirements accounts for scurf, endogenous urinary, and metabolic fecal protein losses and averaged 4.2 g/kg BW. Cattle performance data demonstrate formulating diets to meet the beef NRC model recommended

  12. Wandering in both mind and body: individual differences in mind wandering and inattention predict fidgeting.

    PubMed

    Carriere, Jonathan S A; Seli, Paul; Smilek, Daniel

    2013-03-01

    Anecdotal reports suggest that during periods of inattention or mind wandering, people tend to experience increased fidgeting. In four studies, we examined whether individual differences in the tendency to be inattentive and to mind wander in everyday life are related to the tendency to make spontaneous and involuntary movements (i.e., to fidget). To do so, we developed self-report measures of spontaneous and deliberate mind wandering, as well as a self-report scale to index fidgeting. In addition, we used several existing self-report measures of inattentiveness, attentional control, and memory failures. Across our studies, a series of multiple regression analyses indicated that fidgeting was uniquely predicted by inattentiveness and spontaneous mind wandering but not by other related factors, including deliberate mind wandering, attentional control, and memory failures. As a result, we suggest that only spontaneously wandering thoughts are related to a wandering body.

  13. Asymmetry in pay-off predicts how familiar individuals respond to one another.

    PubMed

    Granroth-Wilding, Hanna M V; Magurran, Anne E

    2013-06-23

    Familiarity influences individual decision-making in many vertebrate species. Here, we propose that familiarity modulates behaviour to different extents depending on the social context of the interaction. Specifically, the more that one player stands to gain relative to the other, the less important familiarity will be in influencing their responses to one another. We test this prediction using pairs of male guppies (Poecilia reticulata) in three competitive scenarios of increasing asymmetry in outcome to the two players: schooling under potential threat (similar outcomes), competing for a defensible food source (some asymmetry) and competing for a receptive female (strongly asymmetrical outcomes). Males show a graded response as asymmetry increases, with familiarity producing marked behavioural differences under potential threat, minor changes when competing for food, but none at all in competition for mating opportunities. This suggests that mutualistic benefits can arise as a by-product of selfish behaviour, supporting the role of pseudo-reciprocity in the evolution of cooperation.

  14. Olfactory Performance Is Predicted by Individual Sex-Atypicality, but Not Sexual Orientation

    PubMed Central

    Nováková, Lenka; Varella Valentová, Jaroslava; Havlíček, Jan

    2013-01-01

    Many previous studies have reported robust sex differences in olfactory perception. However, both men and women can be expected to vary in the degree to which they exhibit olfactory performance considered typical of their own or the opposite sex. Sex-atypicality is often described in terms of childhood gender nonconformity, which, however, is not a perfect correlate of non-heterosexual orientation. Here we explored intrasexual variability in psychophysical olfactory performance in a sample of 156 individuals (83 non-heterosexual) and found the lowest odor identification scores in heterosexual men. However, when childhood gender nonconformity was entered in the model along with sexual orientation, better odor identification scores were exhibited by gender-nonconforming men, and greater olfactory sensitivity by gender-conforming women, irrespective of their sexual orientation. Thus, sex-atypicality, but not sexual orientation predicts olfactory performance, and we propose that this might not be limited to olfaction, but represent a more general phenomenon. PMID:24244657

  15. FKBP5 and Emotional Neglect Interact to Predict Individual Differences in Amygdala Reactivity

    PubMed Central

    White, Michael G.; Bogdan, Ryan; Fisher, Patrick M.; Muñoz, Karen; Williamson, Douglas E.; Hariri, Ahmad R.

    2013-01-01

    Individual variation in physiological responsiveness to stress mediates risk for mental illness and is influenced by both experiential and genetic factors. Common polymorphisms in the human gene for FK506 binding protein 5 (FKBP5), which is involved in transcriptional regulation of the hypothalamic-pituitary-adrenal (HPA) axis, have been shown to interact with childhood abuse and trauma to predict stress-related psychopathology. In the current study, we examined if such gene-environment interaction effects may be related to variability in the threat-related reactivity of the amygdala, which plays a critical role in mediating physiological and behavioral adaptions to stress including modulation of the HPA axis. To this end 139 healthy, Caucasian youth completed a BOLD fMRI probe of amygdala reactivity and self-report assessments of emotional neglect (EN) and other forms of maltreatment. These individuals were genotyped for six FKBP5 polymorphisms (rs7748266, rs1360780, rs9296158, rs3800373, rs9470080, and rs9394309) previously associated with psychopathology and/or HPA axis function. Interactions between each SNP and EN emerged such that risk alleles predicted relatively increased dorsal amygdala reactivity in the context of higher EN, even after correcting for multiple testing. Two different haplotype analyses confirmed this relationship as haplotypes with risk alleles also exhibited increased amygdala reactivity in the context of higher EN. Our results suggest that increased threat-related amygdala reactivity may represent a mechanism linking psychopathology to interactions between common genetic variants affecting HPA axis function and childhood trauma. PMID:22979952

  16. An Examination of Polygenic Score Risk Prediction in Individuals With First-Episode Psychosis.

    PubMed

    Vassos, Evangelos; Di Forti, Marta; Coleman, Jonathan; Iyegbe, Conrad; Prata, Diana; Euesden, Jack; O'Reilly, Paul; Curtis, Charles; Kolliakou, Anna; Patel, Hamel; Newhouse, Stephen; Traylor, Matthew; Ajnakina, Olesya; Mondelli, Valeria; Marques, Tiago Reis; Gardner-Sood, Poonam; Aitchison, Katherine J; Powell, John; Atakan, Zerrin; Greenwood, Kathryn E; Smith, Shubulade; Ismail, Khalida; Pariante, Carmine; Gaughran, Fiona; Dazzan, Paola; Markus, Hugh S; David, Anthony S; Lewis, Cathryn M; Murray, Robin M; Breen, Gerome

    2017-03-15

    Polygenic risk scores (PRSs) have successfully summarized genome-wide effects of genetic variants in schizophrenia with significant predictive power. In a clinical sample of first-episode psychosis (FEP) patients, we estimated the ability of PRSs to discriminate case-control status and to predict the development of schizophrenia as opposed to other psychoses. The sample (445 case and 265 control subjects) was genotyped on the Illumina HumanCore Exome BeadChip with an additional 828 control subjects of African ancestry genotyped on the Illumina Multi-Ethnic Genotyping Array. To calculate PRSs, we used the results from the latest Psychiatric Genomics Consortium schizophrenia meta-analysis. We examined the association of PRSs with case-control status and with schizophrenia versus other psychoses in European and African ancestry FEP patients and in a second sample of 248 case subjects with chronic psychosis. PRS had good discriminative ability of case-control status in FEP European ancestry individuals (9.4% of the variance explained, p < 10(-6)), but lower in individuals of African ancestry (R(2) = 1.1%, p = .004). Furthermore, PRS distinguished European ancestry case subjects who went on to acquire a schizophrenia diagnosis from those who developed other psychotic disorders (R(2) = 9.2%, p = .002). PRS was a powerful predictor of case-control status in a European sample of patients with FEP, even though a large proportion did not have an established diagnosis of schizophrenia at the time of assessment. PRS was significantly different between those case subjects who developed schizophrenia from those who did not, although the discriminative accuracy may not yet be sufficient for clinical utility in FEP. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  17. Attentional and motor impulsivity interactively predict 'food addiction' in obese individuals.

    PubMed

    Meule, Adrian; de Zwaan, Martina; Müller, Astrid

    2017-01-01

    Impulsivity is a multifaceted construct and constitutes a common risk factor for a range of behaviors associated with poor self-control (e.g., substance use or binge eating). The short form of the Barratt Impulsiveness Scale (BIS-15) measures impulsive behaviors related to attentional (inability to focus attention or concentrate), motor (acting without thinking), and non-planning (lack of future orientation or forethought) impulsivity. Eating-related measures appear to be particularly related to attentional and motor impulsivity and recent findings suggest that interactive effects between these two facets may play a role in eating- and weight-regulation. One-hundred thirty-three obese individuals presenting for bariatric surgery (77.4% female) completed the BIS-15 and the Yale Food Addiction Scale (YFAS) 2.0, which measures addiction-like eating based on the eleven symptoms of substance use disorder outlined in the fifth version of the Diagnostic and Statistical Manual of Mental Disorders. Sixty-three participants (47.4%) were classified as being 'food addicted'. Scores on attentional and motor impulsivity interactively predicted 'food addiction' status: higher attentional impulsivity was associated with a higher likelihood of receiving a YFAS 2.0 diagnosis only at high (+1 SD), but not at low (-1 SD) levels of motor impulsivity. Results support previous findings showing that non-planning impulsivity does not appear to play a role in eating-related self-regulation. Furthermore, this is the first study that shows interactive effects between different impulsivity facets when predicting 'food addiction' in obese individuals. Self-regulatory failure in eating-regulation (e.g., addiction-like overeating) may particularly emerge when both attentional and motor impulsivity levels are elevated. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Prediction of individual genetic risk to prostate cancer using a polygenic score.

    PubMed

    Szulkin, Robert; Whitington, Thomas; Eklund, Martin; Aly, Markus; Eeles, Rosalind A; Easton, Douglas; Kote-Jarai, Z Sofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel M; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Lubiński, Jan; Kluźniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Stegmaier, Christa; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Lim, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Gronberg, Henrik; Wiklund, Fredrik

    2015-09-01

    Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. © 2015 Wiley Periodicals, Inc.

  19. Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11.

    PubMed

    Liu, Tong; Wang, Yiheng; Eickholt, Jesse; Wang, Zheng

    2016-01-14

    Quality assessment of a protein model is to predict the absolute or relative quality of a protein model using computational methods before the native structure is available. Single-model methods only need one model as input and can predict the absolute residue-specific quality of an individual model. Here, we have developed four novel single-model methods (Wang_deep_1, Wang_deep_2, Wang_deep_3, and Wang_SVM) based on stacked denoising autoencoders (SdAs) and support vector machines (SVMs). We evaluated these four methods along with six other methods participating in CASP11 at the global and local levels using Pearson's correlation coefficients and ROC analysis. As for residue-specific quality assessment, our four methods achieved better performance than most of the six other CASP11 methods in distinguishing the reliably modeled residues from the unreliable measured by ROC analysis; and our SdA-based method Wang_deep_1 has achieved the highest accuracy, 0.77, compared to SVM-based methods and our ensemble of an SVM and SdAs. However, we found that Wang_deep_2 and Wang_deep_3, both based on an ensemble of multiple SdAs and an SVM, performed slightly better than Wang_deep_1 in terms of ROC analysis, indicating that integrating an SVM with deep networks works well in terms of certain measurements.

  20. Individual differences in social dominance orientation predict support for the use of cognitive ability tests.

    PubMed

    Kim, Anita; Berry, Christopher M

    2015-02-01

    This study investigates the personality processes involved in the debate surrounding the use of cognitive ability tests in college admissions. In Study 1, 108 undergraduates (Mage  = 18.88 years, 60 women, 80 Whites) completed measures of social dominance orientation (SDO), testing self-efficacy, and attitudes regarding the use of cognitive ability tests in college admissions; SAT/ACT scores were collected from the registrar. Sixty-seven undergraduates (Mage  = 19.06 years, 39 women, 49 Whites) completed the same measures in Study 2, along with measures of endorsement of commonly presented arguments about test use. In Study 3, 321 American adults (Mage  = 35.58 years, 180 women, 251 Whites) completed the same measures used in Study 2; half were provided with facts about race and validity issues surrounding cognitive ability tests. Individual differences in SDO significantly predicted support for the use of cognitive ability tests in all samples, after controlling for SAT/ACT scores and test self-efficacy and also among participants who read facts about cognitive ability tests. Moreover, arguments for and against test use mediated this effect. The present study sheds new light on an old debate by demonstrating that individual differences in beliefs about hierarchy play a key role in attitudes toward cognitive ability test use.

  1. Evidence for predictive validity of blood assays to evaluate individual radiosensitivity

    SciTech Connect

    Severin, Erhard . E-mail: severie@uni-muenster.de; Greve, Burkhard; Pascher, Elke; Wedemeyer, Niels; Hacker-Klom, Ursula; Silling, Gerda; Kienast, Joachim; Willich, Normann; Goehde, Wolfgang

    2006-01-01

    Purpose: An escalation in standard irradiation dose ensuring improved local tumor control is estimated, but this strategy would require the exclusion of the most sensitive individuals from treatment. Therefore, fast and reliable assays for prediction of the individual radiosensitivity are urgently required. Methods and Materials: Seven parameters in lymphocytes of 40 patients with leukemia were analyzed before, during, and after total body irradiation (TBI) and in vitro X-ray irradiation. These were: cell proliferation, nuclear damage, activation of cytokines, and numbers of total leukocytes of CD34+ hematopoietic blood stem cells and of CD4+ and CD8+ lymphocytes. Additionally, antioxidative capacity of blood plasma, uric acid, and hemoglobin levels were measured. Blood samples of 67 healthy donors were used as controls. Results: In vivo and in vitro irradiations showed comparable results. A dose-response relationship was found for most parameters. Three parameters were associated with severe acute oral mucositis (Grade 3 or 4 vs. Grade 0 to 2): leukocytes fewer than 6200/{mu}L after 4 Gy TBI, a rate of >19% lymphocytes with reduced DNA and protein content ('necroses') after 4 Gy in vitro irradiation, and a small antioxidative capacity in blood plasma (<0.68 mMol) after 8 Gy TBI. Conclusion: Three simple blood assays were associated with oral mucositis that are posed here hypothetically as an early symptom of enhanced radiosensitivity in leukemic patients: leukocyte count, damaged lymphocyte score, and the antioxidative capacity after exposure.

  2. PLASMA OXYTOCIN LEVELS PREDICT SOCIAL CUE RECOGNITION IN INDIVIDUALS WITH SCHIZOPHRENIA

    PubMed Central

    Strauss, Gregory P.; Keller, William R.; Koenig, James I.; Gold, James M.; Frost, Katherine H.; Buchanan, Robert W.

    2015-01-01

    Lower endogenous levels of the neuropeptide oxytocin may be an important biological predictor of social cognition impairments in schizophrenia (SZ). Prior studies have demonstrated that lower-level social cognitive processes (e.g., facial affect perception) are significantly associated with reduced plasma oxytocin levels in SZ; however, it is unclear whether higher-level social cognition, which requires inferential processes and knowledge not directly presented in the stimulus, is associated with endogenous oxytocin. The current study explored the association between endogenous oxytocin levels and lower- and higher-level social cognition in 40 individuals diagnosed with SZ and 22 demographically matched healthy controls (CN). All participants received the Social Cue Recognition Test (SCRT), which presents participants with videotaped interpersonal vignettes and subsequent true/false questions related to concrete or abstract aspects of social interactions in the vignettes. Results indicated that SZ had significantly higher plasma oxytocin concentrations than CN. SZ and CN did not differ on SCRT hits, but SZ had more false positives and lower sensitivity scores than CN. Higher plasma oxytocin levels were associated with better sensitivity scores for abstract items in CN and fewer false positives for concrete items in individuals with SZ. Findings indicate that endogenous oxytocin levels predict accurate encoding of lower-level socially relevant information in SZ. PMID:25673435

  3. Plausibility of Individual Decisions from Random Forests in Clinical Predictive Modelling Applications.

    PubMed

    Hayn, Dieter; Walch, Harald; Stieg, Jörg; Kreiner, Karl; Ebner, Hubert; Schreier, Günter

    2017-01-01

    Machine learning algorithms are a promising approach to help physicians to deal with the ever increasing amount of data collected in healthcare each day. However, interpretation of suggestions derived from predictive models can be difficult. The aim of this work was to quantify the influence of a specific feature on an individual decision proposed by a random forest (RF). For each decision tree within the RF, the influence of each feature on a specific decision (FID) was quantified. For each feature, changes in outcome value due to the feature were summarized along the path. Results from all the trees in the RF were statistically merged. The ratio of FID to the respective feature's global importance was calculated (FIDrel). Global feature importance, FID and FIDrel significantly differed, depending on the individual input data. Therefore, we suggest to present the most important features as determined for FID and for FIDrel, whenever results of a RF are visualized. Feature influence on a specific decision can be quantified in RFs. Further studies will be necessary to evaluate our approach in a real world scenario.

  4. Individualized Early Prediction of Familial Risk of Dyslexia: A Study of Infant Vocabulary Development.

    PubMed

    Chen, Ao; Wijnen, Frank; Koster, Charlotte; Schnack, Hugo

    2017-01-01

    We examined early vocabulary development in children at familial risk (FR) of dyslexia and typically developing (TD) children between 17 and 35 months of age. We trained a support vector machine to classify TD and FR using these vocabulary data at the individual level. The Dutch version of the McArthur-Bates Communicative Development Inventory (Words and Sentences) (N-CDI) was used to measure vocabulary development. We analyzed group-level differences for both total vocabulary as well as lexical classes: common nouns, predicates, and closed class words. The generalizability of the classification model was tested using cross-validation. At the group level, for both total vocabulary and the composites, the difference between TD and FR was most pronounced at 19-20 months, with FRs having lower scores. For the individual prediction, highest cross-validation accuracy (68%) was obtained at 19-20 months, with sensitivity (correctly classified FR) being 70% and specificity (correctly classified TD) being 67%. There is a sensitive window in which the difference between FR and TD is most evident. Machine learning methods are promising techniques for separating FR and TD children at an early age, before they start reading.

  5. Individualized Early Prediction of Familial Risk of Dyslexia: A Study of Infant Vocabulary Development

    PubMed Central

    Chen, Ao; Wijnen, Frank; Koster, Charlotte; Schnack, Hugo

    2017-01-01

    We examined early vocabulary development in children at familial risk (FR) of dyslexia and typically developing (TD) children between 17 and 35 months of age. We trained a support vector machine to classify TD and FR using these vocabulary data at the individual level. The Dutch version of the McArthur-Bates Communicative Development Inventory (Words and Sentences) (N-CDI) was used to measure vocabulary development. We analyzed group-level differences for both total vocabulary as well as lexical classes: common nouns, predicates, and closed class words. The generalizability of the classification model was tested using cross-validation. At the group level, for both total vocabulary and the composites, the difference between TD and FR was most pronounced at 19–20 months, with FRs having lower scores. For the individual prediction, highest cross-validation accuracy (68%) was obtained at 19–20 months, with sensitivity (correctly classified FR) being 70% and specificity (correctly classified TD) being 67%. There is a sensitive window in which the difference between FR and TD is most evident. Machine learning methods are promising techniques for separating FR and TD children at an early age, before they start reading. PMID:28270778

  6. Prediction of individual implant bone levels and the existence of implant "phenotypes".

    PubMed

    Papantonopoulos, Georgios; Gogos, Christos; Housos, Efthymios; Bountis, Tassos; Loos, Bruno G

    2017-07-01

    To cluster implants placed in patients of a private practice and identify possible implant "phenotypes" and predictors of individual implant mean bone levels (IIMBL). Clinical and radiographical variables were collected from 72 implant-treated patients with 237 implants and a mean 7.4 ± 3.5 years of function. We clustered implants using the k-means method guided by multidimensional unfolding. For predicting IIMBL, we used principal component analysis (PCA) as a variable reduction method for an ensemble selection (ES) and a support vector machines models (SVMs). Network analysis investigated variable interactions. We identified a cluster of implants susceptible to peri-implantitis (96% of the implants in the cluster were affected by peri-implantitis) and two overlapping clusters of implants resistant to peri-implantitis. The cluster susceptible to peri-implantitis showed a mean IIMBL of 5.2 mm and included implants placed mainly in the lower front jaw and in mouths having a mean of eight teeth. PCA extracted the parameters such as number of teeth, full-mouth plaque scores, implant surface, periodontitis severity, age and diabetes as significant in explaining the data variability. ES and SVMs showed good results in predicting IIMBL (root-mean-squared error of 0.133 and 0.149, 10-fold cross-validation error of 0.147 and 0.150, respectively). Network analysis revealed limited interdependencies of variables among peri-implantitis-affected and non-affected implants and supported the hypothesis of the existence of distinct implant "phenotypes." Two implant "phenotypes" were identified, one with susceptibility and another with resistance to peri-implantitis. Prediction of IIMBL could be achieved by using six variables. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Predictive and Feedback Performance Errors are Signaled in the Simple Spike Discharge of Individual Purkinje Cells

    PubMed Central

    Popa, Laurentiu S.; Hewitt, Angela L.; Ebner, Timothy J.

    2012-01-01

    The cerebellum has been implicated in processing motor errors required for online control of movement and motor learning. The dominant view is that Purkinje cell complex spike discharge signals motor errors. This study investigated whether errors are encoded in the simple spike discharge of Purkinje cells in monkeys trained to manually track a pseudo-randomly moving target. Four task error signals were evaluated based on cursor movement relative to target movement. Linear regression analyses based on firing residuals ensured that the modulation with a specific error parameter was independent of the other error parameters and kinematics. The results demonstrate that simple spike firing in lobules IV–VI is significantly correlated with position, distance and directional errors. Independent of the error signals, the same Purkinje cells encode kinematics. The strongest error modulation occurs at feedback timing. However, in 72% of cells at least one of the R2 temporal profiles resulting from regressing firing with individual errors exhibit two peak R2 values. For these bimodal profiles, the first peak is at a negative τ (lead) and a second peak at a positive τ (lag), implying that Purkinje cells encode both prediction and feedback about an error. For the majority of the bimodal profiles, the signs of the regression coefficients or preferred directions reverse at the times of the peaks. The sign reversal results in opposing simple spike modulation for the predictive and feedback components. Dual error representations may provide the signals needed to generate sensory prediction errors used to update a forward internal model. PMID:23115173

  8. Efficient temporal search range prediction for motion estimation in H.264

    NASA Astrophysics Data System (ADS)

    Kim, Changsung; Kuo, C.-C. Jay

    2005-08-01

    An efficient search range prediction method is proposed to reduce the complexity of motion search in the H.264 video coding standard in this work. The main idea is to predict the temporal search range by modeling the relationship between the rate-distortion (RD) coding gain and the required computational complexity. The proposed algorithm first predicts the temporal search range to maximize the ratio of the expected RD coding gain and the normalized computational cost. Then, fast motion search is performed within the predicted search range with some early termination rule. Experimental results show that the proposed algorithm can save approximately 63-75% of the encoding complexity in motion estimation of H.264 (JM9.3) with negligible degradation in the RD performance.

  9. Individualized Prediction and Clinical Staging of Bipolar Disorders using Neuroanatomical Biomarkers

    PubMed Central

    Mwangi, Benson; Wu, Mon-Ju; Cao, Bo; Passos, Ives C.; Lavagnino, Luca; Keser, Zafer; Zunta-Soares, Giovana B.; Hasan, Khader M.; Kapczinski, Flavio; Soares, Jair C.

    2016-01-01

    Background Neuroanatomical abnormalities in Bipolar disorder (BD) have previously been reported. However, the utility of these abnormalities in distinguishing individual BD patients from Healthy controls and stratify patients based on overall illness burden has not been investigated in a large cohort. Methods In this study, we examined whether structural neuroimaging scans coupled with a machine learning algorithm are able to distinguish individual BD patients from Healthy controls in a large cohort of 256 subjects. Additionally, we investigated the relationship between machine learning predicted probability scores and subjects’ clinical characteristics such as illness duration and clinical stages. Neuroimaging scans were acquired from 128 BD patients and 128 Healthy controls. Gray and white matter density maps were obtained and used to ‘train’ a relevance vector machine (RVM) learning algorithm which was used to distinguish individual patients from Healthy controls. Results The RVM algorithm distinguished patients from Healthy controls with 70.3 % accuracy (74.2 % specificity, 66.4 % sensitivity, chi-square p<0.005) using white matter density data and 64.9 % accuracy (71.1 % specificity, 58.6 % sensitivity, chi-square p<0.005) with gray matter density. Multiple brain regions – largely covering the fronto – limbic system were identified as ‘most relevant’ in distinguishing both groups. Patients identified by the algorithm with high certainty (a high probability score) – belonged to a subgroup with more than ten total lifetime manic episodes including hospitalizations (late stage). Conclusions These results indicate the presence of widespread structural brain abnormalities in BD which are associated with higher illness burden – which points to neuroprogression. PMID:27047994

  10. Prediction and quantification of individual differences in susceptibility to simulator sickness in fixed-base simulators

    NASA Astrophysics Data System (ADS)

    Yoo, Young H.

    Simulator sickness in a fixed-base simulator is a form of visually-induced motion sickness. Visual-vestibular interaction on spatial orientation and postural control predicts that vection information in the visual stimuli triggers compensatory head sways to stabilize body orientation to perceived visual motion. Simulator sickness might result from perceptual conflicts caused by the visual-vestibular interaction in unusual environments (i.e., fixed-base simulators). Relationship between simulator sickness, vection, and compensatory head sways to perceived vection might help to quantify and predict presence and magnitude of simulator sickness in simulated environments. It was hypothesized that there was significant and positive relationship between sickness, vection, and compensatory head sways. Existence of individual differences was also possible, depending on individual sensitivity to vection. It was also hypothesized that females would experience more intense vection than males because females have wider periphery and shorter vection latencies. Correlations and the multiple linear regression analyses were performed to test the linear relationship between simulator sickness, vection, head sway, gender, and age. There was significant linear relationship between variables. It was concluded that vection and Y-velocity are significant predictors by itself and in interaction forms. Interaction between gender and vection, Y-velocity, and age in the regression function implied that gender difference is significant and gender is also a significant predictor of simulator sickness. Therefore, it was also concluded that there was significant gender difference in susceptibility to simulator sickness between males and females. General linear model also indicates that mean difference in magnitudes of vection, and Y-velocity and difference in gender and age have effects on the magnitude of simulator sickness. Time-course of vection implies that magnitude of vection increases as

  11. Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

    PubMed

    Martínez, Kenia; Janssen, Joost; Pineda-Pardo, José Ángel; Carmona, Susanna; Román, Francisco Javier; Alemán-Gómez, Yasser; Garcia-Garcia, David; Escorial, Sergio; Quiroga, María Ángeles; Santarnecchi, Emiliano; Navas-Sánchez, Francisco Javier; Desco, Manuel; Arango, Celso; Colom, Roberto

    2017-07-15

    Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T1-weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and

  12. High-Throughput Near-Infrared Reflectance Spectroscopy for Predicting Quantitative and Qualitative Composition Phenotypes of Individual Maize Kernels

    USDA-ARS?s Scientific Manuscript database

    Near-infrared reflectance (NIR) spectroscopy can be used for fast and reliable prediction of organic compounds in complex biological samples. We used a recently developed NIR spectroscopy instrument to predict starch, protein, oil, and weight of individual maize (Zea mays) seeds. The starch, prote...

  13. An Individual-Tree Growth and Yield Prediction System for Even-Aged Natural Shortleaf Pine Forests

    Treesearch

    Thomas B. Lynch; Kenneth L. Hitch; Michael M. Huebschmann; Paul A. Murphy

    1999-01-01

    The development of a system of equations that model the growth and development of even-aged natural shortleaf (Pinus echinata Mill.) pine forests is described. The growth prediction system is a distance-independent individual-tree simulator containing equations that predict basal-area growth, survival, total and merchantable heights, and total and...

  14. [A gate spring which can torque an individual tooth with high efficiency].

    PubMed

    Li, Yu; Guan, Yu; Pan, Lanlan; Zhao, Zhihe

    2012-04-01

    It is to address torquing an individual tooth using a gate spring. The gate spring is made of a rectangular stainless steal wire, in the shape of a gate, which is incorporated to the archwire by spot welding. Torque is generated by the combined effects of the gate spring and the archwire. After 2-3 months, the gate spring can obviously torque individual tooth.

  15. Role of Microalbuminuria in Predicting Cardiovascular Mortality in Individuals With Subclinical Hypothyroidism.

    PubMed

    Tuliani, Tushar A; Shenoy, Maithili; Belgrave, Kevin; Deshmukh, Abhishek; Pant, Sadip; Hilliard, Anthony; Afonso, Luis

    2017-09-01

    Studies suggest that subclinical hypothyroidism (SCH) is related to cardiovascular mortality (CVM). We explored the role of microalbuminuria (MIA) as a predictor of long-term CVM in population with and without SCH with normal kidney function. We examined the National Health and Nutrition Education Survey - III database (n = 6,812). Individuals younger than 40 years, thyroid-stimulating hormone levels ≥20 and ≤0.35mIU/L, estimated glomerular filtration rate <60mL/minute/1.73m(2) and urine albumin-to-creatinine ratio of >250mg/g in men and >355mg/g in women were excluded. SCH was defined as thyroid-stimulating hormone levels between 5 and 19.99mIU/L and serum T4 levels between 5 and 12µg/dL. MIA was defined as urine albumin-to-creatinine ratio of 17-250mg/g in men and 25-355mg/g in women. Patients were categorized into the following 4 groups: (1) no SCH or MIA, (2) MIA, but no SCH, (3) SCH, but no MIA and (4) both SCH and MIA. Prevalence of MIA in the subclinical hypothyroid cohort was 21% compared to 16.4% in those without SCH (P = 0.03). SCH was a significant independent predictor of MIA (n = 6,812), after adjusting for traditional risk factors (unadjusted odds ratio = 1.75; 95% CI: 1.24-2.48; P = 0.002 and adjusted odds ratio = 1.83; 95% CI: 1.2-2.79; P = 0.006). MIA was a significant independent predictor of long-term all-cause (adjusted hazard ratio = 1.7, 95% CI: 1.24-2.33) and CVM (adjusted hazard ratio = 1.72, 95% CI: 1.07-2.76) in subclinical hypothyroid individuals. In a cohort of subclinical hypothyroid individuals, the presence of MIA predicts increased risk of CVM as compared to nonmicroalbuminurics with SCH. Further randomized trials are needed to assess the benefits of treating microalbuminuric subclinical hypothyroid individuals and impact on CVM. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

  16. Individual differences in degree of handedness and somesthetic asymmetry predict individual differences in left-right confusion.

    PubMed

    Vingerhoets, Guy; Sarrechia, Iemke

    2009-12-01

    Confusion or frustration connected with daily demands involving left-right discrimination is a common observation even in neurologically intact adults. We aimed to test the hypothesis that the degree of left-right confusion is associated with bodily asymmetry. Sixty-two female volunteers performed a left-right decision task that required fast responses to visually presented directional words (left, right, up, down) or pictograms (<--, -->, upward arrow, downward arrow). Participants also performed several tests that measured asymmetry of handedness, grip strength, and tactile sensitivity, and completed self-reports on left-right confusion and perceived bodily asymmetry. Results showed significant correlations between left-right confusion and the degree of handedness and asymmetry in tactile sensitivity. These results suggest that individuals who reveal a stronger internal bias between both sides of the body show less left-right confusion than people with less salient bodily asymmetry.

  17. Thermodynamic Route to Efficient Prediction of Gas Diffusivity in Nanoporous Materials.

    PubMed

    Tian, Yun; Xu, Xiaofei; Wu, Jianzhong

    2017-09-26

    We report an efficient computational procedure for rapid and accurate prediction of the self-diffusivity of gas molecules in nanoporous materials by implementing the transition state theory for intercage hopping at infinite dilution with the string method in conjunction with the excess-entropy scaling for predicting gas diffusion coefficients at finite loadings. The theoretical procedure has been calibrated with molecular dynamics simulations for the diffusion coefficients of methane and hydrogen gases in representative nanoporous materials including metal organic frameworks and zeolites. Combined with the classical density functional theory for calculating the excess entropy of gas molecules in micropores, the theoretical procedure enables efficient computation of both thermodynamic and transport properties important for design and screening of nanostructured materials for gas storage and separation.

  18. Prediction of removal efficiency of Lanaset Red G on walnut husk using artificial neural network model.

    PubMed

    Çelekli, Abuzer; Birecikligil, Sevil Sungur; Geyik, Faruk; Bozkurt, Hüseyin

    2012-01-01

    An artificial neural network (ANN) model was used to predict removal efficiency of Lanaset Red (LR) G on walnut husk (WH). This adsorbent was characterized by FTIR-ATR. Effects of particle size, adsorbent dose, initial pH value, dye concentration, and contact time were investigated to optimize sorption process. Operating variables were used as the inputs to the constructed neural network to predict the dye uptake at any time as an output. Commonly used pseudo second-order model was fitted to the experimental data to compare with ANN model. According to error analyses and determination of coefficients, ANN was the more appropriate model to describe this sorption process. Results of ANN indicated that pH was the most efficient parameter (43%), followed by initial dye concentration (40%) for sorption of LR G on WH.

  19. [Blood DNA Radiosensitivity May Be Predictive Marker for Efficacy of Radiation Therapy in Glioma Tumorbearing Individuals].

    PubMed

    Ivanov, S D; Korytova, L I; Yamshanov, V A; Zhabina, R M; Semenov, A L; Krasnikova, V G

    2015-01-01

    Animal and clinical studies were conducted to evaluate the association between the blood DNA radiosensitivity, assessed by determining the original S-index ex vivo, and the response of gliomas to irradiation in vivo. Possible modifications of the latter after administration of iron-containing water (ICW) in rats were also explored. The study was performed on the rats with subcutaneously implanted experimental glioma-35. The tumors were locally X-irradiated with a single 15 Gy dose as a radiation therapy (RT). ICW (60-63 mg · Fe 2+/l) was administered as a drinking water for 3 days before treatment. The animals underwent blood sampling for analysis of the DNA concentration and leukocyte count. The DNA index was estimated 24 h after RT. The S-index was evaluated within 4 h before RT. The mean initial S-index in the blood samples of glioma-bearing rats was 0.73 ± 0.05. Addition of ICW ex vivo resulted in a significantly increased S-index in a half of the samples. In general, the irradiated rats, which had been given pretreatment with ICW and demonstrated an ex vivo increase of the S-index to > 1.0, showed the most marked inhibition of tumor progression and the smallest tumor volume 25 days after irradiation. They also exhibited the lowest rate of growth and the longest survival. Determination of the biochemical S-index and evaluation of its changes ex vivo caused by ICW may be predictive of the response of experimental glioma to irradiation with radiomodification. The S-index may serve as a predictive indicator in clinic of the efficient evaluation of RT in patients with glioma.

  20. A Simple and Efficient Computational Approach to Chafed Cable Time-Domain Reflectometry Signature Prediction

    NASA Technical Reports Server (NTRS)

    Kowalski, Marc Edward

    2009-01-01

    A method for the prediction of time-domain signatures of chafed coaxial cables is presented. The method is quasi-static in nature, and is thus efficient enough to be included in inference and inversion routines. Unlike previous models proposed, no restriction on the geometry or size of the chafe is required in the present approach. The model is validated and its speed is illustrated via comparison to simulations from a commercial, three-dimensional electromagnetic simulator.

  1. Predicting body composition using foot-to-foot bioelectrical impedance analysis in healthy Asian individuals.

    PubMed

    Wu, Chun-Shien; Chen, Yu-Yawn; Chuang, Chih-Lin; Chiang, Li-Ming; Dwyer, Gregory B; Hsu, Ying-Lin; Huang, Ai-Chun; Lai, Chung-Liang; Hsieh, Kuen-Chang

    2015-05-19

    The objectives of this study were to develop a regression model for predicting fat-free mass (FFM) in a population of healthy Taiwanese individuals using standing foot-to-foot bioelectrical impedance analysis (BIA) and to test the model's performance in predicting FFM with different body fat percentages (BF%). We used dual-energy X-ray absorptiometry (DXA) to measure the FFM of 554 healthy Asian subjects (age, 16-75 y; body mass index, 15.8-43.1 kg/m(2)). We also evaluated the validity of the developed multivariate model using a double cross-validation technique and assessed the accuracy of the model in an all-subjects sample and subgroup samples with different body fat levels. Predictors in the all-subjects multivariate model included height(2)/impedance, weight, year, and sex (FFM = 13.055 + 0.204 weight + 0.394 height(2)/Impedance - 0.136 age + 8.125 sex (sex: Female = 0, Male = 1), r(2) = 0.92, standard error of the estimate = 3.17 kg). The correlation coefficients between predictive FFM by BIA (FFMBIA) and DXA-measured FFM (FFMDXA) in female subjects with a total-subjects BF%DXA of <20 %, 20 %-30 %, 30 %-40 % and >40 % were r = 0.87, 0.90, 0.91, 0.89, and 0.94, respectively, with bias ± 2SD of 0.0 ± 3.0 kg, -2.6 ± 1.7 kg, -1.5 ± 2.8 kg, 0.5 ± 2.7 kg, and 2.0 ± 2.9 kg, respectively. The correlation coefficients between FFMBIA and FFMDXA in male subjects with a total-subjects BF%DXA of <10 %, 10 %-20 %, 20 %-30 %, and >30 % were r = 0.89, 0.89, 0.90, 0.93, and 0.91, respectively, with bias ± 2SD of 0.0 ± 3.2 kg, -2.3 ± 2.5 kg, -0.5 ± 3.2 kg, 0.4 ± 3.1 kg, and 2.1 ± 3.2 kg, respectively. The standing foot-to-foot BIA method developed in this study can accurately predict FFM in healthy Asian individuals with different levels of body fat.

  2. The Carbon_h-factor: predicting individuals' research impact at early stages of their career.

    PubMed

    Carbon, Claus-Christian

    2011-01-01

    Assessing an individual's research impact on the basis of a transparent algorithm is an important task for evaluation and comparison purposes. Besides simple but also inaccurate indices such as counting the mere number of publications or the accumulation of overall citations, and highly complex but also overwhelming full-range publication lists in their raw format, Hirsch (2005) introduced a single figure cleverly combining different approaches. The so-called h-index has undoubtedly become the standard in scientometrics of individuals' research impact (note: in the present paper I will always use the term "research impact" to describe the research performance as the logic of the paper is based on the h-index, which quantifies the specific "impact" of, e.g., researchers, but also because the genuine meaning of impact refers to quality as well). As the h-index reflects the number h of papers a researcher has published with at least h citations, the index is inherently positively biased towards senior level researchers. This might sometimes be problematic when predictive tools are needed for assessing young scientists' potential, especially when recruiting early career positions or equipping young scientists' labs. To be compatible with the standard h-index, the proposed index integrates the scientist's research age (Carbon_h-factor) into the h-index, thus reporting the average gain of h-index per year. Comprehensive calculations of the Carbon_h-factor were made for a broad variety of four research-disciplines (economics, neuroscience, physics and psychology) and for researchers performing on three high levels of research impact (substantial, outstanding and epochal) with ten researchers per category. For all research areas and output levels we obtained linear developments of the h-index demonstrating the validity of predicting one's later impact in terms of research impact already at an early stage of their career with the Carbon_h-factor being approx. 0.4, 0.8, and

  3. Efficiency prediction for a low head bulb turbine with SAS SST and zonal LES turbulence models

    NASA Astrophysics Data System (ADS)

    Jošt, D.; Škerlavaj, A.

    2014-03-01

    A comparison between results of numerical simulations and measurements for a 3-blade bulb turbine is presented in order to determine an appropriate numerical setup for accurate and reliable simulations of flow in low head turbines. Numerical analysis was done for three angles of runner blades at two values of head. For the smallest blade angle the efficiency was quite accurately predicted, but for the optimal and maximal blade angles steady state analysis entirely failed to predict the efficiency due to underestimated torque on the shaft and incorrect results in the draft tube. Transient simulation with SST did not give satisfactory results, but with SAS and zonal LES models the prediction of efficiency was significantly improved. From the results obtained by SAS and zonal LES the interdependence between turbulence models, vortex structures in the flow, values of eddy viscosity and flow energy losses in the draft tube can be seen. Also the effect of using the bounded central differential scheme instead of the high resolution scheme was evident. To test the effect of grid density, simulations were performed on four grids. While a difference between results obtained on the basic grid and on the fine grid was small, the results obtained on the coarse grids were not satisfactory.

  4. Earthquake Predictability: Results From Aggregating Seismicity Data And Assessment Of Theoretical Individual Cases Via Synthetic Data

    NASA Astrophysics Data System (ADS)

    Adamaki, A.; Roberts, R.

    2016-12-01

    For many years an important aim in seismological studies has been forecasting the occurrence of large earthquakes. Despite some well-established statistical behavior of earthquake sequences, expressed by e.g. the Omori law for aftershock sequences and the Gutenburg-Richter distribution of event magnitudes, purely statistical approaches to short-term earthquake prediction have in general not been successful. It seems that better understanding of the processes leading to critical stress build-up prior to larger events is necessary to identify useful precursory activity, if this exists, and statistical analyses are an important tool in this context. There has been considerable debate on the usefulness or otherwise of foreshock studies for short-term earthquake prediction. We investigate generic patterns of foreshock activity using aggregated data and by studying not only strong but also moderate magnitude events. Aggregating empirical local seismicity time series prior to larger events observed in and around Greece reveals a statistically significant increasing rate of seismicity over 20 days prior to M>3.5 earthquakes. This increase cannot be explained by tempo-spatial clustering models such as ETAS, implying genuine changes in the mechanical situation just prior to larger events and thus the possible existence of useful precursory information. Because of tempo-spatial clustering, including aftershocks to foreshocks, even if such generic behavior exists it does not necessarily follow that foreshocks have the potential to provide useful precursory information for individual larger events. Using synthetic catalogs produced based on different clustering models and different presumed system sensitivities we are now investigating to what extent the apparently established generic foreshock rate acceleration may or may not imply that the foreshocks have potential in the context of routine forecasting of larger events. Preliminary results suggest that this is the case, but

  5. Emotional traits predict individual differences in amphetamine-induced positive mood in healthy volunteers

    PubMed Central

    Kirkpatrick, Matthew G.; Goldenson, Nicholas I.; Kapadia, Nahel; Kahler, Christopher W.; de Wit, Harriet; Swift, Robert M.; McGeary, John E.; Sussman, Steve; Leventhal, Adam M.

    2015-01-01

    BACKGROUND Previous research on emotional correlates of individual differences in subjective responses to d-amphetamine has focused on relatively broad personality traits. Yet, emotional functioning is best characterized by several narrow subcomponents, each of which may contribute uniquely to amphetamine response. Here, we examine several specific subdomains of emotional functioning in relation to acute amphetamine response. METHOD At a baseline session, healthy stimulant-naïve volunteers (N=97) completed measures of several subdomains of baseline trait emotional functioning, and then completed two counterbalanced experimental sessions during which they received a single dose of 20-mg oral d-amphetamine or placebo. Acute subjective drug response measures were completed at repeated intervals before and after drug administration. Data from subjective measures that were significantly modulated by amphetamine were reduced using principal components analysis (amphetamine – placebo) into three higher-order factors of “Positive Mood,” “Arousal,” and “Drug High.” Amphetamine did not significantly alter any “negative” subjective states. Separate multiple regression analyses were conducted regressing these three drug factors on baseline trait emotional functioning scales. RESULTS The combined set of trait emotional functioning indicators accounted for approximately 22% of the variance in acute amphetamine-induced positive mood changes. Greater anticipatory pleasure and greater anxious distress each uniquely predicted greater amphetamine-induced Positive Mood. Trait emotional functioning did not significantly predict amphetamine-induced changes in Arousal or Drug High. DISCUSSION Emotional traits appear to moderate drug-induced positive mood but not other dimensions of amphetamine effects. Different facets of emotional functioning may differentially modulate amphetamine's subjective effect profile. PMID:26429791

  6. Neural activity tied to reading predicts individual differences in extended-text comprehension

    PubMed Central

    Mossbridge, Julia A.; Grabowecky, Marcia; Paller, Ken A.; Suzuki, Satoru

    2013-01-01

    Reading comprehension depends on neural processes supporting the access, understanding, and storage of words over time. Examinations of the neural activity correlated with reading have contributed to our understanding of reading comprehension, especially for the comprehension of sentences and short passages. However, the neural activity associated with comprehending an extended text is not well-understood. Here we describe a current-source-density (CSD) index that predicts individual differences in the comprehension of an extended text. The index is the difference in CSD-transformed event-related potentials (ERPs) to a target word between two conditions: a comprehension condition with words from a story presented in their original order, and a scrambled condition with the same words presented in a randomized order. In both conditions participants responded to the target word, and in the comprehension condition they also tried to follow the story in preparation for a comprehension test. We reasoned that the spatiotemporal pattern of difference-CSDs would reflect comprehension-related processes beyond word-level processing. We used a pattern-classification method to identify the component of the difference-CSDs that accurately (88%) discriminated good from poor comprehenders. The critical CSD index was focused at a frontal-midline scalp site, occurred 400–500 ms after target-word onset, and was strongly correlated with comprehension performance. Behavioral data indicated that group differences in effort or motor preparation could not explain these results. Further, our CSD index appears to be distinct from the well-known P300 and N400 components, and CSD transformation seems to be crucial for distinguishing good from poor comprehenders using our experimental paradigm. Once our CSD index is fully characterized, this neural signature of individual differences in extended-text comprehension may aid the diagnosis and remediation of reading comprehension deficits. PMID

  7. Individual variation in avian reproductive physiology does not reliably predict variation in laying date.

    PubMed

    Schaper, Sonja V; Dawson, Alistair; Sharp, Peter J; Caro, Samuel P; Visser, Marcel E

    2012-10-01

    Most animals reproduce seasonally. They time their reproduction in response to environmental cues, like increasing photoperiod and temperature, which are predictive for the time of high food availability. Although individuals of a population use the same cues, they vary in their onset of reproduction, with some animals reproducing consistently early or late. In avian research, timing of reproduction often refers to the laying date of the first egg, which is a key determinant of fitness. Experiments measuring temporal patterns of reproductive hormone concentrations or gonadal size under controlled conditions in response to a cue commonly assume that these proxies are indicative of the timing of egg laying. This assumption often remains untested, with few studies reporting both reproductive development and the onset of laying. We kept in total 144 pairs of great tits (Parus major) in separate climate-controlled aviaries over 4 years to correlate pre-breeding plasma luteinizing hormone (LH), prolactin (PRL) and gonadal growth with the timing of laying. Individuals varied consistently in hormone concentrations over spring, but this was not directly related to the timing of gonadal growth, nor with the laying date of the first egg. The timing of gonadal development in both sexes was similarly not correlated with the timing of laying. This demonstrates the female's ability to adjust the onset of laying to environmental conditions irrespective of substantial differences in pre-laying development. We conclude that stages of reproductive development are regulated by different cues, and therefore egg laying dates need to be studied to measure the influences of environmental cues on timing of seasonal reproduction.

  8. Plasma lipidomic profiling of treated HIV-positive individuals and the implications for cardiovascular risk prediction.

    PubMed

    Wong, Gerard; Trevillyan, Janine M; Fatou, Benoit; Cinel, Michelle; Weir, Jacquelyn M; Hoy, Jennifer F; Meikle, Peter J

    2014-01-01

    The increased risk of coronary artery disease in human immunodeficiency virus (HIV) positive patients is collectively contributed to by the human immunodeficiency virus and antiretroviral-associated dyslipidaemia. In this study, we investigate the characterisation of the plasma lipid profiles of treated HIV patients and the relationship of 316 plasma lipid species across multiple lipid classes with the risk of future cardiovascular events in HIV-positive patients. In a retrospective case-control study, we analysed plasma lipid profiles of 113 subjects. Cases (n = 23) were HIV-positive individuals with a stored blood sample available 12 months prior to their diagnosis of coronary artery disease (CAD). They were age and sex matched to HIV-positive individuals without a diagnosis of CAD (n = 45) and with healthy HIV-negative volunteers (n = 45). Association of plasma lipid species and classes with HIV infection and cardiovascular risk in HIV were determined. In multiple logistic regression, we identified 83 lipids species and 7 lipid classes significantly associated with HIV infection and a further identified 74 lipid species and 8 lipid classes significantly associated with future cardiovascular events in HIV-positive subjects. Risk prediction models incorporating lipid species attained an area under the receiver operator characteristic curve (AUC) of 0.78 (0.775, 0.785)) and outperformed all other tested markers and risk scores in the identification of HIV-positive subjects with increased risk of cardiovascular events. Our results demonstrate that HIV-positive patients have significant differences in their plasma lipid profiles compared with healthy HIV-negative controls and that numerous lipid species were significantly associated with elevated cardiovascular risk. This suggests a potential novel application for plasma lipids in cardiovascular risk screening of HIV-positive patients.

  9. The role of effort in moderating the anxiety-performance relationship: Testing the prediction of processing efficiency theory in simulated rally driving.

    PubMed

    Wilson, Mark; Smith, Nickolas C; Chattington, Mark; Ford, Mike; Marple-Horvat, Dilwyn E

    2006-11-01

    We tested some of the key predictions of processing efficiency theory using a simulated rally driving task. Two groups of participants were classified as either dispositionally high or low anxious based on trait anxiety scores and trained on a simulated driving task. Participants then raced individually on two similar courses under counterbalanced experimental conditions designed to manipulate the level of anxiety experienced. The effort exerted on the driving tasks was assessed though self-report (RSME), psychophysiological measures (pupil dilation) and visual gaze data. Efficiency was measured in terms of efficiency of visual processing (search rate) and driving control (variability of wheel and accelerator pedal) indices. Driving performance was measured as the time taken to complete the course. As predicted, increased anxiety had a negative effect on processing efficiency as indexed by the self-report, pupillary response and variability of gaze data. Predicted differences due to dispositional levels of anxiety were also found in the driving control and effort data. Although both groups of drivers performed worse under the threatening condition, the performance of the high trait anxious individuals was affected to a greater extent by the anxiety manipulation than the performance of the low trait anxious drivers. The findings suggest that processing efficiency theory holds promise as a theoretical framework for examining the relationship between anxiety and performance in sport.

  10. Individual variability in finger-to-finger transmission efficiency of Enterococcus faecium clones

    PubMed Central

    del Campo, Rosa; Sánchez-Díaz, Ana María; Zamora, Javier; Torres, Carmen; Cintas, Luis María; Franco, Elvira; Cantón, Rafael; Baquero, Fernando

    2014-01-01

    A fingertip-to-fingertip intraindividual transmission experiment was carried out in 30 healthy volunteers, using four MLST-typed Enterococcus faecium clones. Overall results showed an adequate fit goodness to a theoretical exponential model, whereas four volunteers (13%) exhibited a significantly higher finger-to-finger bacterial transmission efficiency. This observation might have deep consequences in nosocomial epidemiology. PMID:24382843

  11. Communication Efficiency in Children: A Function of Individual Skill or Dyadic Interaction?

    ERIC Educational Resources Information Center

    Stipek, Deborah; Nelson, Katherine

    Two experiments investigating the efficiency of communication between 5th grade children from differing socioeconomic (SES) backgrounds are described. In each experiment, 40 same-sex pairs, half male and half female, were formed into dyadic groupings by combining lower- and middle-SES children into the four possible speaker-listener combinations.…

  12. Communication Efficiency in Children: A Function of Individual Skill or Dyadic Interaction?

    ERIC Educational Resources Information Center

    Stipek, Deborah; Nelson, Katherine

    Two experiments investigating the efficiency of communication between 5th grade children from differing socioeconomic (SES) backgrounds are described. In each experiment, 40 same-sex pairs, half male and half female, were formed into dyadic groupings by combining lower- and middle-SES children into the four possible speaker-listener combinations.…

  13. Accuracies of genomic prediction of feed efficiency traits using different prediction and validation methods in an experimental Nelore cattle population.

    PubMed

    Silva, R M O; Fragomeni, B O; Lourenco, D A L; Magalhães, A F B; Irano, N; Carvalheiro, R; Canesin, R C; Mercadante, M E Z; Boligon, A A; Baldi, F S; Misztal, I; Albuquerque, L G

    2016-09-01

    Animal feeding is the most important economic component of beef production systems. Selection for feed efficiency has not been effective mainly due to difficult and high costs to obtain the phenotypes. The application of genomic selection using SNP can decrease the cost of animal evaluation as well as the generation interval. The objective of this study was to compare methods for genomic evaluation of feed efficiency traits using different cross-validation layouts in an experimental beef cattle population genotyped for a high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA). After quality control, a total of 437,197 SNP genotypes were available for 761 Nelore animals from the Institute of Animal Science, Sertãozinho, São Paulo, Brazil. The studied traits were residual feed intake, feed conversion ratio, ADG, and DMI. Methods of analysis were traditional BLUP, single-step genomic BLUP (ssGBLUP), genomic BLUP (GBLUP), and a Bayesian regression method (BayesCπ). Direct genomic values (DGV) from the last 2 methods were compared directly or in an index that combines DGV with parent average. Three cross-validation approaches were used to validate the models: 1) YOUNG, in which the partition into training and testing sets was based on year of birth and testing animals were born after 2010; 2) UNREL, in which the data set was split into 3 less related subsets and the validation was done in each subset a time; and 3) RANDOM, in which the data set was randomly divided into 4 subsets (considering the contemporary groups) and the validation was done in each subset at a time. On average, the RANDOM design provided the most accurate predictions. Average accuracies ranged from 0.10 to 0.58 using BLUP, from 0.09 to 0.48 using GBLUP, from 0.06 to 0.49 using BayesCπ, and from 0.22 to 0.49 using ssGBLUP. The most accurate and consistent predictions were obtained using ssGBLUP for all analyzed traits. The ssGBLUP seems to be more suitable to obtain

  14. Oxygen uptake efficiency slope and peak oxygen consumption predict prognosis in children with tetralogy of Fallot.

    PubMed

    Tsai, Yun-Jeng; Li, Min-Hui; Tsai, Wan-Jung; Tuan, Sheng-Hui; Liao, Tin-Yun; Lin, Ko-Long

    2016-07-01

    Oxygen uptake efficiency slope (OUES) and peak oxygen consumption (VO2peak) are exercise parameters that can predict cardiac morbidity in patients with numerous heart diseases. But the predictive value in patients with tetralogy of Fallot is still undetermined, especially in children. We evaluated the prognostic value of OUES and VO2peak in children with total repair of tetralogy of Fallot. Retrospective cohort study. Forty tetralogy of Fallot patients younger than 12 years old were recruited. They underwent a cardiopulmonary exercise test during the follow-up period after total repair surgery. The results of the cardiopulmonary exercise test were used to predict the cardiac related hospitalization in the following two years after the test. OUES normalized by body surface area (OUES/BSA) and the percentage of predicted VO2peak appeared to be predictive for two-year cardiac related hospitalization. Receiver operating characteristic curve analysis demonstrated that the best threshold value for OUES/BSA was 1.029 (area under the curve = 0.70, p = 0.03), and for VO2peak was 74% of age prediction (area under the curve = 0.72, p = 0.02). The aforementioned findings were confirmed by Kaplan-Meier plots and log-rank test. OUES/BSA and VO2peak are useful predictors of cardiac-related hospitalization in children with total repair of tetralogy of Fallot. © The European Society of Cardiology 2015.

  15. An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Saxena, Abhinav; Goebel, Kai

    2012-01-01

    Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithm must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty, and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transformation. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.

  16. An approximate solution to improve computational efficiency of impedance-type payload load prediction

    NASA Technical Reports Server (NTRS)

    White, C. W.

    1981-01-01

    The computational efficiency of the impedance type loads prediction method was studied. Three goals were addressed: devise a method to make the impedance method operate more efficiently in the computer; assess the accuracy and convenience of the method for determining the effect of design changes; and investigate the use of the method to identify design changes for reduction of payload loads. The method is suitable for calculation of dynamic response in either the frequency or time domain. It is concluded that: the choice of an orthogonal coordinate system will allow the impedance method to operate more efficiently in the computer; the approximate mode impedance technique is adequate for determining the effect of design changes, and is applicable for both statically determinate and statically indeterminate payload attachments; and beneficial design changes to reduce payload loads can be identified by the combined application of impedance techniques and energy distribution review techniques.

  17. Efficient Prediction Structures for H.264 Multi View Coding Using Temporal Scalability

    NASA Astrophysics Data System (ADS)

    Guruvareddiar, Palanivel; Joseph, Biju K.

    2014-03-01

    Prediction structures with "disposable view components based" hierarchical coding have been proven to be efficient for H.264 multi view coding. Though these prediction structures along with the QP cascading schemes provide superior compression efficiency when compared to the traditional IBBP coding scheme, the temporal scalability requirements of the bit stream could not be met to the fullest. On the other hand, a fully scalable bit stream, obtained by "temporal identifier based" hierarchical coding, provides a number of advantages including bit rate adaptations and improved error resilience, but lacks in compression efficiency when compared to the former scheme. In this paper it is proposed to combine the two approaches such that a fully scalable bit stream could be realized with minimal reduction in compression efficiency when compared to state-of-the-art "disposable view components based" hierarchical coding. Simulation results shows that the proposed method enables full temporal scalability with maximum BDPSNR reduction of only 0.34 dB. A novel method also has been proposed for the identification of temporal identifier for the legacy H.264/AVC base layer packets. Simulation results also show that this enables the scenario where the enhancement views could be extracted at a lower frame rate (1/2nd or 1/4th of base view) with average extraction time for a view component of only 0.38 ms.

  18. Modeling recombination processes and predicting energy conversion efficiency of dye sensitized solar cells from first principles

    NASA Astrophysics Data System (ADS)

    Ma, Wei; Meng, Sheng

    2014-03-01

    We present a set of algorithms based on solo first principles calculations, to accurately calculate key properties of a DSC device including sunlight harvest, electron injection, electron-hole recombination, and open circuit voltages. Two series of D- π-A dyes are adopted as sample dyes. The short circuit current can be predicted by calculating the dyes' photo absorption, and the electron injection and recombination lifetime using real-time time-dependent density functional theory (TDDFT) simulations. Open circuit voltage can be reproduced by calculating energy difference between the quasi-Fermi level of electrons in the semiconductor and the electrolyte redox potential, considering the influence of electron recombination. Based on timescales obtained from real time TDDFT dynamics for excited states, the estimated power conversion efficiency of DSC fits nicely with the experiment, with deviation below 1-2%. Light harvesting efficiency, incident photon-to-electron conversion efficiency and the current-voltage characteristics can also be well reproduced. The predicted efficiency can serve as either an ideal limit for optimizing photovoltaic performance of a given dye, or a virtual device that closely mimicking the performance of a real device under different experimental settings.

  19. Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction.

    PubMed

    Cheng, Hao; Garrick, Dorian J; Fernando, Rohan L

    2017-01-01

    A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify the predictive ability of a statistical model. Naive application of Leave-one-out cross validation is computationally intensive because the training and validation analyses need to be repeated n times, once for each observation. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis. Efficient Leave-one-out cross validation strategies is 786 times faster than the naive application for a simulated dataset with 1,000 observations and 10,000 markers and 99 times faster with 1,000 observations and 100 markers. These efficiencies relative to the naive approach using the same model will increase with increases in the number of observations. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis.

  20. POSE: Prediction-Based Opportunistic Sensing for Energy Efficiency in Sensor Networks Using Distributed Supervisors.

    PubMed

    Hare, James Z; Gupta, Shalabh; Wettergren, Thomas A

    2017-08-11

    This paper presents a distributed supervisory control algorithm that enables opportunistic sensing for energy-efficient target tracking in a sensor network. The algorithm called Prediction-based Opportunistic Sensing (POSE), is a distributed node-level energy management approach for minimizing energy usage. Distributed sensor nodes in the POSE network self-adapt to target trajectories by enabling high power consuming devices when they predict that a target is arriving in their coverage area, while enabling low power consuming devices when the target is absent. Each node has a Probabilistic Finite State Automaton which acts as a supervisor to dynamically control its various sensing and communication devices based on target's predicted position. The POSE algorithm is validated by extensive Monte Carlo simulations and compared with random scheduling schemes. The results show that the POSE algorithm provides significant energy savings while also improving track estimation via fusion-driven state initialization.

  1. Individual changes in clozapine levels after smoking cessation: results and a predictive model.

    PubMed

    Meyer, J M

    2001-12-01

    Published reports document 20-40% lower mean serum clozapine concentrations in smokers compared with nonsmokers due to enzyme induction. Despite the increase in nonsmoking psychiatric facilities in the United States, previous studies have not tracked individual changes in serum clozapine levels after smoking cessation. Clozapine level changes were analyzed in 11 patients at Oregon State Hospital who were on stable clozapine doses, before and after implementation of a hospital-wide nonsmoking policy. A mean increase in clozapine levels of 71.9% (442.4 ng/ml +/- 598.8 ng/ml) occurred upon smoking cessation (p < .034) from a baseline level of 550.2 ng/ml (+/- 160.18 ng/ml). One serious adverse event, aspiration pneumonia, was associated with a nonsmoking serum clozapine level of 3066 ng/ml. Elimination of statistically extreme results generated a mean increase of 57.4 % or 284.1 ng/ml (+/- 105.2 ng/ml) for the remaining cases (p < .001) and permitted construction of a linear model which explains 80.9% of changes in clozapine levels upon smoking cessation (F = 34.9;p = .001): clozapine level as nonsmoker = 45.3 + 1.474 (clozapine level as smoker). These findings suggest that significant increases in clozapine levels upon smoking cessation may be predicted by use of a model. Those with high baseline levels should be monitored for serious adverse events.

  2. Individual differences in acute alcohol impairment of inhibitory control predict ad libitum alcohol consumption

    PubMed Central

    Weafer, Jessica

    2015-01-01

    Rationale Research has begun to examine how acute cognitive impairment from alcohol could contribute to alcohol abuse. Specifically, alcohol-induced impairment of inhibitory control could compromise the drinker’s ability to stop the self-administration of alcohol, increasing the risk of binge drinking. Objective The present study was designed to test this hypothesis by examining the relation between acute alcohol impairment of inhibitory control and alcohol consumption during a single drinking episode. Materials and methods Twenty-six healthy adults performed a cued go/no-go task that measured inhibitory control. The study tested the degree to which their inhibitory control was impaired by a moderate dose of alcohol (0.65 g/kg) versus a placebo and the extent to which individual differences in this impairment predicted levels of alcohol consumption as assessed by ad lib drinking in the laboratory. Results In accord with the hypothesis, greater impairment of inhibitory control from alcohol was associated with increased ad lib consumption. Conclusion Acute impairment of inhibitory control might be an important cognitive effect that contributes to abuse in addition to the positive rewarding effects of the drug. PMID:18758758

  3. Can personality predict individual differences in brook trout spatial learning ability?

    PubMed

    White, S L; Wagner, T; Gowan, C; Braithwaite, V A

    2017-08-01

    While differences in individual personality are common in animal populations, understanding the ecological significance of variation has not yet been resolved. Evidence suggests that personality may influence learning and memory; a finding that could improve our understanding of the evolutionary processes that produce and maintain intraspecific behavioural heterogeneity. Here, we tested whether boldness, the most studied personality trait in fish, could predict learning ability in brook trout. After quantifying boldness, fish were trained to find a hidden food patch in a maze environment. Stable landmark cues were provided to indicate the location of food and, at the conclusion of training, cues were rearranged to test for learning. There was a negative relationship between boldness and learning as shy fish were increasingly more successful at navigating the maze and locating food during training trials compared to bold fish. In the altered testing environment, only shy fish continued using cues to search for food. Overall, the learning rate of bold fish was found to be lower than that of shy fish for several metrics suggesting that personality could have widespread effects on behaviour. Because learning can increase plasticity to environmental change, these results have significant implications for fish conservation. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Predicting co-morbidities in chemically sensitive individuals from exhaled breath analysis.

    PubMed

    Zeliger, Harold I; Pan, Yaqin; Rea, William J

    2012-09-01

    The exhaled breath of more than four hundred patients who presented at the Environmental Health Center - Dallas with chemical sensitivity conditions were analyzed for the relative abundance of their breath chemical composition by gas chromatography and mass spectrometry for volatile and semi-volatile organic compounds. All presenting patients had no fewer than four and as many as eight co-morbid conditions. Surprisingly, almost all the exhaled breath analyses showed the presence of a preponderance of lipophilic aliphatic and aromatic hydrocarbons. The hydrophilic compounds present were almost entirely of natural origin, i.e. expected metabolites of foods. The lipophile, primarily C3 to C16 hydrocarbons and believed to have come from inhalation of polluted air, were, in all cases, present at concentrations far below those known to be toxic to humans, but caused sensitivity and signs of chemical overload. The co-morbid health effects observed are believed to be caused by the sequential absorption of lipophilic and hydrophilic chemicals; an initial absorption and retention of lipophile followed by a subsequent absorption of hydrophilic species facilitated by the retained lipophile to produce chemical mixtures that are toxic at very low levels. It is hypothesized that co-morbid conditions in chemically sensitive individuals can be predicted from analysis of their exhaled breath.

  5. Individual differences in attributional style but not in interoceptive sensitivity, predict subjective estimates of action intention.

    PubMed

    Penton, Tegan; Thierry, Guillaume L; Davis, Nick J

    2014-01-01

    The debate on the existence of free will is on-going. Seminal findings by Libet et al. (1983) demonstrate that subjective awareness of a voluntary urge to act (the W-judgment) occurs before action execution. Libet's paradigm requires participants to perform voluntary actions while watching a clock hand rotate. On response trials, participants make a retrospective judgment related to awareness of their urge to act. This research investigates the relationship between individual differences in performance on the Libet task and self-awareness. We examined the relationship between W-judgment, attributional style (AS; a measure of perceived control) and interoceptive sensitivity (IS; awareness of stimuli originating from one's body; e.g., heartbeats). Thirty participants completed the AS questionnaire (ASQ), a heartbeat estimation task (IS), and the Libet paradigm. The ASQ score significantly predicted performance on the Libet task, while IS did not - more negative ASQ scores indicated larger latency between W-judgment and action execution. A significant correlation was also observed between ASQ score and IS. This is the first research to report a relationship between W-judgment and AS and should inform the future use of electroencephalography (EEG) to investigate the relationship between AS, W-judgment and RP onset. Our findings raise questions surrounding the importance of one's perceived control in determining the point of conscious intention to act. Furthermore, we demonstrate possible negative implications associated with a longer period between conscious awareness and action execution.

  6. Dorsolateral prefrontal γ-aminobutyric acid in men predicts individual differences in rash impulsivity.

    PubMed

    Boy, Frederic; Evans, C John; Edden, Richard A E; Lawrence, Andrew D; Singh, Krish D; Husain, Masud; Sumner, Petroc

    2011-11-01

    Impulsivity is a multifaceted personality construct associated with numerous psychiatric disorders. Recent research has characterized four facets of impulsivity: "urgency" (the tendency to act rashly especially in the context of distress or cravings); "lack of premeditation" (not envisaging the consequences of actions); "lack of perseverance" (not staying focused on a task); and "sensation seeking" (engaging in exciting activities). Urgency is particularly associated with clinical populations and problematic disinhibited behavior. We used magnetic resonance spectroscopy to measure concentration of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the dorsolateral prefrontal cortex (DLPFC) in two cohorts of 12 and 13 participants. We find that variation in trait urgency in healthy men correlates with GABA concentration in the DLPFC. The result was replicated in an independent cohort. More GABA predicted lower urgency scores, consistent with a role in self-control for GABA-mediated inhibitory mechanisms in DLPFC. These findings help account for individual differences in self-control and thus clarify the relationship between GABA and a wide range of psychiatric disorders associated with impaired self-control. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    NASA Technical Reports Server (NTRS)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  8. Within-person Changes in Individual Symptoms of Depression Predict Subsequent Depressive Episodes in Adolescents: A Prospective Study

    PubMed Central

    Kouros, Chrystyna D.; Morris, Matthew C.; Garber, Judy

    2015-01-01

    The current longitudinal study examined which individual symptoms of depression uniquely predicted a subsequent Major Depressive Episode (MDE) in adolescents, and whether these relations differed by sex. Adolescents (N=240) were first interviewed in grade 6 (M=11.86 years old; SD = 0.56; 54% female; 81.5% Caucasian) and then annually through grade 12 regarding their individual symptoms of depression as well as the occurrence of MDEs. Individual symptoms of depression were assessed with the Children’s Depression Rating Scale-Revised (CDRS-R) and depressive episodes were assessed with the Longitudinal Interval Follow-up Evaluation (LIFE). Results showed that within-person changes in sleep problems and low self-esteem/excessive guilt positively predicted an increased likelihood of an MDE for both boys and girls. Significant sex differences also were found. Within-person changes in anhedonia predicted an increased likelihood of a subsequent MDE among boys, whereas irritability predicted a decreased likelihood of a future MDE among boys, and concentration difficulties predicted a decreased likelihood of an MDE in girls. These results identified individual depressive symptoms that predicted subsequent depressive episodes in male and female adolescents, and may be used to guide the early detection, treatment, and prevention of depressive disorders in youth. PMID:26105209

  9. Can a mathematical model predict an individual's trait-like response to both total and partial sleep loss?

    PubMed

    Ramakrishnan, Sridhar; Lu, Wei; Laxminarayan, Srinivas; Wesensten, Nancy J; Rupp, Tracy L; Balkin, Thomas J; Reifman, Jaques

    2015-06-01

    Humans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance (UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation (TSD) and (ii) chronic sleep restriction (CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over non-individualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions. © 2014 European Sleep Research Society.

  10. Disorder prediction-based construct optimization improves activity and catalytic efficiency of Bacillus naganoensis pullulanase

    PubMed Central

    Wang, Xinye; Nie, Yao; Mu, Xiaoqing; Xu, Yan; Xiao, Rong

    2016-01-01

    Pullulanase is a well-known starch-debranching enzyme. However, the production level of pullulanase is yet low in both wide-type strains and heterologous expression systems. We predicted the disorder propensities of Bacillus naganoensis pullulanase (PUL) using the bioinformatics tool, Disorder Prediction Meta-Server. On the basis of disorder prediction, eight constructs, including PULΔN5, PULΔN22, PULΔN45, PULΔN64, PULΔN78 and PULΔN106 by deleting the first 5, 22, 45, 64, 78 and 106 residues from the N-terminus, and PULΔC9 and PULΔC36 by deleting the last 9 and 36 residues from the C-terminus, were cloned into the recombinant expression vector pET-28a-PelB and auto-induced in Escherichia coli BL21 (DE3) cells. All constructs were evaluated in production level, specific activities and kinetic parameters. Both PULΔN5 and PULΔN106 gave higher production levels of protein than the wide type and displayed increased specific activities. Kinetic studies showed that substrate affinities of the mutants were improved in various degrees and the catalytic efficiency of PULΔN5, PULΔN45, PULΔN78, PULΔN106 and PULΔC9 were enhanced. However, the truncated mutations did not change the advantageous properties of the enzyme involving optimum temperature and pH for further application. Therefore, Disorder prediction-based truncation would be helpful to efficiently improve the enzyme activity and catalytic efficiency. PMID:27091115

  11. A Multifactorial Approach to Predicting Death Anxiety: Assessing the Role of Religiosity, Susceptibility to Mortality Cues, and Individual Differences.

    PubMed

    French, Carrie; Greenauer, Nathan; Mello, Catherine

    2017-06-14

    Death anxiety is not only experienced by individuals receiving end-of-life care, but also by family members, social workers, and other service providers who support these individuals. Thus, identifying predictors of individual differences in experienced death anxiety levels may have both theoretical and clinical ramifications. The present study assessed the relative influence of religiosity, susceptibility to mortality cues, state and trait anxiety, and demographic factors in the experience of death anxiety through an online survey distributed to members of two online communities related to end-of-life care. Results indicated that cognitive and emotional susceptibility to mortality cues, as well as gender, predicted differences in death anxiety. Conversely, religiosity and age did not increase the predictive power of the model. Thus, death anxiety may be a function of emotional, cognitive, and sociocultural factors that interact in complex, but predictable, ways to modulate the response to mortality cues that occur in one's life.

  12. How Plantar Exteroceptive Efficiency Modulates Postural and Oculomotor Control: Inter-Individual Variability.

    PubMed

    Foisy, Arnaud; Kapoula, Zoï

    2016-01-01

    In a previous experiment, we showed that among young and healthy subjects, thin plantar inserts improve postural control and modify vergence amplitudes. In this experiment, however, significant inter-individual variability was observed. We hypothesize that its origin could be attributed to a different reliance upon feet cutaneous afferents. In order to test this hypothesis, we re-analyzed the data relative to 31 young (age 25.7 ± 3.8) and healthy subjects who participated in the first experiment after having classified them into two groups depending on their Plantar Quotient (PQ = Surface area of CoPfoam/Surface area of CoPfirm ground × 100). Foam decreases the information arising from the feet, normally resulting in a PQ > 100. Hence, the PQ provides information on the weight of plantar cutaneous afferents used in postural control. Twelve people were Plantar-Independent Subjects, as indicated by a PQ < 100. These individuals did not behave like the Normal Plantar Quotient Subjects: they were almost insensitive to the plantar stimulations in terms of postural control and totally insensitive in terms of oculomotor control. We conclude that the inter-individual variability observed in our first experiment is explained by the subjects' degree of plantar reliance. We propose that plantar independence is a dysfunctional situation revealing inefficiency in plantar cutaneous afferents. The latter could be due to a latent somatosensory dysfunction generating a noise which prevents the CNS from correctly processing and using feet somatosensory afferents both for balance and vergence control: Plantar Irritating Stimulus. Considering the non-noxious nature and prevalence of this phenomenon, these results can be of great interest to researchers and clinicians who attempt to trigger postural or oculomotor responses through mechanical stimulation of the foot sole.

  13. Efficient Monte Carlo modelling of individual tumour cell propagation for hypoxic head and neck cancer

    NASA Astrophysics Data System (ADS)

    Tuckwell, W.; Bezak, E.; Yeoh, E.; Marcu, L.

    2008-09-01

    A Monte Carlo tumour model has been developed to simulate tumour cell propagation for head and neck squamous cell carcinoma. The model aims to eventually provide a radiobiological tool for radiation oncology clinicians to plan patient treatment schedules based on properties of the individual tumour. The inclusion of an oxygen distribution amongst the tumour cells enables the model to incorporate hypoxia and other associated parameters, which affect tumour growth. The object oriented program FORTRAN 95 has been used to create the model algorithm, with Monte Carlo methods being employed to randomly assign many of the cell parameters from probability distributions. Hypoxia has been implemented through random assignment of partial oxygen pressure values to individual cells during tumour growth, based on in vivo Eppendorf probe experimental data. The accumulation of up to 10 million virtual tumour cells in 15 min of computer running time has been achieved. The stem cell percentage and the degree of hypoxia are the parameters which most influence the final tumour growth rate. For a tumour with a doubling time of 40 days, the final stem cell percentage is approximately 1% of the total cell population. The effect of hypoxia on the tumour growth rate is significant. Using a hypoxia induced cell quiescence limit which affects 50% of cells with and oxygen levels less than 1 mm Hg, the tumour doubling time increases to over 200 days and the time of tumour growth for a clinically detectable tumour (109 cells) increases from 3 to 8 years. A biologically plausible Monte Carlo model of hypoxic head and neck squamous cell carcinoma tumour growth has been developed for real time assessment of the effects of multiple biological parameters which impact upon the response of the individual patient to fractionated radiotherapy.

  14. IPR 1.0: an efficient method for calculating solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Chen, W.; Li, J.

    2013-12-01

    Climate change may alter the spatial distribution, composition, structure, and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate solar radiation absorbed by individual plants for understanding and predicting their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the analytical solutions of random distributions of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and is suitable for ecological models to simulate long-term transient responses of plant communities to climate change.

  15. IPR 1.0: an efficient method for calculating solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Chen, W.; Li, J.

    2014-07-01

    Climate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.

  16. Thermal substitution and aerobic efficiency: measuring and predicting effects of heat balance on endotherm diving energetics.

    PubMed

    Lovvorn, J R

    2007-11-29

    For diving endotherms, modelling costs of locomotion as a function of prey dispersion requires estimates of the costs of diving to different depths. One approach is to estimate the physical costs of locomotion (Pmech) with biomechanical models and to convert those estimates to chemical energy needs by an aerobic efficiency (eta=Pmech/Vo2) based on oxygen consumption (Vo2) in captive animals. Variations in eta with temperature depend partly on thermal substitution, whereby heat from the inefficiency of exercising muscles or the heat increment of feeding (HIF) can substitute for thermogenesis. However, measurements of substitution have ranged from lack of detection to nearly complete use of exercise heat or HIF. This inconsistency may reflect (i) problems in methods of calculating substitution, (ii) confounding mechanisms of thermoregulatory control, or (iii) varying conditions that affect heat balance and allow substitution to be expressed. At present, understanding of how heat generation is regulated, and how heat is transported among tissues during exercise, digestion, thermal challenge and breath holding, is inadequate for predicting substitution and aerobic efficiencies without direct measurements for conditions of interest. Confirming that work rates during exercise are generally conserved, and identifying temperatures at those work rates below which shivering begins, may allow better prediction of aerobic efficiencies for ecological models.

  17. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    NASA Astrophysics Data System (ADS)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  18. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  19. Model-based evaluation of subsurface monitoring networks for improved efficiency and predictive certainty of regional groundwater models

    NASA Astrophysics Data System (ADS)

    Gosses, M. J.; Wöhling, Th.; Moore, C. R.; Dann, R.; Scott, D. M.; Close, M.

    2012-04-01

    -specific prediction target under consideration. Therefore, the worth of individual observation locations may differ for different prediction targets. Our evaluation is based on predictions of lowland stream discharge resulting from changes in land use and irrigation in the upper Central Plains catchment. In our analysis, we adopt the model predictive uncertainty analysis method by Moore and Doherty (2005) which accounts for contributions from both measurement errors and uncertain structural heterogeneity. The method is robust and efficient due to a linearity assumption in the governing equations and readily implemented for application in the model-independent parameter estimation and uncertainty analysis toolkit PEST (Doherty, 2010). The proposed methods can be applied not only for the evaluation of monitoring networks, but also for the optimization of networks, to compare alternative monitoring strategies, as well as to identify best cost-benefit monitoring design even prior to any data acquisition.

  20. Studying Individual Differences in Predictability with Gamma Regression and Nonlinear Multilevel Models

    ERIC Educational Resources Information Center

    Culpepper, Steven Andrew

    2010-01-01

    Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…

  1. Studying Individual Differences in Predictability with Gamma Regression and Nonlinear Multilevel Models

    ERIC Educational Resources Information Center

    Culpepper, Steven Andrew

    2010-01-01

    Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…

  2. Neural activity in the hippocampus predicts individual visual short-term memory capacity.

    PubMed

    von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

    2013-07-01

    Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating.

  3. Inter-individual variation in vertebral kinematics affects predictions of neck musculoskeletal models.

    PubMed

    Nevins, Derek D; Zheng, Liying; Vasavada, Anita N

    2014-10-17

    Experimental studies have found significant variation in cervical intervertebral kinematics (IVK) among healthy subjects, but the effect of this variation on biomechanical properties, such as neck strength, has not been explored. The goal of this study was to quantify variation in model predictions of extension strength, flexion strength and gravitational demand (the ratio of gravitational load from the weight of the head to neck muscle extension strength), due to inter-subject variation in IVK. IVK were measured from sagittal radiographs of 24 subjects (14F, 10M) in five postures: maximal extension, mid-extension, neutral, mid-flexion, and maximal flexion. IVK were defined by the position (anterior-posterior and superior-inferior) of each cervical vertebra with respect to T1 and its angle with respect to horizontal, and fit with a cubic polynomial over the range of motion. The IVK of each subject were scaled and incorporated into musculoskeletal models to create models that were identical in muscle force- and moment-generating properties but had subject-specific kinematics. The effect of inter-subject variation in IVK was quantified using the coefficient of variation (COV), the ratio of the standard deviation to the mean. COV of extension strength ranged from 8% to 15% over the range of motion, but COV of flexion strength was 20-80%. Moreover, the COV of gravitational demand was 80-90%, because the gravitational demand is affected by head position as well as neck strength. These results indicate that including inter-individual variation in models is important for evaluating neck musculoskeletal biomechanical properties. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. INTER-INDIVIDUAL VARIATION IN VERTEBRAL KINEMATICS AFFECTS PREDICTIONS OF NECK MUSCULOSKELETAL MODELS

    PubMed Central

    Nevins, Derek D.; Zheng, Liying; Vasavada, Anita N.

    2014-01-01

    Experimental studies have found significant variation in cervical intervertebral kinematics (IVK) among healthy subjects, but the effect of this variation on biomechanical properties, such as neck strength, has not been explored. The goal of this study was to quantify variation in model predictions of extension strength, flexion strength and gravitational demand (the ratio of gravitational load from the weight of the head to neck muscle extension strength), due to inter-subject variation in IVK. IVK were measured from sagittal radiographs of twenty-four subjects (14F, 10M) in five postures: maximal extension, mid-extension, neutral, mid-flexion, and maximal flexion. IVK were defined by the position (anterior-posterior and superior-inferior) of each cervical vertebra with respect to T1 and its angle with respect to horizontal, and fit with a cubic polynomial over the range of motion. The IVK of each subject were scaled and incorporated into musculoskeletal models to create models that were identical in muscle force- and moment-generating properties but had subject-specific kinematics. The effect of inter-subject variation in IVK was quantified using the coefficient of variation (COV), the ratio of the standard deviation to the mean. COV of extension strength ranged from 8 – 15% over the range of motion, but COV of flexion strength were 20 – 80%. Moreover, the COV of gravitational demand was 80 – 90%, because the gravitational demand is affected by head position as well as neck strength. These results indicate that including inter-individual variation in models is important for evaluating neck musculoskeletal biomechanical properties. PMID:25234351

  5. HBV-DNA levels predict overall mortality in HIV/HBV coinfected individuals.

    PubMed

    Nikolopoulos, Georgios K; Paraskevis, Dimitrios; Psichogiou, Mina; Hatzakis, Angelos

    2016-03-01

    The coinfection of Hepatitis B virus (HBV) and human immunodeficiency virus (HIV) has been associated with increased death rates. However, the relevant research has mostly relied on serologic HBV testing [HBV surface antigen (HBsAg)]. The aim of this work was to explore the relationship of HBV viraemia with overall mortality among HIV/HBV coinfected individuals. The analysis included 1,609 HIV seropositives of a previously described cohort (1984-2003) with limited exposure to tenofovir (12%) and a median follow-up of approximately 5 years. Those with persistent expression of HBsAg were further tested for HBV-DNA. The data were analyzed using Poisson regression models. Totally, 101 participants were chronic carriers of HBsAg (6.28%). Of these, 81 were tested for HBV-DNA. The median HBV-DNA levels were 3.81 log (base-10) International Units (IU)/ml. A third (31%) of those tested for HBV-DNA had received tenofovir. Before developing acquired immune deficiency syndrome (AIDS), the adjusted incidence rate ratio (IRR) for all-cause mortality of coinfected patients with HBV viraemia above the median value versus the HIV monoinfected group was 3.44 [95% confidence interval (CI): 1.05-11.27]. Multivariable regressions in the coinfected group only (n = 81) showed that one log-10 increase in HBV-DNA levels was associated with an elevated risk for death (IRR: 1.24, 95%CI: 1.03-1.49). HBV-DNA levels predict overall mortality in the setting of HIV/HBV coinfection, especially during the period before developing AIDS, and could thus help prioritize needs and determine the frequency of medical monitoring.

  6. Student perception of group dynamics predicts individual performance: Comfort and equity matter

    PubMed Central

    Theobald, Elli J.; Eddy, Sarah L.; Grunspan, Daniel Z.; Wiggins, Benjamin L.

    2017-01-01

    Active learning in college classes and participation in the workforce frequently hinge on small group work. However, group dynamics vary, ranging from equitable collaboration to dysfunctional groups dominated by one individual. To explore how group dynamics impact student learning, we asked students in a large-enrollment university biology class to self-report their experience during in-class group work. Specifically, we asked students whether there was a friend in their group, whether they were comfortable in their group, and whether someone dominated their group. Surveys were administered after students participated in two different types of intentionally constructed group activities: 1) a loosely-structured activity wherein students worked together for an entire class period (termed the ‘single-group’ activity), or 2) a highly-structured ‘jigsaw’ activity wherein students first independently mastered different subtopics, then formed new groups to peer-teach their respective subtopics. We measured content mastery by the change in score on identical pre-/post-tests. We then investigated whether activity type or student demographics predicted the likelihood of reporting working with a dominator, being comfortable in their group, or working with a friend. We found that students who more strongly agreed that they worked with a dominator were 17.8% less likely to answer an additional question correct on the 8-question post-test. Similarly, when students were comfortable in their group, content mastery increased by 27.5%. Working with a friend was the single biggest predictor of student comfort, although working with a friend did not impact performance. Finally, we found that students were 67% less likely to agree that someone dominated their group during the jigsaw activities than during the single group activities. We conclude that group activities that rely on positive interdependence, and include turn-taking and have explicit prompts for students to explain

  7. Predicting Retrograde Autobiographical Memory Changes Following Electroconvulsive Therapy: Relationships between Individual, Treatment, and Early Clinical Factors.

    PubMed

    Martin, Donel M; Gálvez, Verònica; Loo, Colleen K

    2015-06-19

    Loss of personal memories experienced prior to receiving electroconvulsive therapy is common and distressing and in some patients can persist for many months following treatment. Improved understanding of the relationships between individual patient factors, electroconvulsive therapy treatment factors, and clinical indicators measured early in the electroconvulsive therapy course may help clinicians minimize these side effects through better management of the electroconvulsive therapy treatment approach. In this study we examined the associations between the above factors for predicting retrograde autobiographical memory changes following electroconvulsive therapy. Seventy-four depressed participants with major depressive disorder were administered electroconvulsive therapy 3 times per week using either a right unilateral or bitemporal electrode placement and brief or ultrabrief pulse width. Verbal fluency and retrograde autobiographical memory (assessed using the Columbia Autobiographical Memory Interview - Short Form) were tested at baseline and after the last electroconvulsive therapy treatment. Time to reorientation was measured immediately following the third and sixth electroconvulsive therapy treatments. Results confirmed the utility of measuring time to reorientation early during the electroconvulsive therapy treatment course as a predictor of greater retrograde amnesia and the importance of assessing baseline cognitive status for identifying patients at greater risk for developing later side effects. With increased number of electroconvulsive therapy treatments, older age was associated with increased time to reorientation. Consistency of verbal fluency performance was moderately correlated with change in Columbia Autobiographical Memory Interview - Short Form scores following right unilateral electroconvulsive therapy. Electroconvulsive therapy treatment techniques associated with lesser cognitive side effects should be particularly considered for

  8. Predicting Retrograde Autobiographical Memory Changes Following Electroconvulsive Therapy: Relationships between Individual, Treatment, and Early Clinical Factors

    PubMed Central

    Gálvez, Verònica; Loo, Colleen K.

    2015-01-01

    Background: Loss of personal memories experienced prior to receiving electroconvulsive therapy is common and distressing and in some patients can persist for many months following treatment. Improved understanding of the relationships between individual patient factors, electroconvulsive therapy treatment factors, and clinical indicators measured early in the electroconvulsive therapy course may help clinicians minimize these side effects through better management of the electroconvulsive therapy treatment approach. In this study we examined the associations between the above factors for predicting retrograde autobiographical memory changes following electroconvulsive therapy. Methods: Seventy-four depressed participants with major depressive disorder were administered electroconvulsive therapy 3 times per week using either a right unilateral or bitemporal electrode placement and brief or ultrabrief pulse width. Verbal fluency and retrograde autobiographical memory (assessed using the Columbia Autobiographical Memory Interview – Short Form) were tested at baseline and after the last electroconvulsive therapy treatment. Time to reorientation was measured immediately following the third and sixth electroconvulsive therapy treatments. Results: Results confirmed the utility of measuring time to reorientation early during the electroconvulsive therapy treatment course as a predictor of greater retrograde amnesia and the importance of assessing baseline cognitive status for identifying patients at greater risk for developing later side effects. With increased number of electroconvulsive therapy treatments, older age was associated with increased time to reorientation. Consistency of verbal fluency performance was moderately correlated with change in Columbia Autobiographical Memory Interview – Short Form scores following right unilateral electroconvulsive therapy. Conclusions: Electroconvulsive therapy treatment techniques associated with lesser cognitive side

  9. Competition versus planning in health care: implications for corporate and individual incentives, efficiency & control.

    PubMed

    Lee, K

    1991-01-01

    This paper is about the management of change; and, most especially, about the changing tides of thinking that health planning and, more latterly, competition could bring about desired change in the health industry towards cost containment, efficiency and control. Looking back over the decade of the 1980s, it was characterised, for many countries, as a real questioning of the role of the public sector in people's life, and--in terms of public/private provision--a re-examination of what is public and should be. Coupled with this inquiry was a growing belief that comprehensive health planning was too lofty a goal, and that however elegant in theory, its delivery in practice fell far short of its ideals. Attention has therefore focused on the workings of competitive markets, and the extent to which objectives of cost containment and economic efficiency can be better addressed through competition and internal markets. In reality, the mixed economy is the only policy option available to developed countries today. Public and private monopolies are frowned upon, and the search is on for intermediate possibilities that capture some of the advantages of markets without their disadvantages, and arrangements that motivate consumer choice and simultaneously yield efficiency in the production and distribution of health care. By way of illustration, this paper looks at a number of innovations taking place to address these issues; and, in the context of the UK, at the most recent government proposals in respect of self-governing trusts and GP budget holders, as illustrations of the move towards the internal market, or to managed competition. Not surprisingly, the two areas that feature large on the agenda are hospital (and community) information systems; and, the motivations, rewards and penalties of the provider institutions that deliver services, and the consumers and purchasers who will "buy" them. Whether the mould can and should be broken is left tantalisingly open in the

  10. Both Nearest Neighbours and Long-term Affiliates Predict Individual Locations During Collective Movement in Wild Baboons.

    PubMed

    Farine, Damien R; Strandburg-Peshkin, Ariana; Berger-Wolf, Tanya; Ziebart, Brian; Brugere, Ivan; Li, Jia; Crofoot, Margaret C

    2016-06-13

    In many animal societies, groups of individuals form stable social units that are shaped by well-delineated dominance hierarchies and a range of affiliative relationships. How do socially complex groups maintain cohesion and achieve collective movement? Using high-resolution GPS tracking of members of a wild baboon troop, we test whether collective movement in stable social groups is governed by interactions among local neighbours (commonly found in groups with largely anonymous memberships), social affiliates, and/or by individuals paying attention to global group structure. We construct candidate movement prediction models and evaluate their ability to predict the future trajectory of focal individuals. We find that baboon movements are best predicted by 4 to 6 neighbours. While these are generally individuals' nearest neighbours, we find that baboons have distinct preferences for particular neighbours, and that these social affiliates best predict individual location at longer time scales (>10 minutes). Our results support existing theoretical and empirical studies highlighting the importance of local rules in driving collective outcomes, such as collective departures, in primates. We extend previous studies by elucidating the rules that maintain cohesion in baboons 'on the move', as well as the different temporal scales of social interactions that are at play.

  11. High-intensity interval training improves performance in young and older individuals by increasing mechanical efficiency.

    PubMed

    Jabbour, Georges; Iancu, Horia-Daniel; Mauriège, Pascale; Joanisse, Denis R; Martin, Luc J

    2017-04-01

    This study evaluated the effects of 6 weeks of high-intensity interval training (HIIT) on mechanical efficiency (ME) in young and older groups. Seventeen healthy young adults [26.2(2.4) year], and thirteen healthy older adults [54.5(2.3) year] completed a 6-week HIIT intervention (three sessions per week) on an electromagnetically braked cycle ergometer. Each HIIT session contained six repetitions of supramaximal exercise intervals (6 seconds each) with 2 min of passive recovery between each repetition. ME (%) were computed in net terms across stages corresponding to ventilator thresholds 1 (VT1) and 2 (VT2) and at 100% of maximal oxygen consumption (VO2max) of an incremental maximal cycling test. After 6 weeks, the ME values did not differ between the two groups and were significantly higher than the ones at baseline (P < 0.01). In this study, the multiple linear regression analysis demonstrated the increases in maximal power (Pmax) contributed significantly to ME increases over 6 weeks at VT1, VT2 and at 100% of VO2max This model accounted respectively for 28, 38, and 42%, of the increases. In older adults, ME determined during incremental maximal cycling test increases at VT1, VT2 and at 100% over 6-week HIIT intervention, and the increment appeared to be related to increases in Pmax. HIIT can be recommended as a strategy aimed at improving muscle efficiency among older adults.

  12. A branch scale analytical model for predicting the vegetation collection efficiency of ultrafine particles

    NASA Astrophysics Data System (ADS)

    Lin, M.; Katul, G. G.; Khlystov, A.

    2012-05-01

    The removal of ultrafine particles (UFP) by vegetation is now receiving significant attention given their role in cloud physics, human health and respiratory related diseases. Vegetation is known to be a sink for UFP, prompting interest in their collection efficiency. A number of models have tackled the UFP collection efficiency of an isolated leaf or a flat surface; however, up-scaling these theories to the ecosystem level has resisted complete theoretical treatment. To progress on a narrower scope of this problem, simultaneous experimental and theoretical investigations are carried out at the “intermediate” branch scale. Such a scale retains the large number of leaves and their interaction with the flow without the heterogeneities and added geometric complexities encountered within ecosystems. The experiments focused on the collection efficiencies of UFP in the size range 12.6-102 nm for pine and juniper branches in a wind tunnel facility. Scanning mobility particle sizers were used to measure the concentration of each diameter class of UFP upstream and downstream of the vegetation branches thereby allowing the determination of the UFP vegetation collection efficiencies. The UFP vegetation collection efficiency was measured at different wind speeds (0.3-1.5 m s-1), packing density (i.e. volume fraction of leaf or needle fibers; 0.017 and 0.040 for pine and 0.037, 0.055 for juniper), and branch orientations. These measurements were then used to investigate the performance of a proposed analytical model that predicts the branch-scale collection efficiency using conventional canopy properties such as the drag coefficient and leaf area density. Despite the numerous simplifications employed, the proposed analytical model agreed with the wind tunnel measurements mostly to within 20%. This analytical tractability can benefit future air quality and climate models incorporating UFP.

  13. Controlled formation of polymer nanocapsules with high diffusion-barrier properties and prediction of encapsulation efficiency.

    PubMed

    Hofmeister, Ines; Landfester, Katharina; Taden, Andreas

    2015-01-02

    Polymer nanocapsules with high diffusion-barrier performance were designed following simple thermodynamic considerations. Hindered diffusion of the enclosed material leads to high encapsulation efficiencies (EEs), which was demonstrated based on the encapsulation of highly volatile compounds of different chemical natures. Low interactions between core and shell materials are key factors to achieve phase separation and a high diffusion barrier of the resulting polymeric shell. These interactions can be characterized and quantified using the Hansen solubility parameters. A systematic study of our copolymer system revealed a linear relationship between the Hansen parameter for hydrogen bonding (δh ) and encapsulation efficiencies which enables the prediction of encapsulated amounts for any material. Furthermore EEs of poorly encapsulated materials can be increased by mixing them with a mediator compound to give lower overall δh values.

  14. An efficient sampling algorithm for uncertain abnormal data detection in biomedical image processing and disease prediction.

    PubMed

    Liu, Fei; Zhang, Xi; Jia, Yan

    2015-01-01

    In this paper, we propose a computer information processing algorithm that can be used for biomedical image processing and disease prediction. A biomedical image is considered a data object in a multi-dimensional space. Each dimension is a feature that can be used for disease diagnosis. We introduce a new concept of the top (k1,k2) outlier. It can be used to detect abnormal data objects in the multi-dimensional space. This technique focuses on uncertain space, where each data object has several possible instances with distinct probabilities. We design an efficient sampling algorithm for the top (k1,k2) outlier in uncertain space. Some improvement techniques are used for acceleration. Experiments show our methods' high accuracy and high efficiency.

  15. Predicting the effects of human developments on individual dolphins to understand potential long-term population consequences

    PubMed Central

    Pirotta, Enrico; Harwood, John; Thompson, Paul M.; New, Leslie; Cheney, Barbara; Arso, Monica; Hammond, Philip S.; Donovan, Carl; Lusseau, David

    2015-01-01

    Human activities that impact wildlife do not necessarily remove individuals from populations. They may also change individual behaviour in ways that have sublethal effects. This has driven interest in developing analytical tools that predict the population consequences of short-term behavioural responses. In this study, we incorporate empirical information on the ecology of a population of bottlenose dolphins into an individual-based model that predicts how individuals' behavioural dynamics arise from their underlying motivational states, as well as their interaction with boat traffic and dredging activities. We simulate the potential effects of proposed coastal developments on this population and predict that the operational phase may affect animals' motivational states. For such results to be relevant for management, the effects on individuals' vital rates also need to be quantified. We investigate whether the relationship between an individual's exposure and the survival of its calves can be directly estimated using a Bayesian multi-stage model for calf survival. The results suggest that any effect on calf survival is probably small and that a significant relationship could only be detected in large, closely studied populations. Our work can be used to guide management decisions, accelerate the consenting process for coastal and offshore developments and design targeted monitoring. PMID:26511044

  16. Predicting the effects of human developments on individual dolphins to understand potential long-term population consequences.

    PubMed

    Pirotta, Enrico; Harwood, John; Thompson, Paul M; New, Leslie; Cheney, Barbara; Arso, Monica; Hammond, Philip S; Donovan, Carl; Lusseau, David

    2015-11-07

    Human activities that impact wildlife do not necessarily remove individuals from populations. They may also change individual behaviour in ways that have sublethal effects. This has driven interest in developing analytical tools that predict the population consequences of short-term behavioural responses. In this study, we incorporate empirical information on the ecology of a population of bottlenose dolphins into an individual-based model that predicts how individuals' behavioural dynamics arise from their underlying motivational states, as well as their interaction with boat traffic and dredging activities. We simulate the potential effects of proposed coastal developments on this population and predict that the operational phase may affect animals' motivational states. For such results to be relevant for management, the effects on individuals' vital rates also need to be quantified. We investigate whether the relationship between an individual's exposure and the survival of its calves can be directly estimated using a Bayesian multi-stage model for calf survival. The results suggest that any effect on calf survival is probably small and that a significant relationship could only be detected in large, closely studied populations. Our work can be used to guide management decisions, accelerate the consenting process for coastal and offshore developments and design targeted monitoring.

  17. Oxygen Uptake Efficiency Slope Predicts Poor Outcome in Patients With Idiopathic Pulmonary Arterial Hypertension.

    PubMed

    Tang, Yi; Luo, Qin; Liu, Zhihong; Ma, Xiuping; Zhao, Zhihui; Huang, Zhiwei; Gao, Liu; Jin, Qi; Xiong, Changming; Ni, Xinhai

    2017-06-30

    Few published studies have evaluated the power of the oxygen uptake efficiency slope (OUES) to predict outcomes in patients with idiopathic pulmonary arterial hypertension (IPAH), who typically die of right-sided heart failure. Our study sought to evaluate the power of OUES to predict clinical worsening and mortality in patients with IPAH. Patients with newly diagnosed IPAH who underwent symptom-limited cardiopulmonary exercise testing from November 11, 2010, to June 25, 2015, in our hospital were prospectively enrolled and followed for up to 66 months. Clinical worsening and mortality were recorded. A total of 210 patients with IPAH (159 women; mean age, 32±10 years) were studied with a median follow-up of 41 months. Thirty-one patients died, 1 patient underwent lung transplantation, and 85 patients presented with clinical worsening. The univariate analysis revealed that OUES, OUESI (OUESI=OUES/body surface area), peak oxygen uptake (V˙O2), peak V˙O2/kg, ventilation (V˙E)/carbon dioxide output (V˙CO2) slope, peak systolic blood pressure, heart rate recovery, pulmonary vascular resistance, cardiac index, N-terminal prohormone brain natriuretic peptide, and World Health Organization functional class were all predictive of clinical worsening and mortality (all P<0.05). Multivariate analysis demonstrated that OUESI and cardiac index were independently predictive of clinical worsening, and OUESI and N-terminal prohormone brain natriuretic peptide were independently predictive of mortality. Patients with OUESI ≤0.52 m(-2) had a worse 5-year survival rate than patients with OUESI >0.52 m(-2) (41.9% versus 89.8%, P<0.0001). The OUES, a submaximal parameter obtained from cardiopulmonary exercise testing, provides prognostic information for predicting clinical worsening and mortality in patients with IPAH. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  18. Digestive efficiency mediated by serum calcium predicts bone mineral density in the common marmoset (Callithrix jacchus).

    PubMed

    Jarcho, Michael R; Power, Michael L; Layne-Colon, Donna G; Tardif, Suzette D

    2013-02-01

    Two health problems have plagued captive common marmoset (Callithrix jacchus) colonies for nearly as long as those colonies have existed: marmoset wasting syndrome and metabolic bone disease. While marmoset wasting syndrome is explicitly linked to nutrient malabsorption, we propose metabolic bone disease is also linked to nutrient malabsorption, although indirectly. If animals experience negative nutrient balance chronically, critical nutrients may be taken from mineral stores such as the skeleton, thus leaving those stores depleted. We indirectly tested this prediction through an initial investigation of digestive efficiency, as measured by apparent energy digestibility, and serum parameters known to play a part in metabolic bone mineral density of captive common marmoset monkeys. In our initial study on 12 clinically healthy animals, we found a wide range of digestive efficiencies, and subjects with lower digestive efficiency had lower serum vitamin D despite having higher food intakes. A second experiment on 23 subjects including several with suspected bone disease was undertaken to measure digestive and serum parameters, with the addition of a measure of bone mineral density by dual-energy X-ray absorptiometry (DEXA). Bone mineral density was positively associated with apparent digestibility of energy, vitamin D, and serum calcium. Further, digestive efficiency was found to predict bone mineral density when mediated by serum calcium. These data indicate that a poor ability to digest and absorb nutrients leads to calcium and vitamin D insufficiency. Vitamin D absorption may be particularly critical for indoor-housed animals, as opposed to animals in a more natural setting, because vitamin D that would otherwise be synthesized via exposure to sunlight must be absorbed from their diet. If malabsorption persists, metabolic bone disease is a possible consequence in common marmosets. These findings support our hypothesis that both wasting syndrome and metabolic bone

  19. Quantitative Regression Models for the Prediction of Chemical Properties by an Efficient Workflow.

    PubMed

    Yin, Yongmin; Xu, Congying; Gu, Shikai; Li, Weihua; Liu, Guixia; Tang, Yun

    2015-10-01

    Rapid safety assessment is more and more needed for the increasing chemicals both in chemical industries and regulators around the world. The traditional experimental methods couldn't meet the current demand any more. With the development of the information technology and the growth of experimental data, in silico modeling has become a practical and rapid alternative for the assessment of chemical properties, especially for the toxicity prediction of organic chemicals. In this study, a quantitative regression workflow was built by KNIME to predict chemical properties. With this regression workflow, quantitative values of chemical properties can be obtained, which is different from the binary-classification model or multi-classification models that can only give qualitative results. To illustrate the usage of the workflow, two predictive models were constructed based on datasets of Tetrahymena pyriformis toxicity and Aqueous solubility. The qcv (2) and qtest (2) of 5-fold cross validation and external validation for both types of models were greater than 0.7, which implies that our models are robust and reliable, and the workflow is very convenient and efficient in prediction of various chemical properties. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. [Prediction of the efficiency of endoscopic lung volume reduction by valves in severe emphysema].

    PubMed

    Bocquillon, V; Briault, A; Reymond, E; Arbib, F; Jankowski, A; Ferretti, G; Pison, C

    2016-11-01

    In severe emphysema, endoscopic lung volume reduction with valves is an alternative to surgery with less morbidity and mortality. In 2015, selection of patients who will respond to this technique is based on emphysema heterogeneity, a complete fissure visible on the CT-scan and absence of collateral ventilation between lobes. Our case report highlights that individualized prediction is possible. A 58-year-old woman had severe, disabling pulmonary emphysema. A high resolution thoracic computed tomography scan showed that the emphysema was heterogeneous, predominantly in the upper lobes, integrity of the left greater fissure and no collateral ventilation with the left lower lobe. A valve was inserted in the left upper lobe bronchus. At one year, clinical and functional benefits were significant with complete atelectasis of the treated lobe. The success of endoscopic lung volume reduction with a valve can be predicted, an example of personalized medicine. Copyright © 2016 SPLF. Published by Elsevier Masson SAS. All rights reserved.

  1. The role of Doppler studies in predicting individual intrauterine fetal demise after laser therapy for twin-twin transfusion syndrome.

    PubMed

    Martínez, J M; Bermúdez, C; Becerra, C; López, J; Morales, W J; Quintero, R A

    2003-09-01

    To investigate the role of Doppler studies in predicting individual fetal demise in patients scheduled for selective laser photocoagulation of communicating vessels (SLPCV) for twin-twin transfusion syndrome (TTTS). Doppler studies of the umbilical artery, umbilical vein, ductus venosus, tricuspid valve regurgitation and middle cerebral artery were performed in the donor and recipient twins before and 24 hours after SLPCV. Results were analyzed cross-sectionally and longitudinally. As multiple comparisons were made, an a priori alpha rejection was set at P < 0.001. One hundred and ten consecutive patients were available for analysis. Overall fetal survival was 68.6% (151/220) with at least one survivor in 88.2% (97/110) of cases. Absent or reversed end-diastolic velocity in the umbilical artery of the donor twin was the only preoperative Doppler result predictive of intrauterine fetal demise (IUFD) (10/15, 66.7%, P < 0.001). Postoperatively, reversed flow during atrial contraction in the ductus venosus of the donor twin showed a trend towards prediction of IUFD of this fetus (4/5, 80%, P = 0.007). No other Doppler studies, including the longitudinal analyses, were predictive of IUFD. Our data suggest that preoperative absent or reversed end-diastolic velocity in the umbilical artery may be useful in predicting individual fetal demise of the donor twin in TTTS patients scheduled for SLPCV. This may reflect the role of decreased individual placental mass that may be associated with some donor twins. The inability of other Doppler studies to predict individual IUFD may be explained preoperatively by the effect of the interfetal vascular connections on the individual Doppler signals and postoperatively by the effect of surgery or the timing of the assessment. Our findings may be important in patient counseling, in furthering understanding of the disease, and perhaps in improving surgical technique. Copyright 2003 ISUOG. Published by John Wiley & Sons, Ltd.

  2. A New Method for Predicting Patient Survivorship Using Efficient Bayesian Network Learning

    PubMed Central

    Jiang, Xia; Xue, Diyang; Brufsky, Adam; Khan, Seema; Neapolitan, Richard

    2014-01-01

    The purpose of this investigation is to develop and evaluate a new Bayesian network (BN)-based patient survivorship prediction method. The central hypothesis is that the method predicts patient survivorship well, while having the capability to handle high-dimensional data and be incorporated into a clinical decision support system (CDSS). We have developed EBMC_Survivorship (EBMC_S), which predicts survivorship for each year individually. EBMC_S is based on the EBMC BN algorithm, which has been shown to handle high-dimensional data. BNs have excellent architecture for decision support systems. In this study, we evaluate EBMC_S using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which concerns breast tumors. A 5-fold cross-validation study indicates that EMBC_S performs better than the Cox proportional hazard model and is comparable to the random survival forest method. We show that EBMC_S provides additional information such as sensitivity analyses, which covariates predict each year, and yearly areas under the ROC curve (AUROCs). We conclude that our investigation supports the central hypothesis. PMID:24558297

  3. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment.

    PubMed

    Kraatz, Miriam; Sears, Lindsay E; Coberley, Carter R; Pope, James E

    2016-08-01

    Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284-290).

  4. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment

    PubMed Central

    Kraatz, Miriam; Coberley, Carter R.; Pope, James E.

    2016-01-01

    Abstract Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284–290) PMID:26674396

  5. Mitochondrial Efficiency-Dependent Viability of Saccharomyces cerevisiae Mutants Carrying Individual Electron Transport Chain Component Deletions.

    PubMed

    Kwon, Young-Yon; Choi, Kyung-Mi; Cho, ChangYeon; Lee, Cheol-Koo

    2015-12-01

    Mitochondria play a crucial role in eukaryotic cells; the mitochondrial electron transport chain (ETC) generates adenosine triphosphate (ATP), which serves as an energy source for numerous critical cellular activities. However, the ETC also generates deleterious reactive oxygen species (ROS) as a natural byproduct of oxidative phosphorylation. ROS are considered the major cause of aging because they damage proteins, lipids, and DNA by oxidation. We analyzed the chronological life span, growth phenotype, mitochondrial membrane potential (MMP), and intracellular ATP and mitochondrial superoxide levels of 33 single ETC component-deleted strains during the chronological aging process. Among the ETC mutant strains, 14 (sdh1Δ, sdh2Δ, sdh4Δ, cor1Δ, cyt1Δ, qcr7Δ, qcr8Δ, rip1Δ, cox6Δ, cox7Δ, cox9Δ, atp4Δ, atp7Δ, and atp17Δ) showed a significantly shorter life span. The deleted genes encode important elements of the ETC components succinate dehydrogenase (complex II) and cytochrome c oxidase (complex IV), and some of the deletions lead to structural instability of the membrane-F1F0-ATP synthase due to mutations in the stator stalk (complex V). These short-lived strains generated higher superoxide levels and produced lower ATP levels without alteration of MMP. In summary, ETC mutations decreased the life span of yeast due to impaired mitochondrial efficiency.

  6. Enabling Energy Efficiency and Polarity Control in Germanium Nanowire Transistors by Individually Gated Nanojunctions.

    PubMed

    Trommer, Jens; Heinzig, André; Mühle, Uwe; Löffler, Markus; Winzer, Annett; Jordan, Paul M; Beister, Jürgen; Baldauf, Tim; Geidel, Marion; Adolphi, Barbara; Zschech, Ehrenfried; Mikolajick, Thomas; Weber, Walter M

    2017-02-28

    Germanium is a promising material for future very large scale integration transistors, due to its superior hole mobility. However, germanium-based devices typically suffer from high reverse junction leakage due to the low band-gap energy of 0.66 eV and therefore are characterized by high static power dissipation. In this paper, we experimentally demonstrate a solution to suppress the off-state leakage in germanium nanowire Schottky barrier transistors. Thereto, a device layout with two independent gates is used to induce an additional energy barrier to the channel that blocks the undesired carrier type. In addition, the polarity of the same doping-free device can be dynamically switched between p- and n-type. The shown germanium nanowire approach is able to outperform previous polarity-controllable device concepts on other material systems in terms of threshold voltages and normalized on-currents. The dielectric and Schottky barrier interface properties of the device are analyzed in detail. Finite-element drift-diffusion simulations reveal that both leakage current suppression and polarity control can also be achieved at highly scaled geometries, providing solutions for future energy-efficient systems.

  7. The effect of breed and individual heterosis on the feed efficiency, performance, and carcass characteristics of feedlot steers.

    PubMed

    Retallick, K M; Faulkner, D B; Rodriguez-Zas, S L; Nkrumah, J D; Shike, D W

    2013-11-01

    This study was conducted to evaluate maternal breed effects, direct breed effects, and individual heterosis on subsequent steer performance, carcass, and feed efficiency traits. This was a consecutive 2-yr trial using 158 steers. The same dam breeds, Angus (AN) and purebred Simmental (SM), were used both years. Also, the same AN and SM sires (n=11) were used both years. Steers were AN, SM, or AN×SM breed composition. Steers were managed similarly before weaning and early weaned at 56±9 d of age. Steers were then randomly allotted to pens and fed a common finishing ration. Contrasts were written to evaluate direct and maternal breed effects and individual heterosis in the PROC MIXED procedure of SAS (SAS Inst. Inc., Cary, NC) using dam breed, sire breed, and year as fixed effects. Simmental direct breed effect resulted in a 26 kg heavier initial BW (P<0.05) and a 46 kg heavier final BW (P<0.05). Simmental maternal breed effect increased initial BW by 43.5 kg (P<0.05). Dry matter intake was not impacted by direct breed effects, maternal breed effects, or individual heterosis. Individual heterosis did improve G:F 3.4% (P<0.05) and residual BW gain 0.048 kg/d (P<0.05). Residual intake and BW gain tended (P=0.07) to improve as a result of individual heterosis. Residual feed intake (RFI) was impacted by direct breed effect with SM cattle having a more desirable RFI (P=0.05). Angus direct breed effect increased backfat (P<0.05) and improved marbling score by 126 units (P<0.05). Simmental direct breed effect increased LM area (P<0.05), had the highest HCW at 410 kg (P<0.05), and had the most desirable yield grade at 2.74 (P<0.05). Individual heterosis improved marbling score (P=0.05). Maternal breed effect increased HCW (P<0.05) as a result of the SM dam. Direct breed effects were present for performance, feed efficiency measures, and carcass traits. Overall, heterosis impacted feedlot performance, carcass characteristics, and feed efficiency, which impacts beef

  8. Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions

    PubMed Central

    2016-01-01

    Recent studies of children's tool innovation have revealed that there is variation in children's success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by children's performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that children's innovation was predicted by specific personal characteristics. PMID:26926280

  9. Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions.

    PubMed

    Beck, Sarah R; Williams, Clare; Cutting, Nicola; Apperly, Ian A; Chappell, Jackie

    2016-03-19

    Recent studies of children's tool innovation have revealed that there is variation in children's success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by children's performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that children's innovation was predicted by specific personal characteristics. © 2016 The Authors.

  10. Efficient Estimation of Mutation Rates during Individual Development by Minimization of Chi-Square.

    PubMed

    Ai, Shi-Meng; Gao, Jian-Jun; Liu, Shu-Qun; Fu, Yun-Xin

    2015-01-01

    Mutation primarily occurs when cells divide and it is highly desirable to have knowledge of the rate of mutations for each of the cell divisions during individual development. Recently, recessive lethal or nearly lethal mutations which were observed in a large mutation accumulation experiment using Drosophila melanogaster suggested that mutation rates vary significantly during the germline development of male Drosophila melanogaster. The analysis of the data was based on a combination of the maximum likelihood framework with numerical assistance from a newly developed coalescent algorithm. Although powerful, the likelihood based framework is computationally highly demanding which limited the scope of the inference. This paper presents a new estimation approach by minimizing chi-square statistics which is asymptotically consistent with the maximum likelihood method. When only at most one mutation in a family is considered the minimization of chi-square is simplified to a constrained weighted minimum least square method which can be solved easily by optimization theory. The new methods effectively eliminates the computational bottleneck of the likelihood. Reanalysis of the published Drosophila melanogaster mutation data results in similar estimates of mutation rates. The new method is also expected to be applicable to the analysis of mutation data generated by next-generation sequencing technology.

  11. Prediction of individual combined benefit and harm for patients with atrial fibrillation considering warfarin therapy: a study protocol

    PubMed Central

    Li, Guowei; Holbrook, Anne; Delate, Thomas; Witt, Daniel M; Levine, Mitchell AH; Thabane, Lehana

    2015-01-01

    Introduction Clinical prediction rules have been validated and widely used in patients with atrial fibrillation (AF) to predict stroke and major bleeding. However, these prediction rules were not developed in the same population, and do not provide the key information that patients and prescribers need at the time anticoagulants are being considered—what is the individual patient-specific risk of both benefit (decreased stroke) and harm (increased major bleeding). In this study, our primary objective is to develop and validate a prediction model for patients’ individual combined benefit and harm outcomes (stroke, major bleeding and neither event) with and without warfarin therapy. Our secondary outcome is all-cause mortality. Methods and analysis We will use data from the Kaiser Permanente Colorado (KPCO) anticoagulation management databases and electronic medical records. Patients with a primary or secondary diagnosis during an ambulatory KPCO medical office visit, emergency department visit, or inpatient stay between 1 January 2005 and 31 December 2012 with no AF diagnosis in the previous 180 days will be included. Patients’ demographic characteristics, laboratory data, comorbidities, warfarin medication data and concurrent use of medication will be used to construct the prediction model. For primary outcomes (stroke with no major bleeding, and major bleeding with no stroke), we will perform polytomous logistic regression to develop a prediction model for patients’ individual combined benefit and harm outcomes, taking neither event group as the reference group. As regards death, we will use Cox proportional hazards regression analysis to build a prediction model for all-cause mortality. Ethics and dissemination This study has been approved by the KPCO Institutional Review Board and the Hamilton Integrated Research Ethics Board. Results from this study will be published in a peer-reviewed journal electronically and in print. The prediction models may aid

  12. Both Nearest Neighbours and Long-term Affiliates Predict Individual Locations During Collective Movement in Wild Baboons

    PubMed Central

    Farine, Damien R.; Strandburg-Peshkin, Ariana; Berger-Wolf, Tanya; Ziebart, Brian; Brugere, Ivan; Li, Jia; Crofoot, Margaret C.

    2016-01-01

    In many animal societies, groups of individuals form stable social units that are shaped by well-delineated dominance hierarchies and a range of affiliative relationships. How do socially complex groups maintain cohesion and achieve collective movement? Using high-resolution GPS tracking of members of a wild baboon troop, we test whether collective movement in stable social groups is governed by interactions among local neighbours (commonly found in groups with largely anonymous memberships), social affiliates, and/or by individuals paying attention to global group structure. We construct candidate movement prediction models and evaluate their ability to predict the future trajectory of focal individuals. We find that baboon movements are best predicted by 4 to 6 neighbours. While these are generally individuals’ nearest neighbours, we find that baboons have distinct preferences for particular neighbours, and that these social affiliates best predict individual location at longer time scales (>10 minutes). Our results support existing theoretical and empirical studies highlighting the importance of local rules in driving collective outcomes, such as collective departures, in primates. We extend previous studies by elucidating the rules that maintain cohesion in baboons ‘on the move’, as well as the different temporal scales of social interactions that are at play. PMID:27292778

  13. Peer Assessments of Normative and Individual Teacher-Student Support Predict Social Acceptance and Engagement among Low-Achieving Children

    ERIC Educational Resources Information Center

    Hughes, Jan N.; Zhang, Duan; Hill, Crystal R.

    2006-01-01

    This study used hierarchical linear modeling to predict first grade students' peer acceptance, classroom engagement, and sense of school belonging from measures of normative classroom teacher-student support and individual teacher-student support. Participants were 509 (54.4% male) ethnically diverse, first grade children attending one of three…

  14. What Predicts the Effectiveness of Foreign-Language Pronunciation Instruction? Investigating the Role of Perception and Other Individual Differences

    ERIC Educational Resources Information Center

    Kissling, Elizabeth M.

    2014-01-01

    This study investigated second language (L2) learners' perception of L2 sounds as an individual difference that predicted their improvement in pronunciation after receiving instruction. Learners were given explicit pronunciation instruction in a series of modules added to their Spanish as a foreign language curriculum and were then tested on their…

  15. How Does Early Developmental Assessment Predict Academic and Attentional-Behavioural Skills at Group and Individual Levels?

    ERIC Educational Resources Information Center

    Valtonen, Riitta; Ahonen, Timo; Tolvanen, Asko; Lyytinen, Paula

    2009-01-01

    The main aim of the study was to explore the ability of a brief developmental assessment to predict teacher-rated learning and attentional and behavioural skills in the first grade of school at both the group and individual levels. A sample of 394 children (181 males, 213 females) aged 4 years were followed to the age of 6 years, and 283 of the…

  16. Predicting Individual Differences in Attention, Memory, and Planning in First Graders from Experiences at Home, Child Care, and School

    ERIC Educational Resources Information Center

    Developmental Psychology, 2005

    2005-01-01

    This study adds to the growing literature linking children's experiences in the environment to individual differences in their developing skills in attention, memory, and planning. The authors asked about the extent to which stimulating and sensitive care in the family and in the child-care or school environments would predict these cognitive…

  17. Why Harmless Sensations Might Hurt in Individuals with Chronic Pain: About Heightened Prediction and Perception of Pain in the Mind

    PubMed Central

    Hechler, Tanja; Endres, Dominik; Thorwart, Anna

    2016-01-01

    In individuals with chronic pain harmless bodily sensations can elicit anticipatory fear of pain resulting in maladaptive responses such as taking pain medication. Here, we aim to broaden the perspective taking into account recent evidence that suggests that interoceptive perception is largely a construction of beliefs, which are based on past experience and that are kept in check by the actual state of the body. Taking a Bayesian perspective, we propose that individuals with chronic pain display a heightened prediction of pain [prior probability p(pain)], which results in heightened pain perception [posterior probability p(pain|sensation)] due to an assumed link between pain and a harmless bodily sensation [p(sensation|pain)]. This pain perception emerges because their mind infers pain as the most likely cause for the sensation. When confronted with a mismatch between predicted pain and a (harmless bodily) sensation, individuals with chronic pain try to minimize the mismatch most likely by active inference of pain or alternatively by an attentional shift away from the sensation. The active inference results in activities that produce a stronger sensation that will match with the prediction, allowing subsequent perceptual inference of pain. Here, we depict heightened pain perception in individuals with chronic pain by reformulating and extending the assumptions of the interoceptive predictive coding model from a Bayesian perspective. The review concludes with a research agenda and clinical considerations. PMID:27826271

  18. The predictive value of arterial stiffness on major adverse cardiovascular events in individuals with mildly impaired renal function

    PubMed Central

    Han, Jie; Wang, Xiaona; Ye, Ping; Cao, Ruihua; Yang, Xu; Xiao, Wenkai; Zhang, Yun; Bai, Yongyi; Wu, Hongmei

    2016-01-01

    Objectives Despite growing evidence that arterial stiffness has important predictive value for cardiovascular disease in patients with advanced stages of chronic kidney disease, the predictive significance of arterial stiffness in individuals with mildly impaired renal function has not been established. The aim of this study was to evaluate the predictive value of arterial stiffness on cardiovascular disease in this specific population. Materials and methods We analyzed measurements of arterial stiffness (carotid–femoral pulse-wave velocity [cf-PWV]) and the incidence of major adverse cardiovascular events (MACEs) in 1,499 subjects from a 4.8-year longitudinal study. Results A multivariate Cox proportional-hazard regression analysis showed that in individuals with normal renal function (estimated glomerular filtration rate [eGFR] ≥90 mL/min/1.73 m2), the baseline cf-PWV was not associated with occurrence of MACEs (hazard ratio 1.398, 95% confidence interval 0.748–2.613; P=0.293). In individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2), a higher baseline cf-PWV level was associated with a higher risk of MACEs (hazard ratio 2.334, 95% confidence interval 1.082–5.036; P=0.031). Conclusion Arterial stiffness is a moderate and independent predictive factor for MACEs in individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2). PMID:27621605

  19. What Predicts the Effectiveness of Foreign-Language Pronunciation Instruction? Investigating the Role of Perception and Other Individual Differences

    ERIC Educational Resources Information Center

    Kissling, Elizabeth M.

    2014-01-01

    This study investigated second language (L2) learners' perception of L2 sounds as an individual difference that predicted their improvement in pronunciation after receiving instruction. Learners were given explicit pronunciation instruction in a series of modules added to their Spanish as a foreign language curriculum and were then tested on their…

  20. Developmental Trajectories in Toddlers' Self-Restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

    ERIC Educational Resources Information Center

    Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

    2011-01-01

    We examined whether self-restraint in early childhood predicted individual differences in 3 executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of approximately 950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not…

  1. Predicting Children's Interactions with Unfamiliar Peers: Contributions of Parent-Child Interaction Style and Child Individual Behavior.

    ERIC Educational Resources Information Center

    Carrillo, Sonia; And Others

    This study examined children's play interaction styles with unfamiliar peers; used mother-child and father-child dyadic qualities independently to predict children's social behavior; determined the relationship between children's individual behaviors and peer dyadic characteristics; and compared mother-child and father-child interactions on both…

  2. Developmental Trajectories in Toddlers' Self-Restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

    ERIC Educational Resources Information Center

    Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

    2011-01-01

    We examined whether self-restraint in early childhood predicted individual differences in 3 executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of approximately 950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not…

  3. Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

    NASA Astrophysics Data System (ADS)

    Koehler, Sarah Muraoka

    Industrial large-scale control problems present an interesting algorithmic design challenge. A number of controllers must cooperate in real-time on a network of embedded hardware with limited computing power in order to maximize system efficiency while respecting constraints and despite communication delays. Model predictive control (MPC) can automatically synthesize a centralized controller which optimizes an objective function subject to a system model, constraints, and predictions of disturbance. Unfortunately, the computations required by model predictive controllers for large-scale systems often limit its industrial implementation only to medium-scale slow processes. Distributed model predictive control (DMPC) enters the picture as a way to decentralize a large-scale model predictive control problem. The main idea of DMPC is to split the computations required by the MPC problem amongst distributed processors that can compute in parallel and communicate iteratively to find a solution. Some popularly proposed solutions are distributed optimization algorithms such as dual decomposition and the alternating direction method of multipliers (ADMM). However, these algorithms ignore two practical challenges: substantial communication delays present in control systems and also problem non-convexity. This thesis presents two novel and practically effective DMPC algorithms. The first DMPC algorithm is based on a primal-dual active-set method which achieves fast convergence, making it suitable for large-scale control applications which have a large communication delay across its communication network. In particular, this algorithm is suited for MPC problems with a quadratic cost, linear dynamics, forecasted demand, and box constraints. We measure the performance of this algorithm and show that it significantly outperforms both dual decomposition and ADMM in the presence of communication delay. The second DMPC algorithm is based on an inexact interior point method which is

  4. Ultralow mode-volume photonic crystal nanobeam cavities for high-efficiency coupling to individual carbon nanotube emitters

    PubMed Central

    Miura, R.; Imamura, S.; Ohta, R.; Ishii, A.; Liu, X.; Shimada, T.; Iwamoto, S.; Arakawa, Y.; Kato, Y. K.

    2014-01-01

    The unique emission properties of single-walled carbon nanotubes are attractive for achieving increased functionality in integrated photonics. In addition to being room-temperature telecom-band emitters that can be directly grown on silicon, they are ideal for coupling to nanoscale photonic structures. Here we report on high-efficiency coupling of individual air-suspended carbon nanotubes to silicon photonic crystal nanobeam cavities. Photoluminescence images of dielectric- and air-mode cavities reflect their distinctly different mode profiles and show that fields in the air are important for coupling. We find that the air-mode cavities couple more efficiently, and estimated spontaneous emission coupling factors reach a value as high as 0.85. Our results demonstrate advantages of ultralow mode-volumes in air-mode cavities for coupling to low-dimensional nanoscale emitters. PMID:25420679

  5. Ultralow mode-volume photonic crystal nanobeam cavities for high-efficiency coupling to individual carbon nanotube emitters.

    PubMed

    Miura, R; Imamura, S; Ohta, R; Ishii, A; Liu, X; Shimada, T; Iwamoto, S; Arakawa, Y; Kato, Y K

    2014-11-25

    The unique emission properties of single-walled carbon nanotubes are attractive for achieving increased functionality in integrated photonics. In addition to being room-temperature telecom-band emitters that can be directly grown on silicon, they are ideal for coupling to nanoscale photonic structures. Here we report on high-efficiency coupling of individual air-suspended carbon nanotubes to silicon photonic crystal nanobeam cavities. Photoluminescence images of dielectric- and air-mode cavities reflect their distinctly different mode profiles and show that fields in the air are important for coupling. We find that the air-mode cavities couple more efficiently, and estimated spontaneous emission coupling factors reach a value as high as 0.85. Our results demonstrate advantages of ultralow mode-volumes in air-mode cavities for coupling to low-dimensional nanoscale emitters.

  6. Predicting individual change in personality disorder features by simultaneous individual change in personality dimensions linked to neurobehavioral systems: the longitudinal study of personality disorders.

    PubMed

    Lenzenweger, Mark F; Willett, John B

    2007-11-01

    Personality disorders (PDs), long thought to be immutable over time, show considerable evidence of individual change and malleability in modern prospective longitudinal studies. The factors responsible for the evident individual change in PDs over time, however, remain essentially unknown. A neurobehavioral model that posits negative emotion (NEM), nonaffective constraint (CON), communal positive emotion (PEM-C), and agentic positive emotion (PEM-A) as important systems underlying PD provides a theoretical basis for investigating predictors of change in PD features over time. Thus, in this study, the authors investigated how individual change in NEM, CON, PEM-C, and PEM-A over time predicted individual change in PD features over time, using longitudinal data on PD assessed by the International Personality Disorders Examination (A. W. Loranger, 1999), as well as data on normal personality features gathered within a 4-year prospective multiwave longitudinal study (N = 250). The authors used the method of latent growth modeling to conduct their analyses. Lower initial levels of PEM-C predicted initial levels of the growth trajectories for those with elevated Cluster A PD features. Elevated NEM, lower CON, and elevated PEM-A initial levels were found to characterize the initial levels of growth trajectories for those with increased Cluster B PD features. Interestingly, subjects with higher initial levels of PEM-A revealed a more rapid rate of change (declining) in Cluster B PD features over time. Elevated NEM and decreased PEM-C initial levels were found to characterize the growth trajectories for subjects with increased Cluster C PD features. The substantive meaning of these results is discussed, and the methodological advantages offered by this statistical approach are also highlighted.

  7. Deriving the species richness distribution of Geotrupinae (Coleoptera: Scarabaeoidea) in Mexico from the overlap of individual model predictions.

    PubMed

    Trotta-Moreu, Nuria; Lobo, Jorge M

    2010-02-01

    Predictions from individual distribution models for Mexican Geotrupinae species were overlaid to obtain a total species richness map for this group. A database (GEOMEX) that compiles available information from the literature and from several entomological collections was used. A Maximum Entropy method (MaxEnt) was applied to estimate the distribution of each species, taking into account 19 climatic variables as predictors. For each species, suitability values ranging from 0 to 100 were calculated for each grid cell on the map, and 21 different thresholds were used to convert these continuous suitability values into binary ones (presence-absence). By summing all of the individual binary maps, we generated a species richness prediction for each of the considered thresholds. The number of species and faunal composition thus predicted for each Mexican state were subsequently compared with those observed in a preselected set of well-surveyed states. Our results indicate that the sum of individual predictions tends to overestimate species richness but that the selection of an appropriate threshold can reduce this bias. Even under the most optimistic prediction threshold, the mean species richness error is 61% of the observed species richness, with commission errors being significantly more common than omission errors (71 +/- 29 versus 18 +/- 10%). The estimated distribution of Geotrupinae species richness in Mexico in discussed, although our conclusions are preliminary and contingent on the scarce and probably biased available data.

  8. Predicted versus measured photosynthetic water-use efficiency of crop stands under dynamically changing field environments.

    PubMed

    Xu, Liu-Kang; Hsiao, Theodore C

    2004-11-01

    Water-use efficiency (WUE) is critical in determining the adaptation and productivity of plants in water-limited areas, either under the present climate or future global change. Data on WUE are often highly variable and a unifying and quantitative approach is needed to analyse and predict WUE for different environments. Hsiao has already proposed a set of paradigm equations based on leaf gas exchange for this purpose, calculating WUE (ratio of assimilation to transpiration) relative to the WUE for a chosen reference situation. This study tests the validity and applicability of these equations to cotton and sweet corn stands with full canopies in the open field. Measured were evapotranspiration and downward flux of atmospheric CO2 into the canopy, soil CO2 efflux, canopy temperature, and CO2 and vapour pressure of the air surrounding the canopy. With the measured mean WUE and conditions at midday serving as the reference, WUE for other times was predicted from the air CO2 and water vapour data, intercellular water vapour pressure calculated from canopy temperature, and an assumed ratio of Ci/Ca based on leaf gas-exchange data. Provided that the stomatal response to humidity as it affected the Ci/Ca ratio was accounted for, the equations predicted the moment-by-moment changes in canopy WUE of cotton over daily cycles reasonably well, and also the variation in midday WUE from day-to-day over a 47 d period. The prediction for sweet corn was fairly good for most parts of the day except the early morning. Measurement uncertainties and possible causes of the differences between predicted and measured WUE are discussed. Overall, the results indicate that the equations may be suitable to simulate changes in WUE without upscaling, and also demonstrate clearly the importance of stomatal response to humidity in determining stand WUE in the field.

  9. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry V.; Schifer, Nicholas A.; Briggs, Maxwell H.

    2012-01-01

    The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using

  10. Protein β-sheet prediction using an efficient dynamic programming algorithm.

    PubMed

    Sabzekar, Mostafa; Naghibzadeh, Mahmoud; Eghdami, Mahdie; Aydin, Zafer

    2017-10-01

    Predicting the β-sheet structure of a protein is one of the most important intermediate steps towards the identification of its tertiary structure. However, it is regarded as the primary bottleneck due to the presence of non-local interactions between several discontinuous regions in β-sheets. To achieve reliable long-range interactions, a promising approach is to enumerate and rank all β-sheet conformations for a given protein and find the one with the highest score. The problem with this solution is that the search space of the problem grows exponentially with respect to the number of β-strands. Additionally, brute-force calculation in this conformational space leads to dealing with a combinatorial explosion problem with intractable computational complexity. The main contribution of this paper is to generate and search the space of the problem efficiently to reduce the time complexity of the problem. To achieve this, two tree structures, called sheet-tree and grouping-tree, are proposed. They model the search space by breaking it into sub-problems. Then, an advanced dynamic programming is proposed that stores the intermediate results, avoids repetitive calculation by repeatedly uses them efficiently in successive steps and reduces the space of the problem by removing those intermediate results that will no longer be required in later steps. As a consequence, the following contributions have been made. Firstly, more accurate β-sheet structures are found by searching all possible conformations, and secondly, the time complexity of the problem is reduced by searching the space of the problem efficiently which makes the proposed method applicable to predict β-sheet structures with high number of β-strands. Experimental results on the BetaSheet916 dataset showed significant improvements of the proposed method in both execution time and the prediction accuracy in comparison with the state-of-the-art β-sheet structure prediction methods Moreover, we investigate

  11. Maximising the efficiency of clinical screening programmes: balancing predictive genetic testing with a right not to know

    PubMed Central

    Schuurman, Agnes G; van der Kolk, Dorina M; Verkerk, Marian A; Birnie, Erwin; Ranchor, Adelita V; Plantinga, Mirjam; van Langen, Irene M

    2015-01-01

    We explored the dilemma between patients' right not to know their genetic status and the efficient use of health-care resources in the form of clinical cancer screening programmes. Currently, in the Netherlands, 50% risk carriers of heritable cancer syndromes who choose not to know their genetic status have access to the same screening programmes as proven mutation carriers. This implies an inefficient use of health-care resources, because half of this group will not carry the familial mutation. At the moment, only a small number of patients are involved; however, the expanding possibilities for genetic risk profiling means this issue must be addressed because of potentially adverse societal and financial impact. The trade-off between patients' right not to know their genetic status and efficient use of health-care resources was discussed in six focus groups with health-care professionals and patients from three Dutch university hospitals. Professionals prefer patients to undergo a predictive DNA test as a prerequisite for entering cancer screening programmes. Professionals prioritise treating sick patients or proven mutation carriers over screening untested individuals. Participation in cancer screening programmes without prior DNA testing is, however, supported by most professionals, as testing is usually delayed and relatively few patients are involved at present. Reducing the number of 50% risk carriers undergoing screening is expected to be achieved by: offering more psychosocial support, explaining the iatrogenic risks of cancer screening, increasing out-of-pocket costs, and offering a less stringent screening programme for 50% risk carriers. PMID:25564039

  12. Maximising the efficiency of clinical screening programmes: balancing predictive genetic testing with a right not to know.

    PubMed

    Schuurman, Agnes G; van der Kolk, Dorina M; Verkerk, Marian A; Birnie, Erwin; Ranchor, Adelita V; Plantinga, Mirjam; van Langen, Irene M

    2015-09-01

    We explored the dilemma between patients' right not to know their genetic status and the efficient use of health-care resources in the form of clinical cancer screening programmes. Currently, in the Netherlands, 50% risk carriers of heritable cancer syndromes who choose not to know their genetic status have access to the same screening programmes as proven mutation carriers. This implies an inefficient use of health-care resources, because half of this group will not carry the familial mutation. At the moment, only a small number of patients are involved; however, the expanding possibilities for genetic risk profiling means this issue must be addressed because of potentially adverse societal and financial impact. The trade-off between patients' right not to know their genetic status and efficient use of health-care resources was discussed in six focus groups with health-care professionals and patients from three Dutch university hospitals. Professionals prefer patients to undergo a predictive DNA test as a prerequisite for entering cancer screening programmes. Professionals prioritise treating sick patients or proven mutation carriers over screening untested individuals. Participation in cancer screening programmes without prior DNA testing is, however, supported by most professionals, as testing is usually delayed and relatively few patients are involved at present. Reducing the number of 50% risk carriers undergoing screening is expected to be achieved by: offering more psychosocial support, explaining the iatrogenic risks of cancer screening, increasing out-of-pocket costs, and offering a less stringent screening programme for 50% risk carriers.

  13. Prediction of leaf area in individual leaves of cherrybark oak seedlings (Quercus pagoda Raf.)

    Treesearch

    Yanfei Guo; Brian Lockhart; John Hodges

    1995-01-01

    The prediction of leaf area for cherrybark oak (Quercus pagoda Raf.) seedlings is important for studying the physiology of the species. Linear and polynomial models involving leaf length, width, fresh weight, dry weight, and internodal length were tested independently and collectively to predict leaf area. Twenty-nine cherrybark oak seedlings were...

  14. Description and prediction of individual tree biomass on pinon (Pinus edulis) in northern New Mexico

    Treesearch

    Mark Loveall; John T. Harrington

    2008-01-01

    The purpose of this study was to gain reliable information on the distribution of aboveground biomass of an important component of the woodlands of north-central New Mexico, and to develop prediction equations that may be used to quickly compute biomass from relatively simple field measurements. Improved understanding of and ability to predict aboveground biomass...

  15. A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field

    PubMed Central

    Hou, Jiateng; Sun, Yingfei; Sun, Lixin; Pan, Bingyu; Huang, Zhipei; Wu, Jiankang; Zhang, Zhiqiang

    2016-01-01

    This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint angle calculated by fusion of acceleration and angular rate using an extended Kalman filter (EKF) and muscle activations obtained from the sEMG signals were taken as the inputs of the proposed NMS model to determine individual muscle force. The result shows that our NMS model can predict individual muscle force accurately, with the ability to reflect subject-specific joint dynamics and neural control solutions. Our method incorporates sEMG and motion data, making it possible to get a deeper understanding of neurological, physiological, and anatomical characteristics of human dynamic movement. We demonstrate the potential of the proposed NMS model for evaluating the function of upper limb movements in the field of neurorehabilitation. PMID:27916853

  16. Individual-learning ability predicts social-foraging strategy in house sparrows.

    PubMed

    Katsnelson, Edith; Motro, Uzi; Feldman, Marcus W; Lotem, Arnon

    2011-02-22

    Social foragers can use either a 'producer' strategy, which involves searching for food, or a 'scrounger' strategy, which involves joining others' food discoveries. While producers rely on personal information and past experience, we may ask whether the tendency to forage as a producer is related to being a better learner. To answer this question, we hand-raised house sparrow (Passer domesticus) nestlings that upon independence were given an individual-learning task that required them to associate colour signal and food presence. Following the testing phase, all fledglings were released into a shared aviary, and their social-foraging tendencies were measured. We found a significant positive correlation between individual's performance in the individual-learning task and subsequent tendency to use searching (producing) behaviour. Individual-learning score was negatively correlated with initial fear of the test apparatus and with body weight. However, the correlation between individual learning and searching remained significant after controlling for these variables. Since it was measured before the birds entered a social group, individual-learning ability could not be the outcome of being a producer. However, the two traits may be initially associated, or individual learning could facilitate producing behaviour. To our knowledge, this is the first evidence that associates individual-learning abilities with social-foraging strategies in animal groups.

  17. Resting EEG in Alpha and Beta Bands Predicts Individual Differences in Attentional Blink Magnitude

    ERIC Educational Resources Information Center

    MacLean, Mary H.; Arnell, Karen M.; Cote, Kimberly A.

    2012-01-01

    Accuracy for a second target (T2) is reduced when it is presented within 500 ms of a first target (T1) in a rapid serial visual presentation (RSVP)--an attentional blink (AB). There are reliable individual differences in the magnitude of the AB. Recent evidence has shown that the attentional approach that an individual typically adopts during a…

  18. Resting EEG in Alpha and Beta Bands Predicts Individual Differences in Attentional Blink Magnitude

    ERIC Educational Resources Information Center

    MacLean, Mary H.; Arnell, Karen M.; Cote, Kimberly A.

    2012-01-01

    Accuracy for a second target (T2) is reduced when it is presented within 500 ms of a first target (T1) in a rapid serial visual presentation (RSVP)--an attentional blink (AB). There are reliable individual differences in the magnitude of the AB. Recent evidence has shown that the attentional approach that an individual typically adopts during a…

  19. Correlation Equation for Predicting the Single-Collector Contact Efficiency of Colloids in a Horizontal Flow.

    PubMed

    Li, Jing; Xie, Xiaohu; Ghoshal, Subhasis

    2015-07-07

    The single-collector contact efficiency (η0) for physicochemical colloid filtration under horizontal flow in saturated porous media was calculated using trajectory analysis in three dimensions. Past studies have developed correlation equations for colloids with densities close to that of water, such as bacteria and latex particles. A new correlation equation was developed for predicting η0 based on a large number of trajectory simulations to account for higher-density particles representative of metal colloids. The correlation equation was developed by assuming Brownian diffusion, interception, and gravitational sedimentation contributed to η0 in an additive manner. Numerical simulations for colloid trajectory analysis used for calculating η0 were based on horizontal flow around a collector under the action of van der Waals attractive forces, gravity, and hydrodynamic forces as well as Brownian motion. The derived correlation equation shows excellent agreement with existing correlation equations for particles with density close to that of water. However, the correlation equation presented in this study shows that η0 of high-density colloids, such as metal particles, transported under horizontal flow deviates from that predicted by existing correlations for colloids larger than 4 μm and under low approach velocities. Simulations of trajectory paths show that a significantly reduced contact of high-density colloids larger than 4 μm in size with a collector is due to gravity forces causing trajectory paths to deviate away from the underside of collectors. The new correlation equation is suitable for predicting the single collector efficiency of large particles (several hundred nanometers to several micrometers) and with a large amount of density transport in the horizontal flow mode but is unsuitable for particles with a quite small size (several to tens of nanometers) and for the particle with a large amount of density flow in the vertical flow mode. The

  20. Field swimming behavior in largemouth bass deviates from predictions based on economy and propulsive efficiency.

    PubMed

    Han, Angela X; Berlin, Caroline; Ellerby, David J

    2017-09-15

    Locomotion is energetically expensive. This may create selection pressures that favor economical locomotor strategies, such as the adoption of low-cost speeds and efficient propulsive movements. For swimming fish, the energy expended to travel a unit distance, or cost of transport (COT), has a U-shaped relationship to speed. The relationship between propulsive kinematics and speed, summarized by the Strouhal number (St=fA/U, where f is tail beat frequency, A is tail tip amplitude in m and U is swimming speed in m s(-1)), allows for maximal propulsive efficiency where 0.2predicted to minimize their COT. This may reflect speed modulation to meet competing functional demands such as enabling effective prey detection and capture. St exceeded the optimal range for the lowest observed swimming speeds. Mechanical and physiological constraints may prevent adoption of efficient St during low-speed swimming. © 2017. Published by The Company of Biologists Ltd.

  1. Distribution Patterns Predict Individual Specialization in the Diet of Dolphin Gulls

    PubMed Central

    Masello, Juan F.; Wikelski, Martin; Voigt, Christian C.; Quillfeldt, Petra

    2013-01-01

    Many animals show some degree of individual specialization in foraging strategies and diet. This has profound ecological and evolutionary implications. For example, populations containing diverse individual foraging strategies will respond in different ways to changes in the environment, thus affecting the capacity of the populations to adapt to environmental changes and to diversify. However, patterns of individual specialization have been examined in few species. Likewise it is usually unknown whether specialization is maintained over time, because examining the temporal scale at which specialization occurs can prove difficult in the field. In the present study, we analyzed individual specialization in foraging in Dolphin Gulls Leucophaeus scoresbii, a scavenger endemic to the southernmost coasts of South America. We used GPS position logging and stable isotope analyses (SIA) to investigate individual specialization in feeding strategies and their persistence over time. The analysis of GPS data indicated two major foraging strategies in Dolphin Gulls from New I. (Falkland Is./Islas Malvinas). Tagged individuals repeatedly attended either a site with mussel beds or seabird and seal colonies during 5 to 7 days of tracking. Females foraging at mussel beds were heavier than those foraging at seabird colonies. Nitrogen isotope ratios (δ15N) of Dolphin Gull blood cells clustered in two groups, showing that individuals were consistent in their preferred foraging strategies over a period of at least several weeks. The results of the SIA as well as the foraging patterns recorded revealed a high degree of specialization for particular feeding sites and diets by individual Dolphin Gulls. Individual differences in foraging behavior were not related to sex. Specialization in Dolphin Gulls may be favored by the advantages of learning and memorizing optimal feeding locations and behaviors. Specialized individuals may reduce search and handling time and thus, optimize their

  2. Use of community versus individual socioeconomic data in predicting variation in hospital use.

    PubMed

    Hofer, T P; Wolfe, R A; Tedeschi, P J; McMahon, L F; Griffith, J R

    1998-06-01

    (1) To examine the association of socioeconomic characteristics (SES) with hospitalization by age group, and when using measures of SES at the community as opposed to the individual level. (2) Thus, to support the inference that socioeconomic factors are important in the analysis of small area utilization data and address potential criticisms of this conclusion. The 1989 Michigan Inpatient Database (MIDB), the 1990 U.S. Census, the 1989 Area Resource File (ARF), and the 1990 National Health Interview Survey (NHIS). A qualitative comparison of socioeconomic predictors of hospitalization in two cross-sectional analyses when using community as opposed to individual socioeconomic characteristics was done. DATA EXTRACTION. Hospitalizations (excluding delivery) were extracted by county from the MIDB and by individual from the NHIS. SES variables were extracted from the U.S. Census for communities and from the NHIS for individuals. Measures of employment for communities were from the ARF and information on health insurance and health status of individuals from the NHIS. Both analyses show similar age-specific patterns for income and education. The effects were greatest in young adults, and diminished with increasing age. Accounting for multiple admissions did not change these conclusions. In the individual-level data the addition of variables representing health and insurance status substantially diminished the size of the coefficients for the socioeconomic variables. By comparison to parallel individual-level analyses, small area analyses with community-level SES characteristics appear to represent the effect of individual-level characteristics. They are also not substantially affected by the inability to track individuals with multiple readmissions across hospitals. We conclude that the impact of SES characteristics on hospitalization rates is consistent when measured by individual or community-level measures and varies substantially by age. These variables should be

  3. An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

    PubMed

    Kundu, Kousik; Backofen, Rolf

    2017-01-01

    Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

  4. An Efficient Interval Type-2 Fuzzy CMAC for Chaos Time-Series Prediction and Synchronization.

    PubMed

    Lee, Ching-Hung; Chang, Feng-Yu; Lin, Chih-Min

    2014-03-01

    This paper aims to propose a more efficient control algorithm for chaos time-series prediction and synchronization. A novel type-2 fuzzy cerebellar model articulation controller (T2FCMAC) is proposed. In some special cases, this T2FCMAC can be reduced to an interval type-2 fuzzy neural network, a fuzzy neural network, and a fuzzy cerebellar model articulation controller (CMAC). So, this T2FCMAC is a more generalized network with better learning ability, thus, it is used for the chaos time-series prediction and synchronization. Moreover, this T2FCMAC realizes the un-normalized interval type-2 fuzzy logic system based on the structure of the CMAC. It can provide better capabilities for handling uncertainty and more design degree of freedom than traditional type-1 fuzzy CMAC. Unlike most of the interval type-2 fuzzy system, the type-reduction of T2FCMAC is bypassed due to the property of un-normalized interval type-2 fuzzy logic system. This causes T2FCMAC to have lower computational complexity and is more practical. For chaos time-series prediction and synchronization applications, the training architectures with corresponding convergence analyses and optimal learning rates based on Lyapunov stability approach are introduced. Finally, two illustrated examples are presented to demonstrate the performance of the proposed T2FCMAC.

  5. An efficient approach for site-specific scenery prediction in surveillance imaging near Earth's surface

    NASA Astrophysics Data System (ADS)

    Jylhä, Juha; Marjanen, Kalle; Rantala, Mikko; Metsäpuro, Petri; Visa, Ari

    2006-09-01

    Surveillance camera automation and camera network development are growing areas of interest. This paper proposes a competent approach to enhance the camera surveillance with Geographic Information Systems (GIS) when the camera is located at the height of 10-1000 m. A digital elevation model (DEM), a terrain class model, and a flight obstacle register comprise exploited auxiliary information. The approach takes into account spherical shape of the Earth and realistic terrain slopes. Accordingly, considering also forests, it determines visible and shadow regions. The efficiency arises out of reduced dimensionality in the visibility computation. Image processing is aided by predicting certain advance features of visible terrain. The features include distance from the camera and the terrain or object class such as coniferous forest, field, urban site, lake, or mast. The performance of the approach is studied by comparing a photograph of Finnish forested landscape with the prediction. The predicted background is well-fitting, and potential knowledge-aid for various purposes becomes apparent.

  6. Perceived control predicting the recovery of individual-specific walking behaviours following stroke: testing psychological models and constructs.

    PubMed

    Bonetti, D; Johnston, M

    2008-09-01

    Perceived control predicts activity limitations, but there are many control belief concepts and how these are defined and measured has implications for intervention design. This study examined whether individual-specific activity limitations and recovery were predicted by theoretically derived control conceptualizations, the Theory of Planned Behaviour and an integrated model (Theory of Planned Behaviour with the World Health Organization ICF (International Classification of Functioning, Disability and Health) model). This predictive cohort study used measures of impairment, intention and perceived control (perceived behavioural control, Theory of Planned Behaviour; self-efficacy, Social Cognitive Theory; locus of control, Social Learning Theory), assessed 2 weeks after hospital discharge, to predict walking limitation (UK SIP: FLP) and recovery after 6 months. Theoretically derived items were individually tailored for patients' baseline walking limitation. Two hundred and three stroke patients (124 men and 79 women; mean age = 68.88, SD = 12.31 years) Walking limitation and walking recovery (respectively) were predicted by perceived behavioural control (r = -.36(**), .26(**)) and self-efficacy (r = -.30(**), .22(**)), but not locus of control (r = -.07, .02). Both theoretical models accounted for significant variance in walking limitation and recovery--but not beyond that explained by perceived behavioural control. Predictive power was not improved by modifying the control component or by including impairment in regression equations. Results suggest that perceived control predicts individual-specific disability and recovery and that reductions in activity limitations may be achieved by manipulating control cognitions. In addition, reducing impairments may not have maximal effect on reducing disability unless beliefs about control over performing the behaviour are also influenced.

  7. Predicting an Individual’s Physiologic State without a Crystal Ball

    DTIC Science & Technology

    2008-04-05

    RT) CGM # of Diabetes Sampling Frequency (min)Device* Subjects Type iSense 9 1 1 DexCom 7 2 5 Guardian RT 18 1 5 Glucose Prediction for Type 1 & 2...40.5 41 Prediction 95% Prediction interval Measurement Time, hh:mm *Data provided by Ken Ward (iSense), Robert Vigersky ( DexCom ), Direcnet (Guardian...Diabetes - three studies using distinct continuous glucose monitoring ( CGM ) devices - Collection Time (days) 5 56 6 Time (min) G l u c o s e ( m g / d

  8. A Multidimensional Risk Score to Predict All-Cause Hospitalization in Community-Dwelling Older Individuals With Obstructive Lung Disease.

    PubMed

    Beijers, Rosanne J H C G; van den Borst, Bram; Newman, Anne B; Yende, Sachin; Kritchevsky, Stephen B; Cassano, Patricia A; Bauer, Douglas C; Harris, Tamara B; Schols, Annemie M W J

    2016-06-01

    Both respiratory and nonrespiratory hospitalizations are common and costly events in older individuals with obstructive lung disease. Prevention of any hospitalization in these individuals is essential. We aimed to construct a prediction model for all-cause hospitalization risk in community-dwelling older individuals with obstructive lung disease. We studied 268 community-dwelling individuals with obstructive lung disease (defined as FEV1/FVCprediction model for 9-year all-cause hospitalization risk using a weighted linear combination based on beta coefficients. There were 225 individuals with 1 or more hospitalizations and 43 individuals free from hospitalization during the follow-up. Heart and vascular disease (H), objectively measured lower extremity dysfunction (O), systemic inflammation (S), dyspnea (P), impaired renal function (I), and tobacco exposure (T) were independent predictors for all-cause hospitalization (ALL). These factors were combined into the HOSPITALL score (0-23 points), with an area under the curve in ROC analysis of 0.70 (P < .001). The hazard ratio for all-cause hospitalization per 1-point increase in the HOSPITALL score was 1.15 (95% confidence interval, 1.11-1.19, P = .001). Increasing HOSPITALL score was further associated with shorter time to first admission, increased admission rate, and